White Paper on Industrial Experience with MDO

Transcription

1 White Paper on Industrial Experience with MDO White Paper on Industrial Experience with MDO The new white Paper on industrial experience with MDO consists of several invited papers and a summary report from the 1998 Symposium on Multidisciplinary Analysis and Optimization. Invited Papers: The Role of MDO within Aerospace Design and Progress towards an MDO Capability, Peter Bartholomew (Defence Evaluation and Research Agency, UK). Issues in Industrial Multidisciplinary Optimization, J. Bennett, P. Fenyes, W. Haering, M. Neal (GM). MDO Technology Needs in Aeroelastic Structural Design, H. G. Hönlinger (German Aerospace Center) and J. Krammer and M. Stettner (Daimler-Benz Aerospace). Multidiscipline Design as Applied to Space, Charles F. Lillie, Michael J. Wehner and Tom Fitzgerald (TRW). (1 of 3)12/29/ :28:17 PM

2 White Paper on Industrial Experience with MDO Multidisciplinary Design Practices from the F-16 Agile Falcon, Michael H. Love (Lockheed Martin). The F-22 Structural/Aeroelastic Design Process with MDO Examples, Nick Radovcich and David Layton (Lockheed Martin). A Collaborative Optimization Environment for Turbine Engine Development, Peter J. Röhl, Beichang He, Peter M. Finnigan (GE CR&D). Boeing Rotorcraft Experience with Rotor Design and Optimization, Frank Tarzanin, Darrell K. Young (Boeing). The Challenge and Promise of Blended-Wing-Body Optimization, Sean Wakayama (Boeing) and Ilan Kroo (Stanford). (2 of 3)12/29/ :28:17 PM

3 White Paper on Industrial Experience with MDO A Description of the F/A-18E/F Design and Design Process, James A. Young, Ronald D. Anderson, and Rudolph N. Yurkovich (Boeing, St. Louis). Summary paper: A Summary of Industry MDO Applications and Needs, Joseph P. Giesing (Boeing) and Jean-Francois M. Barthelemy (NASA Langley). Presentation. Paper. Back to MDO TC Home Page Last Updated: August 10, 1999 Michael Eldred, mseldre@sandia.gov (3 of 3)12/29/ :28:17 PM

4 THE ROLE OF MDO WITHIN AEROSPACE DESIGN AND PROGRESS TOWARDS AN MDO CAPABILITY Peter Bartholomew Defence Evaluation and Research Agency, Farnborough, Hampshire GU14 0LX United Kingdom AIAA ABSTRACT This paper reviews recent progress made in MDO within the European aerospace industry through the activities of a sequence of international collaborative partnerships of increasing complexity. Firstly, a definition of MDO is provided and its function as a key tool in the context of concurrent engineering is discussed. Issues addressed include the limited support given by many MDO tools to detail stressing, validation of aeroelastic optimisation, the role of product models, the definition and execution of MDO process under user control and trade-off studies for requirement capture. The need for the adoption of standards in the definition of the product model and the likely impact of the CALS philosophy of create data once and use many times are highlighted. INTRODUCTION Multidisciplinary design optimisation enables the efficiency of designs to be optimised and supports trade-off studies between the design objectives of diverse disciplines. The MDO process is intended for use within the context of modern engineering design environment, which is characterised by the commercial imperative to reduce time cycles and costs. These commercial pressures, together with the immense volume of design, manufacturing and maintenance data inherent to complex modern equipment, demand a heavily computerised environment. Current practice, as exemplified by Concurrent Engineering (CE), is to move the design of complex equipment away from a process involving a sequence of specialist departments and to emphasise its multidisciplinary nature through the use of integrated product teams. Both the structural integrity of engineering products and demonstration of the performance of proposed designs are increasingly reliant on the use of DERA Fellow, Aero/Structures Dept, AIAA Member British Crown Copyright (1999), DERA. Published with permission of the Controller of Her Majecsty s Stationary Office computer models created during the design process. Although the software tools existing within individual disciplines may be reasonably mature, the challenge is now to provide the tools necessary to support such an integrated approach. The scope of multidisciplinary design optimisation (MDO) is limited to the design of products based on the simulation of physical objects in their environment. The use of multiple simulations is a key concept of MDO. This may involve diverse tools such as: fluid flow solvers (to determine local and overall external forces); structural analysis and detail stressing (to determine structural deformations and internal stresses); electromagnetic analysis (to determine radar signatures from local and overall returns from incident beams); cost modelling and tools for design for reliability. The physics modelling may be mathematical or experimental but the simulation of human interaction effects, for example through the use of flight simulators, is excluded. At a general level, when considering the overall mission performance of an aircraft, tools exist to aid the conceptual design of both military and civil aircraft and are used during the early stages of the project. Although these adopt a fully multidisciplinary approach, only the simplest, Level 1, empirical models are employed to approximate the physics which influences the overall design. Currently most MDO applications, for use in the preliminary design phases of a project, are based on major simplifications in mathematical modelling at level 2, such as beam structural models or panel methods for aerodynamics. The objective is now to achieve the same degree of integration with level 3, state-of-the-art analyses. The limiting factor in the use of such best, proven models is the capacity of current computation technology. Analyses using computational fluid dynamics, computational electro-mechanics, or detailed finite element models are separately capable of pressing computer resources to the limit, and this is compounded by the introduction of sensitivity calculations and 1 American Institute of Aeronautics and Astronautics

5 optimisation. It is evident from conferences devoted to MDO 1-3 that the move to higher fidelity analysis tools, which have formerly been the preserve of specialist departments, is general. The software framework one may require to control such a process, user interface issues and the form of product data used to support design, manufacture and operation are discussed in this paper in the context of a series of MDO collaborative activities within the European Aerospace industry. While the conceptual design tools referenced above tend to be close-coupled, it is of interest that the tools used in the various collaborations have all been loosely coupled. STRUCTURAL OPTIMISATION GARTEUR SM(AG13) Detail design One of the problems in introducing MDO is the complexity of the design process itself. Even within the single discipline of structures, finite element programs will be supplemented by a range of data sheets, detail stressing programs and manual methods, all used to establish structural integrity. It is essential for the credibility of an MDO process that it should be able to accommodate the detailed design processes normally used within the company. The GARTEUR Structures and Materials panel has supported collaborative research activities on Structural Optimisation from 1990 onwards. In particular the GARTEUR Action Group SM(AG13) addressed the use of panel design codes within the overall strength and stiffness design process for aircraft wings. Here, even within the context of a single discipline, the MDO-related issue of multilevel design arises, since the FE-based codes, commonly used to improve overall wing efficiency, may be supplemented by codes for detailed panel stability design and assessment, applied on a panel by panel basis. Codes for the buckling design of composite panels l t skin-ply b t strg-ply Fig. 1 : Dimensions of compression panel h were available from DASA Airbus, NLR and U.Cardiff and others were purpose-written as required. Structural optimisation codes were available from BAe, DASA, SAAB, Dornier, Aerospatiale, NLR and DERA. The major codes were presented by their originators and compared, and multilevel methods for the integration of panel and overall structural optimisation were investigated. (Top skin omitted) Bottom skin Front spar Middle spar Rear spar 'Lumped' stringers Fig. 2 : Simple wing model The methods developed were evaluated using civil and military aircraft wings of differing complexity as benchmark problems 4, the simplest being that shown in figure 2. A larger problem of a commuter-aircraft wing, from DASA Airbus, is regarded as an industrialscale problem and the development of strategies for exploiting composite materials in compression structure were regarded as important. Overall it was found to be possible to include the detailed design of composite stiffened wing panels against buckling within the overall strength and stiffness design process for the wing using relatively simple strategies, although it is acknowledged that interaction effects between adjacent panels are not addressed by these methods. MULTIDISCIPLINARY DESIGN OPTIMISATION OF AIRCRAFT WINGS GARTEUR SM(AG21) Aeroelastic Optimisation GARTEUR Action Group SM(AG21) on multidisciplinary wing design concentrates upon the integration of strength and aeroelastic aspects of the design of high aspect ratio wings typical of modern regional transport aircraft, as illustrated in figure 3. The DERA contribution is based on the use of the inhouse structural optimisation code, STARS 5 which, like several others, embodies aeroelastics as a tightlycoupled functionality. Both the aeroelastic predictions and design strategies to come out of the optimisation 2 American Institute of Aeronautics and Astronautics

6 will be compared with those of the other partners within the group. Fig. 3 GARTEUR SM(AG21) model While several European companies have long had the capability of combining aeroelastic design with basic strength requirements within the context of what are principally structural design codes, the progress of a follow-on GARTEUR Action Group is discussed in providing a forum for the validation and comparison of the capabilities of various companies. Such comparison is felt to be important since, from other collaborative projects, it has been found that significantly different solutions can found by different groups MDO OF AEROSPACE VEHICLES EU IMT PROJECT BE Project outline The MDO project represented a first step into multidisciplinary analysis and design optimisation for many of the partners. The application selected to demonstrate new capabilities developed during the project was based on the A3xx concept currently under development by the Airbus partners. A whole aircraft model was provided for aeroelastic and controls studies, but the design activity was focused upon the wing. The project was subdivided into a series of tasks shown in figure 5. All partners participated in the definition tasks 1-3 and from then on separate groups were responsible for the investigations conducted by tasks 4-7. The project was supported by the software infrastructure group working in task 8 in which participating partners were drawn from each of these task groups. The final stage of the activity was to draw together the lessons learnt from the project as recommendations in task 9. Aerodynamic and Structural design The objective of the work was to develop and demonstrate a capability for the aerodynamic and structural design of a wing which would minimise the direct operating cost (DOC) of the A3xx concept aircraft. The form chosen for the DOC was simply a linear combination of mass and drag relative to that of the reference aircraft viz ( ) DOC = 10. W D econ Task 1: Task 2: Task 4: Planform Optimisation Task 8: Project Management Simplified MDO process Task 3: Primary Sensitivity Study Task 5: Surface-shape Optimisation Task 6: Structural Optimisation Prototype MDO framework Task 9: Recommendations Fig. 5 : Task structure for EU MDO project Task 7: Control Optimisation where W is the mass in tonnes and D the drag in counts. The majority of the optimisation work performed was based on the use of a few gross wing design parameters, namely: area, aspect ratio, rear spar location, sweep, crank thickness and tip twist. The initial work conducted by the partners in Task 5 was simply to optimise the wing with respect to the two surface shape parameters, crank thickness and tip twist, and to compare results for aerodynamic drag and structural mass corresponding to this baseline case 8. The optimisation results in figure 7 3 American Institute of Aeronautics and Astronautics

7 show a considerable variation between partners. In particular, significant differences are found depending upon the treatment of fuselage effects and the design of a wing in isolation also changed significantly when the wing was treated as part of a trimmed aircraft model. Such differences are not a simple matter of right and wrong, but rather depend upon an understanding of the important characteristics of the flow and of the limitations of the various numerical approaches. At this stage in the development of MDO there is little or no interest in close-coupled black-box methods. A strong need was perceived to use familiar legacy codes within a loose-coupled modular framework that enabled the output from every process to be evaluated before proceeding. While differences in the aerodynamics provide the main contribution to the variation of results, similar difficulties are also encountered resolving differences of design arising from the structural optimisation, despite this being regarded as a relatively mature technology. A reasonable consensus was achieved for the finite element results, but the optimisation, particularly that of the commercial codes, tended to be oversensitive to details of the method selected and parameter settings and did not necessarily converge to optimum solutions. The DERA-specific work introduced multiple flight conditions into the optimisation. Aerodynamic analysis Fig. 9 : Spanwise distribution of lift for heavy cruise sis of the wing is performed at light, economic and heavy cruise and the drag calculated is combined with the mass given by structural optimisation, to give an estimate of direct operating cost in the form ( ) DOC = 10. W D D D light econ heavy Some of the trends were similar in the single and multiple condition optimisation. In particular it was noticeable that the lift moves slightly inboard as in figure 9. This changes the trim of the aircraft, reducing the downforce required on the tailplane, and hence decreases the total lift of the wing. This results in a reduction in the lift-induced drag for all flight conditions. Tip twist Reference Wing+fuse -1 Wing only Wing+c/s -2 Wing / no trim Wg+c/s / no trim Crank thickness Fig. 7 : Optimum designs calculated for baseline problem At both economic and heavy cruise conditions there is a weakening of the shock waves which also tend to move inboard. The reduced contribution to the total drag from the shock wave drag is particularly important for heavy cruise. Optimising the wing for the economic cruise condition, in the hope that the design will also prove satisfactory at light and heavy cruise, gives poor results in heavy cruise condition. By optimising the wing for multiple cruise conditions, the drag at heavy cruise is improved without losing the improvement at the other flight conditions. 4 American Institute of Aeronautics and Astronautics

8 This task illustrates the need for flexibility within an MDO process, to allow the user to configure the optimisation process to accommodate multiple assessment tools, specific to each problem. Product models and TDMB The complexity of the data flow which links the disciplines of aerodynamics and structures, is illustrated in figure 10. This starts with a requirements system, which is assumed to be external to the MDO system, in which some freedom is assumed to exist to fine-tune the relative importance of various aspects of performance. An outline concept is then developed as a parameterised product model. This is followed by various assessments, here shown as aerodynamics and structures, with the possibility of making detailed shape and thickness changes for a given configuration. Referring to figure 10, it is clear that large amounts of data, which may well be stored in separate databases, must be communicated between the component parts of the MDO system. The key issue for data transfer is the setting of common standards for the interpretation of information across disciplines. For MDO, the standards must cover all aspects of product geometry definition and design requirements, together with specific discipline-based data that reflects the constraints upon the design. During the early meetings of the MDO project, a series of key activities were decided upon which defined the nature of the project. One was to adopt the BAe program TDMB 7 (Technical Data Modeller & Browser) as the repository for the product model. TDMB provides a text editor user interface which supports an definition of data objects and then expands to store instance data capable of representing several variants of the product together with performance data derived from aerodynamic and structural analysis. A fully parameterised representation of the aircraft configuration was developed, with tools to generate aerodynamic data, finite element models and aeroelastic models used for performance assessment. This data-representation serves the project by providing partners with a common product model upon which design studies were based. The data models defined in TDMB will be exportable to the STEP/EXPRESS data definition language to enable future migration to other systems which conform to evolving standards for product models. The wider use of data which conforms with the STEP standards 6 is an important element of achieving the CALS objective of creating data once and using many times through the product life cycle. MDO process A major factor which will influence the overall success of any MDO implementation is the approach adopted to the co-ordination and scheduling of the diverse range of activities necessary to complete a full design cycle. This aspect of MDO must be adequately defined in the early stages of the development process in order to draw together the different disciplines and allow concepts to be explored. A framework specification document was written by the Task 8 partners and various software tools were provided. These include tools for: software version management, data definition, database technology, process definition, process execution on distributed networks, data visualisation and optimisation. Several alternate frameworks were employed and evaluated against the user and system requirements previously developed. The frameworks assessed included commercial MDO frameworks and toolsets, a process-driven Workflow Management tool and Network middleware. The frameworks tended to operate with a pre-defined sequence of operations and failed to provide the user with sufficient flexibility to reconfigure the process during the early exploratory phases of a design study. The interactive definition of a complex process is a prime requirement of any optimisation framework. The strength of work flow management tool is the traceability and control it offers, whereby only approved users may initiate processes and that only provided the input data has not been invalidated by changes by an upstream process. Network middleware systems enabled the computer resources of the network of machines to be utilised with the facility that one may expect of a single machine, but tended to require userintervention and were weak at running chained processes. As may be expected the purpose-written MDO frameworks provided the most flexible integration support but did not necessarily distinguish the process support aspects (including the registration of tools, the definition of process chains and their execution) from data management (product models and requirements) or from embedded tools (for the visualisation of various categories of data or optimisation functionality). Further development is needed if the frameworks are to operate in a standards driven environment accessing data from corporate data bases. 5 American Institute of Aeronautics and Astronautics

9 Problem set up User Requirements System 00 Requirements data 1. Case set-up 01 Case data 04b Structural response 2. Computeraided design 06a New detail shape 06 New parameters 02 Product description 06b New thicknesses 3a. CFD grid generator Aerodynamics 01 Case data 3b. Finite element pre-processor Structures 03a Multiblock FD grid 03bFinite Element data 4a. Flow solver Euler or N-S 4b. Finite element analysis 04a Aero pressures 04b Structural response 5a. Flow assessment 5b. Structural assessment 05b Lift & drag 05b Struct performance 6a. Airfoil section optimisation 06a New detail shape 6b. Structural Optimisation 06b New thicknesses 07b Structural mass Multi-discipline trade-offs 5. Multi-discipline assesssment 05 Mass, lift & drag 6. Multi-discipline optimisation 07 Pareto Frontier 06 New parameters Revision of requirements 7. Capture design decisions 00 New requirements Fig. 10 : Data flow showing multidisciplinary tools 6 American Institute of Aeronautics and Astronautics

10 The role of the optimiser The role of the optimiser has also been the subject of slight variation within the various partner frameworks. At the simplest, the optimiser calls for function evaluations, possibly including gradients, at a sequence of design points and, in effect, controls the process. As the function evaluations call for increasingly timeconsuming analyses with complex data interactions and, possibly, requiring user-intervention, this becomes a less attractive option. An alternative approach is still to start the design cycle with the optimiser initiating a design change, but to return control to the framework for the performance assessment phase. The optimiser must then be capable of being restarted once the performance assessment is complete. In software terms, the optimiser may then appear as just another MDO process, to be called as required, but its controlling role within the process of design should still be recognised. FRONTIER / ESPRIT PROJECT Project outline Finally the contribution of the EU project Frontier 9 towards the capture of requirements is described. It is almost inevitable that any MDO problem, as initially formulated, will not automatically lead to the required product, since impact of constraints and the balance of conflicting requirements will not be fully understood at the outset. In this project, a Pareto-frontier approach is used together with multi-criterion decision making (MCDM) software to capture customer preferences. Clearly, if cost were a criterion, this leads to a cost/performance assessment which is a key input to any requirement capture process. Although Frontier is a relatively small project, it is of the widest scope in that it considers design against multiple objectives. The project partners consist of universities who are, in the main, acting as suppliers of new technology and industrial partners who are providing user trials relevant to their industry sector. Fig. 12: DERA user trial model 7 American Institute of Aeronautics and Astronautics

11 Fig. 13 : PARETO boundary Requirement capture for military aircraft The user trial to be conducted by DERA in partnership with BAe is based on the design of a military wing and seeks to achieve an acceptable compromise between aircraft range and turn performance. Figure 12 shows the pressure distribution calculated from CFD on the left with the finite element mesh and loading derived from it on the right. In this instance the aerodynamic model is taken as the master model, but in the longer term it would be expected that both the aerodynamics and structures models would be derived from a common product model. The approach taken is a multilevel Pareto-optimisation in which the wing thicknesses (wing-box depth) at various stations are used as top-level variables linking the structures and aerodynamic disciplines. The structural optimisation simply the sizes the composite covers and sub-structure for each geometry, while the aerodynamic optimisation modifies the airfoil shape to maximise a weighted sum of lift to drag ratios corresponding to a supersonic turn condition and transonic cruise. The supersonic turn rate and transonic range shown in figure 13 are then calculated from the drag, mass and fuel volumes. Each curve corresponds to a given spanwise thickness distribution but with the aerodynamic shape optimised to give differing levels of transonic to supersonic performance. In general the thicker wings give greater range due to their increased fuel capacity, but ultimately (case 9) higher drag will reduce the range. The Pareto frontier itself, indicated in grey in figure 13, bounds the region in which it is possible to design products to meet the conflicting requirements. The best products have performance characteristics which lie close to the top-right part of the boundary. From here it is only possible to improve one characteristic at the expense of the other. The use of genetic algorithms is to be assessed as a method of achieving convergence to the boundary of the region. Typically such direct search methods require many function evaluations, each one of which will call on a full structural optimisation for mass as well as an aerodynamic minimisation of drag for two flight conditions. The fact that these tasks are computationally intensive makes the activity appropriate for high-performance computing in the longer term, but to reduce the computing costs during this project, response surfaces have been calculated for the wing mass and drag. The Pareto frontier may then be calculated on the basis of 8 American Institute of Aeronautics and Astronautics

12 the cheaper response surface information rather than from further calls to the underlying design software. This will enable sufficient computing resources to be devoted to the assessment of genetic algorithms within the Pareto frontier approach and to evaluating the MCDM software tool for deducing the weightings attached to the various design objectives from customer preferences. This aspect of the Frontier project is of particular interest as it extends the scope of MDO so that it assists with identification of the design requirements that the product should meet. CONCLUSIONS A number of developments relevant to the practical use of MDO have been identified By reference to a sequence of collaborative research activities within European aerospace industry. A definition of MDO as incorporating state-of-the-art analysis tools is provided and its function as a key tool in the context of concurrent engineering is discussed. It is believed essential for the credibility of an MDO process that it should be able to accommodate the detailed design processes normally used by engineers within the company to assess and validate their products. Scepticism as to the results from each step of an MDO process is vital and the comparative studies conducted by partnership have often produced widely varying results. The validation of methods such as within the GARTEUR activity on aeroelastic design is seen as an essential activity. The central the role of the product model is highlighted and the desirability of using STEP to standardise the form in which product data is shared and exchanged amongst processes is to be emphasised. A good framework for MDO which provides a flexible user interface for the definition, execution and monitoring of MDO processes is essential and further development of clear architectures for such software is still required. While conceptual design tools are often close-coupled, loosely coupled systems appear to be more appropriate to MDO in that they assist the verification of results by specialists. Some loss in process efficiency or even the generation of sub-optimal designs is acceptable provided the design process is understood and credible. The use of trade-off studies and Pareto optimisation methods to assist in the capture of requirements also offers worthwhile benefits. MDO is seen as providing the means to avoid the fragmentation inherent in established methods which extends the time required for the design cycle and limits the efficiency of final designs. MDO permits the constraints of a diverse range of disciplines to be reflected from the earliest stages of the design process. This approach will facilitate the design of higher performance products with improved cost, structural integrity and maintainability. The methods will also offer the opportunity to maximise the exploitation of new materials technology within designs while minimising risk, and will have significant impact on project design times and cost. ACKNOWLEDGMENTS Work referenced in this paper was funded under contracts BE and ESPRIT of the European Community, by the UK DTI CARAD programme and by the UK MOD corporate research programme. REFERENCES 1 NASA Workshop on MDO; Hampton VA, March 13-16, th AIAA/NASA/ISSMO Symposium on MDO Bellevue WA, September 4-6, th Congress of the International Council of the Aeronautical Sciences; Sorrento, Naples, September 8-13, Final Report of the Garteur Action Group on Structural Optimisation SM(AG13), GARTEur TP078 & TP079, DERA/AS/ASD/TR97015 (Feb 1997). 5 Bartholomew P, Vinson S; STARS: Mathematical Foundations; In Software Systems for Structural Optimisation, Birkhauser Verlag, Basel ISO 10301, STEP, 7 Allwright S, Technical Data Management for collaborative Multidiscipline Optimisation, AIAA , 6th Symposium on Multidisciplinary Analysis and Optimization, Seattle WA, Sept A.Gould, Surface shape optimisation, MDO/TR/BAE/AG980105, The FRONTIER Project, ESPRIT Project American Institute of Aeronautics and Astronautics

13 Issues in Industrial Multidisciplinary Optimization J. Bennett, P. Fenyes, W. Haering, M. Neal Body Engineering and Integration Department General Motors Research and Development Center Mound Road Warren, MI Abstract Several mathematically based multidisciplinary design strategies are illustrated with an exploratory multidisciplinary analysis and optimization package on a simple example problem. These examples are used to motivate a discussion of required data handling and processing modules. These requirements envision a situation where some disciplines may have computationally expensive analysis capabilities and where not all disciplines have easily available approximations for all required quantities Introduction There are generally two areas of development in multidisciplinary optimization and design systems. The first is the formal mathematical approach that is generally characterized by the work presented at the Multidisciplinary Design and Optimization Conferences. The second is a more ad hoc approach which is evolving from the traditional design and analysis communities and is typified more by a Multidisciplinary Analysis capability that is evolving in the commercial CAD and CAE environments. These environments envision a common parametric description of the artifact and an ability to generate input information for several disciplines from this format. Then analyses will be performed using complex commercial or proprietary codes and decisions made on how to modify the initial design. This process is usually characterized by significant human interaction to develop the artifact model, generate the analysis models, execute the analysis models and finally to examine the output and make decisions. The formal mathematical approach tends to use much simpler and easily modified local analysis methods (that execute on the order of minutes or seconds) and to concentrate on multidisciplinary design algorithms which interact with the analysis methods in an almost automatic fashion. Copyright c 1998 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. This paper will discuss some of the issues associated with developing an industrial, rapid, multidisciplinary design system that makes use of some aspects of modern multidisciplinary optimization research while being constrained by analysis software packages that do not all have consistent local optimization capabilities and are not easily modified. The work is conducted in the experimental Integrated Vehicle Design Analysis (IVDA) system that has been developed at GM R&D Center over the past few years. This system was described in some detail in [1]. Only that detail which is critical to the present discussion will be included here. A flow chart of the complete system is shown in Figure 1. This system envisions a parametric description format that for a specific instantiation of the parameters will generate a common vehicle description that in turn is used to generate input for an extensive set of disciplinary analysis capabilities. Note that this vehicle database contains more than just a geometric description of the vehicle in that it includes materials and their properties as well as mass and inertia characteristics of various components. The geometric design parameters include both global vehicle dimension and component structural dimensions as shown in Figure 2. The various analysis tools represent a range of capabilities. There are both commercial and proprietary codes and some disciplines have design (optimization) capabilities and others do not. The analysis capabilities in each discipline were selected to represent a preliminary analysis capability. In most cases they represent neither the simplest nor the most complex analysis capability in each discipline. They do characterize the current state of computer based engineering analysis. An initial goal of the system was to be able to complete one full analysis cycle in 24 hrs. For many of the disciplines the development of the input data is considered to be the major time constraint. For this reason, highly automated model generation methods based on templates were developed in each discipline. 1 American Institute of Aeronautics and Astronautics

14 Templates User Input Library Data Parametric Modeler Vehicle Database Discipline Modelers Elastic Structures ODYSSEY, NASTRAN Crashworthiness LPM, DYNA3D External Aerodynamics GM Program Solar Load GM Program Occupant Dynamics CAL3D Suspension Loads ADAMS Fuel Economy GM Program Other Analyses* Discipline Analysis & Sensitivity Calculations Results Database Multidisciplinary Optimization Figure 1. IVDA System Modules and Flow LD LB LR h LA LF b LH FH RH GC FO L WB RO Figure 2. Overall Body Parameters and Typical Structural Parameters 2 American Institute of Aeronautics and Astronautics

15 As will be discussed later, an experimental multidisciplinary optimization capability has been added to the IVDA system. One of the goals of this system was to be able to examine several alternative ways of implementing the design strategy. For that reason there are currently few enforced sequences in the system and the control of the execution of the various modules are under the control of the various discipline and coordination human operators. To illustrate various aspects of this design process and its implementation in IVDA, we will begin by showing several examples. Each example is based on the simple problem outlined below but each uses a different design strategy. The final part of the report will discuss the technology used to implement these capabilities and some of its implications. Examples The example problem considered is to find a rear overhang (RO) that maximizes fuel economy. The available design variables are the total vehicle length (which in this parametric model expresses rear overhang since all quantities forward of the rear of the vehicle such as rear wheel location are not functions of the total length) and the traditional beam cross section sizing dimensions. The shape, other than lengthening, of the rear of the vehicle is not considered. The underlying mechanics of the problem are that as the vehicle is lengthened, the drag will go down, which would tend to increase fuel economy. However, the mass of the vehicle increases which decreases the fuel economy. In addition, increasing the length of the vehicle decreases the fundamental bending and torsion frequencies. If these frequencies are below their target values, additional mass may be required for structural stiffening to bring the frequency back to its requirement. In IVDA the structural analysis and design is handled by using a beam spring model and using the ODYSSEY/NASTRAN [2] programs to calculate response and gradients (sensitivities) and optimize mass for given constraints. An analysis takes approximately 10 minutes on a workstation and an optimization 1-3 hours. The aerodynamic drag is calculated by a neural net fit to test data so it is essentially instantaneous. Similarly, the fuel economy calculation is a rapid spread sheet calculation. Because both the aerodynamic and fuel economy calculations could have been replaced with more accurate and time consuming calculations, we will treat the process as if all three of the calculations required significant amounts of time. The flow of data is shown in Figure 3. Front Overhang Structural Analysis Mass Drag (C d ) Aero Analysis Section Sizes Frequencies Fuel Economy Analysis Figure 3. Information Flow in Example Problems The traditional way to work this problem would be that every time information is required, a full cycle through the analysis is performed. That is full aerodynamic and structure calculations need to be made to calculate drag (C d ) and the structural mass must be adjusted to reflect any frequency requirements, then a fuel economy calculation can be made. Some design or optimization process would drive these calculations. Because this approach tends to require many calls to the analysis process, this tends to be a rather inefficient way to approach the solution. Given the capabilities in a system such as IVDA, the above problem might be implemented in several more efficient ways, three of which we will illustrate. Each of these mimics a non-computer-based design strategy. In Example 1 the disciplines are only asked to provide local response information and after some point in the process are told to execute a design using only local design variables and local constraints. In Example 3, a roll down of requirements is initiated from the beginning, and much local design work is executed, but some iteration at the global level is required. Example 2 is an intermediate approach that makes use of local directional (sensitivity) information to guide the global design. This is often 3 American Institute of Aeronautics and Astronautics

16 proposed as an initial step in flowing down requirements. Table 1. No Initial Local Design Information Step Length Fuel C d Mass Frequency Economy (>25) mm Mpg Kg Hz * * Table 2. Local Design Information Step Length Fuel C d Mass Frequency Economy (>25) mm mpg Kg Hz * * Table 3. Roll Down of Design Available Step Length Fuel C d Mass Frequency Economy (>25) mm mpg Kg Hz * * * Multidisciplinary Optimization Result Example 1: No initial local design The concept is that design variables naturally split into those that are of a global nature and those that are limited to a specific discipline. For this first strategy, only local response information is requested until the final step. This example is shown in Table 1. Step 0 represents a baseline design in which the structural cross section dimensions have been optimized for the given rear overhang (total length = 4627). The fuel economy, C d, mass, and critical frequency constraint are also reported. Since only response information is returned, a step is required to generate directional (sensitivity) information. An arbitrary perturbation of 50mm is taken in Step 1. There is now sufficient information to generate a linear approximation with respect to length for all needed quantities; such as mass, C d,frequency and fuel economy. An optimization algorithm is then applied to identify an optimum length of 4922 which is labeled Step 2. This new length is then transmitted to the analysis codes and the values of C d, mass, frequency, and fuel economy are calculated. Note that the frequency constraint of 25Hz is violated, primarily because the linear approximation was not sufficiently accurate. However, there now exists sufficient information to construct a quadratic approximation to all quantities. Using these approximations an optimization is again conducted, identifying an optimum length of When this length is returned to the analysis codes the remaining values in Step 3 are calculated. It would be possible to stop at this point, or the local analyses could conduct a local design in those variables that do not affect any of the other disciplines. In this problem this would be the cross-section design variables of the entire structure (there are 116 of these). This was done, requiring 3 additional structural analyses, and reduced the mass by 4 American Institute of Aeronautics and Astronautics

17 .2 kg which had no measurable effect on the fuel economy. This process initially used 4 analyses in each discipline plus 2 analyses and 2 sensitivity calculations in the final structural optimization. Example 2: Local information available This implementation uses more than just response information from the disciplines. The results for this approach are shown in Table 2. Step 0 is identical to Step 0 in Example 1. In the example problem, the structures disciplines can in fact generate sensitivities of the mass and frequency with respect to the cross-section design variables. The length variable is not directly known to the structures module so a sensitivity with respect to length cannot be generated. Therefore a Step 1 which is identical to the Step 1 in the first example must be made. Approximations with respect to the length (based on a linear response surface) and with respect to the section design variables (based on sensitivities for 116 variables) can now be made. The multidisciplinary optimization problem can then be solved using all 117 design variables. Only the length is shown in the table (4831). Upon re-analysis the frequency constraint was slightly violated (24.95). At this point a quadratic approximation based on length and updated sensitivity values for the section variables can be generated. The structural approximations based on length are not precisely correct because they contain now an evaluation in which the section variables as well as the length were changed. It is impractical to generate a response surface for all 117 variables since it would require a minimum of 118 analyses. Step 3 shows the results of the approximate multidisciplinary optimization (length 4848) and the subsequent full evaluations (frequency = 24.97, Fuel Economy = This process used 4 analyses in each discipline and 2 structural sensitivity calculations. Note that no final local structural optimization was performed so there remains the possibility that this final design is not precisely optimum. Example 3: Roll down of design In this implementation advantage is taken of local design capabilities. The structural discipline capability has the ability to perform optimizations (designs) which minimize the mass subject to constraints. The results are shown in Table 3. Again Step 0 is the baseline and Step 1 is the 50 mm move, however the results shown in Step 1 are for a structurally optimized design in terms of the cross-section dimensions. Also the approximations used for the multidisciplinary optimization in Step 2 are based on optimized structural designs. The Step 2 multidisciplinary optimization produced a length of When the structural optimization was again performed the frequency constraint was initially infeasible (24.32), but the local optimization was able to resolve this and the final design from Step 2 showed a frequency value of 25Hz. Now quadratic approximations can be built based on these optimized results. The multidisciplinary optimization in Step 3 then produces a value essentially identical to the length for Step 2 so we can conclude that the design has converged. This process used 4 analyses in each discipline with 6 additional analyses and sensitivity calculations for structural optimization. Discussion of Examples Because of the nature of the problem solved it is not possible to draw firm conclusions about either vehicle design trends or the nature of which design strategy is best. What has been shown is a computer implementation that will allow these multidisciplinary problems to be handled mathematically and will allow different design strategies to be applied. The following section of the paper will discuss these issues. However, first, some observations based on the examples can be made. The numerical differences among the quantities are in many cases extremely small. However, throughout the many exercises of these examples there has been sufficient consistency in the results to suggest that they are not being driven by numerical noise. All of the designs consistently allowed the length to increase, which means that the gain in fuel economy from decreased drag offsets the decrease in fuel economy due to the increase in mass. However, once the frequency constraint was encountered, the additional mass required to meet the constraint at the longer lengths eventually overrode the fuel economy gains due to the increased length. The range of final lengths ( ) and Fuel Economy ( ) suggest a rather flat optimum over a relative wide range of lengths. To reliably select a true optima from these designs is probably impossible with the available level of accuracy in the analyses. Similarly it is impossible to identify a best process from this simple example problem. All of the processes work relatively well in terms of efficiency and quality of answer since the two sets of design variables (length and section dimensions) are fairly well independent for this problem. In addition all examples were started from a structural design that was quite good (optimal) for the initial total length so the effects of large changes in the structural cross section design variables was eliminated. However, it is possible to see some of the relative strengths and weaknesses. The no local design approach appears to have the most difficulty in following the frequency constraint, but initially requires the least 5 American Institute of Aeronautics and Astronautics

18 effort from the local disciplines. It is easy to believe that in a more highly coupled problem, this could lead to inefficiencies. The second approach, which brings in local sensitivity information if available, could be considered the most efficient from the standpoint of structural analyses required, but because of the information that is to be shared, is the most complex to implement either informally or mathematically. Ultimately this process will produce a large, but potentially simple, design problem at the global level. The last process which used local design required the most local design effort (finite element analyses). This will occur when there is coupling between the disciplines that are neglected in the roll down process. As indicated previously, in order to implement and automate such a system, several new capabilities are needed. The remainder of this report will discuss these in light of the system that was used for these examples. A Multidisciplinary Design System. Parametric/design variable modeling One of the fundamental issues for successfully implementing a computer-based multidisciplinary design strategy is that each discipline must be able to communicate with other disciplines and the decision making process with the same set of design variables or parameters. If different disciplines use different descriptions of the same quantity or geometric entity they have no way to communicate, particularly mathematically. This says that some common parametric description, or a mapping among different descriptions, must exist. This was a fundamental concept of IVDA and resulted in a significant amount of the development effort. Since the early 90 s the CAD vendors have been evolving such a parametric capability for the geometric representations that they create. Similarly, some CAE vendors, notably the finite element structural analysis vendors, have been evolving optimization capabilities based on parameterized design models. It is logical that a bi-directional coupling could be established. In general this may not be easy since many disciplines have evolved their own geometric preprocessors which parameterize the discipline model in ways that are different from the CAD models. We will assume the existence of such a common parametric system in what follows since we wish to focus on the multidisciplinary design issues, however to insure appropriate implementation, it may be necessary for the MDO community to be actively involved in the evolution of this technology. Approximate Problems There is a large amount of heuristic and research information suggesting that the way engineering design is efficiently conducted is that a limited amount of high quality, time consuming, expensive information is collected and a simple approximation of this information is constructed, either heuristically or mathematically. This simple model is exercised to identify an improved design and this new design is then evaluated using the high quality and expensive method. This process is certainly used in the heuristic and test method of design and the current analysis based methods. From the research standpoint it has been well established in the structural optimization area that this approach reduces the computational effort by at least an order of magnitude for moderately complex problems. We will propose that the ability to create and handle approximations based on more refined data is required. In some disciplines highly accurate, extremely fast analyses may exist. From our standpoint these become highly accurate approximations for which no reference to a more accurate analysis need be made. Multidisciplinary Design Strategy Given the above assumption that a set of approximations will be available there are several pieces to this strategy. First there will need to be some process to operate on the approximations to identify the new and improved design. Since this will operate on the cheap-to-execute approximations, we will assume that any strategy, including exhaustive search, could be used. In practice, exhaustive search many prove inefficient and the process probably would be selected to take advantage of the nature of the approximations. The next level of the strategy is how the approximations are generated. The final piece of the strategy is how the approximations, the designs based on these approximations and the more detailed analysis are interwoven. The three example problems show alternative implementations at this level of strategy. These examples suggest that one would not want to impose a strategy a priori. Clearly at the core is the concept of the approximate models built on information in what might be called the results database. Therefore, we will begin our discussion with how these approximations might be constructed and managed. We will develop the concept of the IVDA results database throughout this discussion, but it is essentially where all of the relevant information that comes from the discipline analyses is located. In the CAD environment, many product data manager (PDM) systems anticipate storing a pointer to files of completed analyses. However, to make use of this information in a 6 American Institute of Aeronautics and Astronautics

19 design system, some sort of data extraction is required. In the IVDA system, we required each discipline to supply specific subsets of their output data to the results database. The form in the results database was structured to meet the requirements of the mathematically based design processes envisioned. Although we located all of the information in one database, there is no reason that the information could not have been distributed in several discipline databases. Part of this vision was that the results database would live through several different multidisciplinary designs as opposed to one single execution of a precisely stated problem. Thus a persistent idea was that old analyses might be reused to construct new approximations for newly posed problems. A conceptual layout of the results database is shown in Figure 4. In the following sections we will discuss several types of data stored in the results database and their relationships. Response Approximations The type of an approximation that we are considering here is a calculation that takes fractions of a second to execute on whatever the current compute platform is. These would generally fall into two categories. The first is some sort of standard mathematical form that would be suitable for any discipline. Forms such as Taylor series, polynomial response surfaces, and neural nets fall into this category. The second category contains models developed for one specific discipline. These could be spreadsheets, lumped parameter models, simple discrete models, or specialized response surface or neural net models. It is anticipated that the generalized mathematical models would be generated from data that exists in the results database. The discipline specific models would be either generated or enhanced from the data in the results database. Thus we clearly need to provide capabilities to interrogate the results database to create and update these models. In IVDA we generate response approximations with up to quadratic terms using two different methods. In the first approach, we use discipline generated responses and sensitivities at a single design point to create linear response approximations. The second approach uses only the discipline generated response values at a number of points in the design space to create up to second order response surface approximations. Both types of approximations are stored in the same relation in the results database. Approximations Based on Discipline Response Sensitivities We chose to make the creation of an approximation a decision at the multidisciplinary level as opposed to the discipline level. This is so the multidisciplinary design process would understand the approximations it had available. On the other hand, we predicated the results database on the idea that a decision to place data in it was made by the local discipline. This essentially placed the burden on the local discipline to warrant that the data was correct and might have some potential value. Thus it was necessary to create a location to store discipline supplied sensitivities prior to the decision to elevate them to approximations to be used in the multidisciplinary design process. While response data can be fairly compact (responses and associated design variables), sensitivity data can be rather extensive and to store this information for each returned response may be prohibitive. For that reason, in the IVDA results database only one set of sensitivities for each discipline is kept, the last one returned. In practice this has proved cumbersome because it requires that before approximations are to be constructed, the correct response is the last one loaded. A module has been implemented which on command transfers the sensitivities for a particular response from the sensitivity relation to the approximation relation in the results database. Approximations Based on Response Surfaces Most response surface generation processes assume that they are provided with a set of responses and their corresponding sets of design variables. They then use a prescribed algorithm to develop an interpolation scheme that fits these points in some best way. Most optimization or design methods that use response surfaces presume that for every new problem, a start from no information is made and that the information to develop the response surfaces is provided (perhaps n+1 vectors of the n design variables for which the responses must first be calculated). We wish to operate in a situation in which several designs have already been created (i.e. the results database is partially populated) and we wish to use as much of the already generated information as possible. We do recognize that at any given point in time there may be insufficient information and some additional analyses may need to be executed, but we wish to minimize the amount of this that must be done. 7 American Institute of Aeronautics and Astronautics

20 CAD Master parameter model Analysis 1 Analysis 2.. Analysis n Design in progress parameter model parameter description parameter values { } response description response values linking histories Parameter set upload module Parameter values Static values Analysis 1.. Proposed new values Local design J.. MDO 1 MDO 2.. Approximate model builder sensitivities approximations MDO problem description Multidisciplinary design and optimization Figure 4. Results Database and Associated Modules To accomplish this a module was developed which for a given response will identify in the results database all designs which calculated a value for this response. It then identifies the values of the design variables associated with these responses. At this point the information is available to submit to a standard response surface generator. There is a question as to whether all of the responses in the database are good in that some could have been loaded and later determined not to be valid. For that reason, it is possible for the user to specify which of the available responses are to be included in the fit. The main difficulty with this process is associated with the potential interrelationships among the design variables. In a traditional regression approach, it is assumed that a unique set of design variables is identified and remains constant throughout the process. In this case the only concern is that the designs used for the response surface must not be linearly dependent in any fashion and there are standard methods to detect this situation. In the process proposed above these conditions cannot be guaranteed unless unreasonable restrictions are placed upon the design process. Design Variable Linking with Approximations in Multidisciplinary Design The fundamental concept in parametric modeling is that the number of degrees of design freedom are reduced by relating potential degrees of freedom to a reduced set of quantities by mathematical expressions. In the example problem described earlier the four points that describe the rear of the vehicle (upper and lower corners of the rear on each side of the vehicle) are all related to the total vehicle length. The process of constructing the relationships between potential design variables and a reduced set of actual variables for a given problem has been called linking in the optimization literature and that term will be used here. In order to allow for some amount of generality and future changes, we anticipate that it will be desirable to retain access to this extended set of potential design variables. Thus the basic set of design variables retained in the IVDA results database is not the set of design variables that are active on the current multidisciplinary design, but the complete set of design variables that is available in the template. For the examples shown earlier there are 3033 of these potential design variables. Again taking the examples described previously, the response surface module will identify that four of these variables (upper and lower, right and left) have been changed for any design that changes the rear overhang. However, for this problem, the local 8 American Institute of Aeronautics and Astronautics

21 linking specifies that all four quantities move the same distance. Since the variables are not independent, we need to fit only one variable, not four. Therefore some process must be implemented that recognizes this situation and accounts for it. In the IVDA implementation this is accomplished by creating a historical link table relation. This relation contains the links that are used in any set of responses that are returned to the results database. It should be recognized that these links could have come from the central vehicle description, or they could have been provided and/or modified by the local disciplines. The response surface generating module then checks to see if the same linking was used for all of the responses to be used. If so, the number of design variables is reduced and the appropriate variables removed from the independent variable list for fitting. This allows a correct response surface approximation to be generated. The difficulty here is that although several variables contributed to the total sensitivity calculation, all of the information is now attributed to one variable. This is fine as long as one wants to retain the current linking throughout the entire process. However, if information from another discipline did not contain this linking, and it was desired to allow linking changes in the multidisciplinary problem, difficulties could arise. Therefore it is desirable to decompose the linked, aggregated sensitivity into the components of the unlinked design variables. This can be done in an approximate sense by using the link relationships and a chain rule. Then based on the linking used in the multidisciplinary problem, the appropriate linked sensitivity can be reconstructed. For the specific example used here, the sensitivities would be equally split among the four points. This capability has been implemented. The difficulties with this approach are also obvious, since one might expect the sensitivities to be equal from side to side, but the two lower points could be expected to have different sensitivities than the two upper points. In looking at the current state of parametric modeling implementation in CAD/CAE software, it is clear that many of these situations will arise here. It is recognized that the discipline parameterization must match the vehicle parameterization in terms of the quantities that are to be communicated. It is not however realized that the relationships among these quantities will change and that an interpretable record of these relationships may need to be kept. Just as it may be appropriate for a discipline to propose a change to a parametric dimension, a discipline may want to propose a change to the way these variables are linked, and the decision making process needs a history of these proposals. Multidisciplinary Analysis with Approximations Although we are dealing with approximations, the relationships among the various approximations for each discipline are the same as for the more complex modules. Therefore the issues associated with exchanging information are the same. There are two possible situations. Information from one discipline may flow forward. That is the output from one discipline may be input for the next discipline. For instance the loads calculated by a suspension program might be the input for a structural optimization program. Similarly there may be a feed back of information in which the output of one program is needed to calculate the input for another program whose output is the input for the first program. For instance the mass calculated by the structural optimization program is needed as input to the suspension program which calculates the load input for the structural optimization program. If there is only feed forward, it is fairly easy to envision how a multidisciplinary design process would work: by properly ordering the analyses (or approximations), the outputs of the programs would be used as inputs for the following programs and all response properties could be properly calculated. An optimization capability could then be wrapped around the feed forward package. If there is any feedback present, the process is more complicated since there will need to be inner loops around these feed back loops to insure convergence of the responses before data is passed to the next step in the process. There are two approaches that might be implemented here. Since we are working with approximations that presumably execute very quickly, we could implement a full feedback and feed forward process that would express all of the interactions implied in the approximations. This in general will require developing approximations of the output quantities of each discipline module with respect to all of the input quantities, not just the design variables. For example in the example problem used here, an approximation of the fuel economy with respect to C d and mass will be needed since these are the input quantities needed by the fuel economy module (Figure 3) The second approach is through a mathematical formulation. Mathematically this situation can be 9 American Institute of Aeronautics and Astronautics

22 expressed by what are called the global sensitivity equations. dgj dxi g j g j dgk = + xi gk dxi (1) In this first order approximation sense these equations allow us to create a complete approximation, dg j /dx i, to describe the effect of a design variable x on any output quantity g in terms of both feed forward and feed back. To do this we need the traditional derivatives, g j / x i, (approximations) of any output quantity with respect to its local input variables, plus the derivatives, g j / g k, (approximations) of any output response quantity with respect to any input response quantity. This is essentially a set of linear algebraic equations that can be solved by standard matrix methods. Thus to implement either of the two approaches we need the same types of additional information, i.e. either approximations or sensitivities of response quantities with respect to input response quantities. In the example problems, we had only a feed forward problem and response/response sensitivities were only needed for the fuel economy program. We used a first order approximation, calculating the sensitivities by finite differences. This was implemented in the first approach, treating the sensitivities as an approximation, and chaining the information through the approximations. This gives the same answer as the global sensitivity equations that in the case of feed forward reduce to a chain rule. Multidisciplinary Design Strategies As indicated earlier there are multiple levels to this strategy. We have proposed an approach in which the design or optimization strategy is applied to the approximations. While virtually any optimization package could be used, we used the feasible directions strategy in ADS [3] for the examples. Any of these packages require the availability of response and perhaps sensitivity information. Some process must be devised to interface the optimization algorithms with the approximation modules as described in the previous section. While we developed a simple input format that would point to the appropriate modules, one of the newer commercial MDO oriented packages could be adapted to the task. The output from the optimization package would then be a proposed new design that must be reloaded into the high level description for reanalysis, if accepted. This brings us to the relationships between the high level vehicle description and the other parts of the process. Both IVDA and the commercial CAD packages envision a high level description of the present state of the vehicle which is the common central description which all analyses reference as their starting point. It is then envisioned that the local disciplines may explore alternative designs and propose a new set of design parameters. Most of the current CAD vendor thinking is around the process of allowing one discipline to upload its new set of parameters to the CAD model. It is unlikely, however, that all of a discipline s proposed changes would be accepted. The more likely situation is that many disciplines may propose conflicting sets of design parameters and these conflicts must be resolved before a design can be uploaded to the central description. This is essentially the job that is handled by the multidisciplinary optimization process. Obviously, there needs to be some intermediate level of data storage to handle all of these proposed new designs. The results database in IVDA stores these proposed designs from all the disciplines. No discipline can directly input its results to the vehicle database. The only way that the vehicle database (CAD model) can be updated is through the results database. A module was created that will select a complete set of design parameters in the results database and return it to the vehicle database (Figure 4). This then treats the approximate multidisciplinary optimization as just another discipline that has returned a proposed design that can be selected for return to the results database. Although it was not implemented in the current version of IVDA, it is reasonable to assume that an intermediate copy of the vehicle database will be needed to hold modifications of the design parameters that are used to construct approximations required by the design process, such as those required by the length variable in the structural discipline in the examples. This is shown in Figure 4 with broken lines. The remaining issue is how a high level multidisciplinary design strategy will interact with the approximate design strategy and the complex analyses. In the example problems this was handled by direct interaction, implementing all of the necessary executions through high level IVDA commands that provide for the input generation, execution, and transfer of the results of the various disciplines. This makes this process more time consuming than necessary, but because the exact series of steps is as yet undetermined, it seemed inappropriate to automate them, until such time as the rest of the system is more formalized. It does 10 American Institute of Aeronautics and Astronautics

23 suggest that a menu of appropriate actions should be generated to guide the user through the process. Summary By first using some simple example problems we have tried to motivate a view of a mathematically based design process that has parallels in the traditional processes. This vision involves an interplay between complex, time consuming analyses and approximations based on these analyses. It is unlikely that a single multidisciplinary design strategy will suffice for all problems. Therefore a system must evolve that will handle a number of different strategies. Three classes of issues were discussed. First, a method to share a common description of design parameters must be implemented, Associated with this is a necessity to keep track of the linking relationships among the potential set of design variables as these may change throughout the design process. Second is the need to have for each discipline a quickly executed approximation of a perhaps more complex behavior. These approximations can either be supplied by the disciplines, for example sensitivities if available, or they might be created at a higher level by examining all of the available detailed analysis results. The IVDA system was constructed explicitly to examine the latter situation and required additional sophistication to implement. Finally, if the previous two capabilities are in place, a shared set of design parameters and a shared set of approximations, the implementation of a design or optimization strategy is fairly straightforward and a wide range of strategies can be implemented including heuristic and mathematically based strategies. Acknowledgements The authors would like to acknowledge the valued contributions of V. Sankar who did much of the development programming of the multidisciplinary capability described here and who contributed to the discussions of the basic strategy. We would also like to acknowledge Bob Lust for pointing out the use of the chain rule and the linking information to develop a more generalized approximation to the decoupling of the aggregated sensitivity information. References 1. J. Bennett, et. al., A Multidisciplinary Framework for Preliminary Vehicle Analysis and Design, GM Research Publication R&D-8290, Feb 9, M. E. Botkin, et al, Structural Sizing Optimization Using an External Finite Element Program, Proceedings of 28 th Structures, Structural Dynamics and Materials Conference, AIAA, New York, G. N. Vanderplaats, H. Sugimoto, and C. M. Sprague, ADS-1: A New General-Purpose Optimization Program, Proceedings of 24 th Structures, Structural Dynamics and Materials Conference, AIAA, New York, American Institute of Aeronautics and Astronautics

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25 AIAA MDO TECHNOLOGY NEEDS IN AEROELASTIC STRUCTURAL DESIGN H.G. Hönlinger * J. Krammer M. Stettner German Aerospace Center (DLR) Göttingen, Germany Daimler-Benz Aerospace AG Munich, Germany Abstract. Increasing performance requirements and economical pressure to reduce aircraft Direct Operational Costs can no longer be met by traditional design processes. In particular, the impact of aeroelastic effects on aircraft design demands the use of multidisciplinary design concepts and optimization (MDO) strategies to develop flutterfree structures and to ensure excellent multipoint performance characteristics. This paper describes the aeroelastic and aeroservoelastic MDO problem, presents a variety of production and research level methods for its solution, and highlights current bottlenecks. Industrial MDO technology needs for aeroelastic structural design are identified by reviewing previous aeroelastic studies performed at Daimler-Benz Aerospace AG Military Aircraft Division (DASA-M) and results from a study in which several DASA-M staff members were asked to specify future analysis and MDO needs. A trend towards loosely coupled approaches is detected which is opposed by a current shortage of framework software and MDO algorithms specifically supporting industrial implementation and use. Another obstacle is the lack of standardized tool interfaces. Finally, cultural changes are required in industry to exploit the full potential of MDO. General Aeroelastic Requirements for High Performance Aircraft Design The whole spectrum of aeroelastic phenomena to be considered during the design process can be classified by means of Collar s well-known aeroelastic triangle of forces illustrated in Fig. 1. Three types of forces - aerodynamic, elastic and inertial - are involved in the aeroelastic process. Generally aeroelastic phenomena can be divided in two main groups: - static aeroelastic phenomena, which lie outside of the triangle, i.e. divergence of the structure, control effectiveness, and load distribution created by aerodynamic and elastic forces, flight mechanic stability. - dynamic aeroelastic phenomena, which lie within the triangle since they involve all three types of forces, i.e. flutter, buffeting, and dynamic response or dynamic flight stability. All of these aeroelastic phenomena have profound effects on the aircraft design and can only be solved in concurrent consideration by all disciplines involved. AERODYNAMIC FORCES STATIC AEROELASTICITY DYNAMIC STABILITY FLIGHT MECHANICS ELASTIC FORCES INERTIAL FORCES VIBRATIONS *. Director, Institute of Aeroelastics Manager Loads/Dynamics, Senior Member AIAA Research Engineer, Member AIAA Fig. 1: Collar s Aeroelastic Triangle Copyright 1998 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. 1 American Institute of Aeronautics and Astronautics

26 The flexibility of the aircraft structure is fundamentally responsible for a variety of aeroelastic phenomena and related problems. As long as the strength requirements are fulfilled, structural flexibility itself is not necessarily objectionable. The aeroelastic deformations, however, may not only strongly influence the structural dynamics and flight stability, but also the overall performance and controllability of the aircraft. Therefore in the conceptual and preliminary design phase of a new aircraft, the application of aeroelastic design criteria becomes imperative for the structural design and optimization process. The following design criteria, among others, become the standard for any aircraft design: - The aircraft must be free of flutter, divergence, and aeroelastic instability within its flight envelope - the control effectiveness must be above a given minimum to assure safe flight performance within the flight envelope - the flight shape of the wing should have minimum aerodynamic drag and sufficient effectiveness for all configurations. Despite all these design criteria in a wide range of applications the airframe design process traditionally starts with a strength design and interactions with any control system are not considered in early design phases. Aeroelastic design criteria, however, are related to flexibility. Flutter stability of strength-designed metallic wing structures therefore must often be ensured with a non optimal repair solution. During the repair process, areas on selected components like spars or attachments with beneficial impact on flutter damping are identified and reinforced. This can be accomplished by analyzing the sensitivity of stiffness and mode shapes to reinforcement 1, as shown in Fig. 2. Nodal lines of the critical modes are moved, and the flutter speed increases (Fig. 3). Only small changes to the existing design are necessary, but a weight penalty is always added - in this particular case 95 kg. Concurrent consideration of stress and flutter constraints in a complete re-design, as demonstrated in a recent European research project on MDO 2 ( MDO-Project ), has the potential to yield a feasible design with a smaller weight increase. To achieve this goal, symmetric and antimetric boundary need to be regarded simultaneously. A large number of structural optimization tools, however, do not permit this approach. As a result, full models must be used, which may render the design problem too large to handle 3. Fig. 2: Results of Sensitivity Analysis (Ref. 1) Fig. 3: Flutter Speed Increase (Ref. 1) Similar repair solutions are used for improving aeroelastic effectivenesses of lifting surfaces. Knowledge of structural bending-twist coupling, i.e. observation of the physical behavior of the structure, may be used to manipulate the stiffness distribution appropriately 4. However, interactions between different aeroelastic requirements are not obvious. An example from the above-mentioned MDO-Project shows that wing optimization with aileron effectiveness constraints may have a noticable effect on the symmetric trim of large jet transport aircraft. Hence, cross-couplings between symmetric and antimetric load cases, boundary conditions, and design requirements exist. Again, limitations of current optimization packages often prohibit simultaneous consideration of constraints from different boundary conditions. 2 American Institute of Aeronautics and Astronautics

27 Servoelastic Aspects for High Performance Aircraft Design The integration of modern electronic flight control systems (EFCS) in combination with fly-bywire technology offer the design engineers a chance to implement additional active control functions in order to gain benefits for the airframe performance. The interaction between the aircraft s flight control and additional active functions has emerged as an important design potential. This field of merging the disciplines structural dynamics, aeroelastic and flight control system dynamics is called aeroservoelasticity. The interactions are illustrated in Fig. 4. UNSTEADY AERODYNAMICS DYNAMIC AEROELASTIC STRUCTURAL DYNAMICS AEROSERVOELASTICITY AEROSERVODYNAMIC SERVOELASTIC Fig. 4: Aeroervoelastic Triangle FLIGHT CONTROL SYSTEM DYNAMICS In the aeroservoelastic triangle, the left leg represents the dynamic aeroelastic interaction which does not include inputs from an active system. Similarly, the lower leg of the triangle stands for classical aeroservodynamic control system synthesis. Finally, the right leg depicts the important dynamic servoelastic coupling between the elastic modes of the aircraft and the active control system. This coupling, together with the unsteady aerodynamic feedback inputs from servo-actuated active control surfaces, then results in an aeroservoelastic interaction which is generally known as structural coupling and can be as dangerous as flutter. To avoid dangerous instabilities aeroservoelastic design criteria have been developed for active control functions which take into account flight dynamics, structural stability, and performance as well. All active functions (control systems) have to be designed to cover full rigid and flexible aircraft frequency ranges with respect to the aircraft rigid mode and structural mode coupling stability requirements for each control system loop. The structural coupling influences will be minimized by notch filters or other measures and the control system must be as robust as possible with regard to all aircraft configurations and to all kinds of nonlinearities of the complete system flying aircraft with active controls. Additional requirements to be met within the design process are: - minimization of impact on actuator fatigue - minimization of impact on actuator back-up structures fatigue life to reduce weight penalties The most important active control functions which are mature for implementation are: - care-free handling - Maneuver Load Control (MLC) - Gust Load Alleviation (GLA) - Fatigue Life Enhancement - Deformation and Elastic Mode Control - Flutter Suppression - Ride Comfort Improvement The first experimental applications of these functions have been repair solutions in most cases to meet aircraft performance specifications. The full potential of this technology however can only be explored when it is used as design tool and fully integrated into the MDO process of active aircraft structures. At present the aeroelastic design of active aircraft structures is still the task of the future. Currently, only a patchwork of methods is available: Active flutter suppression and gust alleviation have matured from an academic to almost an industrial application level 5. In case of a controller failure, however, current certification procedures require an actively controlled aircraft to be dynamically stable with the same, significant safety margins as a purely passively controlled aircraft. Significant structural weight reductions from exploitation of active flutter suppression can therefore not be expected. It might pay off if the common 20% dive speed to flutter speed margin is valid for actively flutter-suppressed aircraft, but a reduced safety margin is accepted in the case of flutter suppression controller failure. The EFCS is usually designed and optimized for flight-dynamic stability and performance with wellestablished methods. The aircraft model in these methods is derived from rigid structure properties using aeroelastic efficiencies. Since the actual aircraft properties differ from those assumed in the 3 American Institute of Aeronautics and Astronautics

28 model - in flexibility and dynamic behavior - expensive and time-consuming adjustments are necessary. Seyffarth et. al. 6 suggest a two-step procedure to correct this discrepancy. First, sensor locations, sensor attachments, actuator transfer functions, and control surface dynamic properties are optimized. Second, notch filters and phase advance filters are designed to eliminate sensor signals from structural vibrations which could affect EFCS performance and stability. This design task is in itself a challenging optimization problem, as multiple loading and flight conditions must be considered 7. This traditional separation between low- and high frequency behavior, EFCS and structural design decomposes the design problem into manageable, discipline-conform sub-tasks, but also poses a number of costly integration challenges. Taking into account that computational power doubles per year new approaches to an integrated flight control design and optimization with respect to flight dynamics, active functions and aeroelastic stability requirements seem to become feasible. High performance computing will not only speed up the MDO process, it will start with better aircraft models and will allow the representation of multiple boundary conditions in an integrated MDO process. Previous Aeroelastic Optimization Applications, Development Trends, and Technology Gaps Table 1 provides an overview of some published DASA-M studies in the field of aeroelasticity which referred to identified shortcomings in the area of aeroelastic optimization at the time of their completion. The table is not meant to provide a summary of these studies, but a condensed account of information pertaining to the topic of this paper. The interested reader is referred to the original papers for details. The following section summarizes technology gaps which were identified in the course of these studies, outlines actions taken to close these gaps, and identifies current trends in the development of aeroelastic optimization capabilities. Selected activities in the 1980s focused on identifying and solving stability problems encountered with existing designs. Flight testing of a 1/3 scale model of the SB-13 tailless glider airplane revealed a severe low-speed instability 8. The problem was analytically traced back to coupling between the aircraft s short period oscillation and the first symmetric wing bending mode. One approach to alleviation of the instability was to use structural optimization. Limitations of the programs TSO and FASTOP, however, made modeling of this coupled flight dynamic/structural elasticity problem very difficult. It was concluded that flight dynamics must be integrated in aeroelastic optimization software. In 1986, transonic wind tunnel tests were used to validate composite fin designs obtained from structural optimization 9. In static aeroelasticity and flight dynamics commonly a linear dependency between a given aerodynamic load coefficient and a control surface deflection is assumed. This assumption is the basis of the notion of aeroelastic effectiveness, a constant factor representing the ratio of a given aerodynamic load coefficient achieved by a flexible structure compared to that of a rigid structure. This wind tunnel test, however, showed a non-linear relationship between rudder twist and stagnation pressure. The phenomenon was traced back to geometric coupling of rudder deflection and load-induced fin box deformation. Hence, flight dynamic calculations considering structural flexibility in form of stagnation pressure independent effectiveness values may be unreliable, and trimmed aeroelastic equilibrium load calculations are required. As seen from these two examples, early studies attempting to avoid aeroelastic stability problems by automatic computational design revealed that the state-of-the-art optimization tools of that time lacked several important analysis and modeling features. Structural analysis programs, on the other hand, did not have the desired open, multidisciplinary optimization features. In order to satisfy both needs, the package LAGRANGE 10 was developed at DASA- M. As a structural optimization utility by design it includes both FE-based analysis capabilities and optimization features, for example a host of optimization algorithms and analytical sensitivity calculation for a number of constraints. The software was successfully applied to optimization problems throughout the 1990s. One of the first applications was weight minimization of the above-mentioned small, simplified ACA-Fin model subject to strength, aeroelastic effectiveness, flutter and gauge constraints 11. Based on success with existing analysis capabilities, additional desirable features were formulated (refer to the Technology Gap column of Table 1, third entry from above). Among these were buckling constraints, which were hence introduced into LAGRANGE. A larger example was optimization of the X- 31A composite wing, which already considered 4 American Institute of Aeronautics and Astronautics

29 buckling in addition to strength, effectiveness, and flutter constraints 12. The resulting ply orientations, however, were not suited for composite manufacturing. The concept of Constructive Design Elements was therefore introduced in LAGRANGE to allow addition of tape laying constraints 13 and shape variables, for example for optimal stringer placement in composite panels under buckling loads 14. Entire aircraft were also modeled and optimized. The JPATS contender Ranger 2000 in was checked in preliminary design for aeroelastic stability, and the potential for control surface flutter was detected. The problem was solved by positioning masses on the control surfaces. The mass values were then optimized with LAGRANGE. The largest application yet was a Stealth Demonstrator model to be optimized for minimum weight subject to strength, buckling, effectiveness, and flutter constraints 3. In order to consider ten symmetric and antimetric load cases simultaneously, a full model had to be used. With 22,000 degrees of freedom, 11,000 structural elements, 360 design variables and 110,000 constraints the problem was at the limits of reasonable size with respect to run time and the possibility of physical interpretation. The need for techniques to solve such tasks with reduced (half-) models and multiple boundary conditions is obvious. A 1992 study with the ACA-Fin 16 showed that constraints like buckling may complicate the structural design space significantly. In such a case the choice of optimizer (or a sequence of optimizers) determines whether an optimum, or even a feasible design, can be found. To date, algorithms suitable for buckling problems are still sought. By the mid-1990s, LAGRANGE had been used to solve most traditional aeroelastic optimization problems using Doublet-Lattice-Method aerodynamics with sizing, shape, and fiber orientation design variables. At the same time, the need for integration of structural optimization, aerodynamic analysis and optimization, flight dynamics and control systems design became a pressing issue. With regard to jig shape, deformed aircraft drag, and flexible aircraft flight dynamics, aerodynamic methods at least comparable in fidelity to those used in preliminary aerodynamic design were required for aeroelastic computations. Furthermore, the capability to alter the global structural layout numerically was desired so that structural data could be quickly generated in response to changes in aircraft configuration - like in the course of wing planform optimization. Further extensions of LAGRANGE were considered to be prohibitively complex and costly, and efforts were made to use the system as a stand-alone component either in tight coupling with a few other disciplinary tools, or loose coupling within larger, more general architectures. With regard to aeroelastic modeling, tight coupling of LAGRANGE with a higher order panel method, HISSS 17, is about to be completed. This combination allows accurate load modeling at given trim conditions. Optimization control remains with LAGRANGE; it communicates with a stand-alone coupling component via shared memory and interprocess control. LAGRANGE already supplied sensitivity information in a 1991 study on integrated aerodynamic, flight dynamic, and structural design of the ACA-Fin 18. Models of four planform variants were generated manually and the sensitivity of aeroelastic side force effectiveness with respect to taper ratio, aspect ratio, and area were calculated. These data were then inserted into the Global Sensitivity Equation, GSE, for derivatives of side force coefficient (flight dynamics), side force (aerodynamics), and effectiveness (structures). Due to the lack of a software framework supporting loosely-coupled, GSE-based algorithms at that time, global sensitivities were used to determine new candidate configurations, but not to drive an automatic optimization. In the MDO-Project 2,19 an automatic model generator was developed and proved to be very useful for rapid variant generation for large transport aircraft wings. In one demonstration application of the program suite, a two-level weight minimization was implemented with structural sizing variables at the lower level using LAGRANGE, and planform variables at the top level controlled by the MDO framework tool isight 20, which had become available since the 1991 ACA-Fin study. The FE models for LAGRANGE were produced by the model generator. Experience with this tool also underscored how important it will be to develop future generators which are applicable to generic wing-type components (transport, fighter, tail, etc.) and multiple structural concepts, and ensure robustness with regard to model degeneration. Similar modules are required for other structural components. In another task of this project, it was necessary to combine the specific capabilities of the aeroservoelastic optimization tool, AIDIA, at Aermacchi in Italy, with those of LAGRANGE at 5 American Institute of Aeronautics and Astronautics

30 DASA-M in Germany. A simple approximationbased approach was used for this particular multisite problem 19. Approximations of flutter constraints on one hand, and weight, stress constraints and aeroelastic effectiveness constraints on the other hand as functions of sizing variables were generated from data produced during optimization studies at Aermacchi and DASA-M, respectively. These approximations were then integrated into isight, and a design satisfying both sets of constraints approximately was found. The availability of a framework tool facilitated implementation of this method. For future studies it is desirable to have offthe-shelve software for generating multi-dimensional function approximations of several types, too. This review indicates that until a few years ago the focus of in-house developments was on improvement of disciplinary analyses and integration of new constraint types in a tightly coupled optimization package. More recently, the need to combine existing disciplinary analysis capabilities in order to solve multi-discipline design problems shifted interest towards tight coupling between specific analysis tools where appropriate and possible. Also due to growing acceptance of MDO ideas in the company, lose coupling via standard interfaces, controlled by framework software is planned and tested for the general case. Important pieces are still missing for industrial application: Software for supporting generic model generation, software for design space approximation, MDO methods for multi-site, multi-partner problems, and a product/process data standard to allow standardization of disciplinary tool interfaces, to name a few. Future Industrial User Requirements In order to provide a comprehensive picture of future trends in aeroelastic structural design and user requirements, a catalogue of questions prepared by Mr. Joe Giesing of McDonnell Douglas Corporation was presented to seven DASA-M staff members in the field of aerodynamics and structural dynamics, ranging from disciplinary experts to technical managers. Questions and answers are listed in Tables 2 and 3. The following paragraphs represent a summary of all responses. Question numbers refer to the order used in Tables 2 and 3. Major barriers to MDO in industry (question 1) are, in the field of structural optimization, the lack of optimization algorithms for topology/layout/material distribution, and Mathematical Programming (MP) tools for dual formulations. Most MDO technologies still not mature enough for industrial application, or have not been implemented in mature software products. Integration of disciplinary analyses is difficult since tool interfaces do not match (see also question 5). Organizational and cultural aspects are an important factor, since the concurrent nature of MDO processes differs significantly from the traditional sequential practice. No coordinating position for MDO is present in typical industrial hierarchies. The typical design problem (question 2) is to find a feasible, better, or locally optimal design in a mostly continuous design space. The global optimum is of lesser interest. Current software integration tools (question 3) have only recently been used in MDO applications. Improved support of design process organization and graphic visualization is required. The latter refers specifically to monitoring of optimization progress which lends itself to physical interpretation and identification of typical features of a family of designs. The most significant integrated simulation challenge (question 4) is nonlinear, aeroelastic, trimmed load calculation. The next important step will be inclusion of EFCS design for fully integrated loads and performance calculation. Current practical challenges are handling of multiple design configurations in load calculation, and consideration of manufacturing aspects like tape steering in composite design. Five barriers for using disciplinary analysis processes in MDO and design (question 5) were mentioned: Tool robustness, automation level, ease of use and checking, lack of control by experts, and lack of interfaces to other disciplines. The last item includes both consideration of other discipline s needs and data format compatibility. Since optimization is also considered a disciplinary analysis, another problem is the reliability of current MP tools. Tightly coupled methods for solution of integrated simulation problems (question 6) are needed for specific problems with strong or high data volume couplings. Loose coupling is preferred though, since the systems are more transparent and flexible. Analytical sensitivity derivatives are used within LAGRANGE, and the current challenge is to integrate this package and other disciplinary tools. Sensitivity derivatives for existing tools (question 7) are therefore not if immediate interest. 6 American Institute of Aeronautics and Astronautics

31 Automatic differentiation tools (question 8) will most probably not be used in-house. It is more likely that this work will be contracted to academia or research laboratories. The most important obstacles for using optimization (question 9) are user familiarity/training and difficulty in interpreting results. Improved graphical monitoring tools would facilitate interpretation (see question 3). A cultural aspect is that optimization is considered to be time consuming, so that in considering product cost vs. possible product improvement the management goahead for efficient optimization often comes too late. The primary reason for not using decomposition-based optimization algorithms (question 10) is the lack of demonstrated and validated software packages. Furthermore, an efficient implementation of such concurrent design methods faces organizational obstacles (see also question 1). In the previous paragraphs, responses were listed irrespective of the questioned persons backgrounds and positions, although the individual perspectives definitely permeate the responses. Staff members involved in the actual computational work are primarily concerned with practical issues like handling of current tools (analysis and optimization alike), solution of aeroelastic simulation problems today or in the near future, disciplinary tool coupling, and interpretation of results. Responses of individuals in charge of project and department management focus on topics like decomposition techniques or design process organization, and organizational challenges impeding MDO implementation in industry. This polarization is most obvious in answers to the last question asking for the three MDO developments which would facilitate the designer s job over the next 10 years (question 11). Assuming that the term MDO developments refers strictly to general-purpose MDO algorithms, methods, and implementations, then the following items can be extracted: - reliable, demonstrated, and validated software packages for industrial-size applications of MDO algorithms from conceptual to detailed design, including graphical monitoring, design space approximation, multi-criteria decision making, and analysis integration tools; - standardized tool interfaces and disciplinary analysis tools which are developed with interdisciplinary interfacing in mind; this requires identification of each single discipline s (or tool class s) required inputs and generated outputs; - MDO algorithms suited for optimization tasks to be performed by heterogeneous industrial consortia. Organizational aspects do not fit within this strict definition, but are nevertheless very important. The answers reflect the opinion that multi-discipline and concurrent design thinking is not manifested in today s industrial design processes and company structures. Summary The need for increasing integration of aerodynamics, structures, and control system design in a Multidisciplinary Optimization environment is evident both from past design trends and industrial user predictions of future directions. The most pressing issue for the structural designer s daily work is the gap in fidelity between aerodynamics used in performance calculations, flight dynamics and aeroelasticity. Generic flowstructure interaction techniques are needed so that Euler and Navier-Stokes Methods can be used in early design for reliable load and maneuver performance predictions. High performance/parallel computing will enable practical use of these methods. In the very near future, however, loosely coupled MDO strategies will be used in the industrial environment. Software framework tools supporting these approaches exist but need to be refined, extended, and validated for productive application. Reliable, robust software for generic model and design space approximation is missing. When this is accomplished, MDO methods like Concurrent Subspace Optimization need to prove applicability to industrial use. Successful implementation might be the key to the required cultural change in industry towards concurrent engineering. 7 American Institute of Aeronautics and Astronautics

32 Model Task Method Key Finding Conclusion Technology Gap SB 13 (1985) 8 eliminate flutter within flight envelope manual optimization/ trend studies with TSO/FASTOP aeroelasticity - flight dynamics coupling ACA-Fin (1986) 9 ACA-Fin (1990) 11 ACA-Fin (1991) 18 ACA-Fin (1992) 16 validation of optimized composite designs weight optimization with strength, aileron effectiveness, flutter, minimum gauge constraints; design variables: composite ply thicknesses integrated planform & sizing optimization for flight dynamic and stress requirements wind tunnel tests optimization with LAGRANGE total sensitivity analysis using 3x3 GSE (flight dynamics, aerodynamics, aeroelasticity) 1. buckling influence optimization with 2. performance of LAGRANGE different optimization algorithms X-31A (1990) 12 minimize weight s.t. buckling, stress, effectiveness, flutter Ranger 2000 alleviate flutter (1994) 15 tendency in preliminary design Stealth Demonstrator (1995) 3 minimize weight s.t. strength, buckling, aeroelasticity; symmetric and antimetric loading MDO-Aircraft 1. optimize wing box (1998) 19 structure (sizing variables) subject to static and dynamic aeroservoelastic constraints at different sites 2. test MDO methods and framework tools optimization with LAGRANGE, material tests optimization with LAGRANGE; flutter flight test; ground resonance test optimization with full model in LAGRANGE development of MDO coordination method based on subproblem approximations; application using MDO framework tool; optimization with LAGRANGE (stress and effectiveness constraints) flutter source: coupling of first elastic symmetric wing and short period mode nonlinear relationship between rudder command and load due to structural deflections transparency of GSE: automated procedure reflects well-known couplings in process structure 1. buckling is design driver; 2. most algorithms find only closest local optimum optimal design not suited for manufacturing mass positioning on control surfaces more efficient than struct. reinforcement sequence of algorithms successful; structural model very large (cycle time) 1. leads to acceptable global design if app. are good; partner studies yield hints at location of global solution 2. tightly and loosely coupled methods required depending on design stage currently still open technology gaps are underscored need to change material, spar position and wing planform traditional design for "effectiveness" possibly unreliable GSE useful for more complex problems 1. buckling must be considered; 2. sequence of optimizers necessary large optimization problems can be handled no weight savings from active flutter suppression under current regulations; sensor location & actuation system parameters needed as design variables; interaction between roll effectiveness and symmetric trim Table 1: Aeroelastic Optimization Applications and Conclusions aeroelastic equilibrium load calculation efficient methods for cross-discipline sensitivities and app. optimization procedures; modeling: FCS, aeroelastic equilibrium and thermal loads, buckling, dynamic response ; fiber orientation, spar positioning; multiobjective optimization optimization proc. using GSE; applicability of existing software to integrated optimization suitable optimization algorithms for buckling problems composite materials manufacturing constraint modeling simultaneous consideration of multiple boundary conditions with half models suitable MDO method; automated, generic, robust model generation; product/ process data standard; approximation generation software; aeroelastic effects in performance and flight dynamics 8 American Institute of Aeronautics and Astronautics

33 1. What are the major barriers and challenges to MDO in industry? Do they pertain to the state of the art in computer sciences, the availability of a suite of robust, automated analyses of varied accuracy, the need for robust optimization algorithms and tools, or the organizational (cultural) challenges you are facing? 2. What is your design problem and design goal? For example, is your goal a better design or the best design? Do you want the code to find the optimum or just show you the design space? Is your optimization mostly continuous or mostly discrete? Do you have multiple objectives to maximize? 3. Has the current state of software integration tools helped your implementation of integrated design and analysis processes? Do these processes require more than your current software tools can deliver in: Database management; distributed computing; analysis and design graphic visualization; analysis and design process organization, integration, monitoring and control 4. There is significant research nowadays directed to, for example, the multidisciplinary simulation for aeroelastic, fully nonlinear, multiple control surface, trimmed load calculation. Do you frequently encounter different integrated simulation challenges which you believe require additional research and development? 5. What are the major barriers in the use of disciplinary analysis processes in MDO and design? Consider the following areas: Cycle time, automation, robustness, fidelity, ease of use and checking, and applicability for MDO, loss of control by technical experts, or other. 6. One can solve integrated analysis and simulation problems using either a tightly coupled or a loosely coupled approach. A tightly coupled approach is a very efficient method but somewhat monolithic and it requires a new simulation code development. Instead, the loosely coupled approach is less efficient, but more modular and requires the integration of existing simulation codes. Most, if not all integrated analysis and simulation problems in place nowadays are of the loosely coupled variety. Would you consider the use of a tightly coupled method? SO industrial processes in companies are sequential; MDO requires more concurrent engineering processes; tool interfaces do not match; MDO technologies not yet available for industrial use (maturity); no coordinating function (persons) for MDO in industry SO lack of general MP tools on dual formulations; lack of topology/ layout/material distribution algorithms MO organizational/cultural: acceptance of MDO by discipline experts and management SO to get a feasible design is most important A multi-point design: feasibility, reliability DE to get a better design SO to find the nearest local optimum; variables: mostly continuous (MP algorithm for discrete variables desirable for composites) MO to find a feasible, better design in a mostly con tinuous design space with a large number of design variables and constraints and multiple objectives AEO reduced time (model generation, results evaluation); include all design drivers; discover critical aspects early; model close to manufacturing (affordability, final weight); continuous process from definition to product SO A analysis and design process organization expert systems for guidance and easy implementation of new applications/analysis tools; multicriteria decision making tools DE all items SO all items MO in decreasing order of importance: analysis and design process organization, graphic visualization (monitoring!) SD visualization/monitoring: extraction of characteristic features of a family of designs SO integration of FCS design and structural dynamics (including aeroelastics and flight dynamics) A virtual aircraft in full flight SO tape steering subject to manufacturing aspects AEO multiple configurations (fuel, stores, actuator failure modes) SO robustness, usability and applicability for MDO, tool interfaces DE automation, ease of use and c hecking SO in decreasing order of importance: robustness, loss of control by technical experts, ease of use/checking, reliability of MP tools MO in decreasing order of importance: applicability to MDO (interfaces), loss of control, ease of use AEO single discipline models too complex, not considering other disciplines requirements (e.g. statics FEM: wing mass, stiffness, DOFs); lack of understanding other disciplines needs SO loosely preferred due to complexit y of tightly coupled systems A loosely coupled: allows for easily exchanging analysis tools SO both is needed! MO tightly coupled only for special problems (with strong coupling); loosely coupled preferred due to flexibility SO department manager, MDO expert MO MDO expert, aeroelastician A R&D project manager, aerodynamicist AEO aeroelastician, structural optimization expert DE conceptual designer SD structural dynamicist SO structural optimization expert Table 2: Responses to MDO Requirements Questionnaire (1) 9 American Institute of Aeronautics and Astronautics

34 7. Sensitivity derivatives are available for a number of commercial and government-supplied simulation codes. Are there other simulations for which you wish you had sensitivity derivatives? Also, would you consider using that information even in other than an optimization setting? If so, do you have specific requirements on such sensitivity capabilities? 8. Are you likely to invest time and effort as a user of automatic differentiation tools to produce your own sensitivity analysis software or are you looking to academia/ government researchers to use those tools and generate sensitivity analysis software for your use? 9. What are the single most important obstacles to your use of optimization? User familiarity and training, optimization code performance, reliability/robustness, ease of use, difficulty in formulating an optimization problem representative of the design problems you face in your day-to-day applications, difficulty in interpreting the resulting designs or in validating them, or other? 10. Few, if any of the currently available multilevel/multidisciplinary (CSSO, CO...) optimization algorithms based on decomposition have been used in industry. Do you attribute that to: The fact that one does not need in reality such general purpose methods, the complexity of the methods, the lack of maturity of the methods, or the lack of demonstrated and validated software packages? 11. In order of decreasing priority, what are the 3 MD developments which would help you do your job better, as a designer over the next 10 years? SO academia/labs SO academia/labs MO academia/labs SO user familiarity and training SO performance, reliability/robustness, difficulty in interpreting/ validating results AEO management go-ahead for efficient optimization often comes too late; external opinion: optimization costly, increases product cost ("... for a 1% weight saving") SO lack of demonstrated and validated software packages MO too complex/immature for industrial applications, also hardly known or understood (organizational aspects); lack of software SO A SO 1. process and company organization; 2. standardized tool interfaces; 3. demonstrated and validated MDO software packages optimization strategies for heterogeneous projects (with partners from various industry branches) 1. conceptual design optimization tools; 2. more general MP tools; 3. easy-to-use monitoring tools MO 1. product/process model standard (data format) and interfaces catering to it; 2. software (MDO algorithms, approximations); 3. MDO strategies for multi-partner, multi-site optimization AEO 1. completeness of single-disciplines' set-of-needs (automatic, integrated load case generation); 2. efficient aerostructures coupling mechanisms (generation, reliability, modifications); 3. formulation of active a/c optimization approach: What is the optimum deformed structure shape? How can it be achieved at minimum cost (energy, mass of actuation system)? What is the optimum passive structure and control system design to achieve an overall optimum design? SO department manager, MDO expert MO MDO expert, aeroelastician A R&D project manager, aerodynamicist AEO aeroelastician, structural optimization expert DE conceptual designer SD structural dynamicist SO structural optimization expert Table 3: Responses to MDO Requirements Questionnaire (2) 10 American Institute of Aeronautics and Astronautics

35 References Snee, J.M.D., Zimmermann, H.; Schierenbeck, D., Heinz, P., Simultaneous Stress and Flutter Optimization for the Wing of a Transport Aircraft Equipped With Four Engines, Bath, UK AGARD-R-784. Allwright, S.A., Technical Data Management for Collaborative Multi-discipline Optimisation, 6 th AIAA/NASA/ISSMO Symposium on Multidisci-plinary Analysis and Optimization, Bellevue, Washington, September AIAA Krammer, J.M., and Lemmen, G., Integrierte Strukturauslegung mit dem Strukturoptimierungsprogramm LAGRANGE am Beispiel des fliegenden Technologieträgers, DGLR Jahrbuch 1996, pp DGLR-JT Haftka, R.T., Structural Optimization with Aeroelastic Constraints: A Survey of US Applications, International Symposium on Aeroelasticity, Nürnberg, Germany, Hönlinger, H., Active Flutter Suppression on an Airplane with Wing Mounted External Stores, Structural Aspects of Active Control, Paper 3, April AGARD-CP-228. Seyffarth, K., Lacabanne, M., König, K., Cassau, H., Comfort in Turbulence (CIT) for a Large Civil Transport Aircraft, Forum Int. Aeroelasticité et Dynamique de Structure, Strassbourg, France, Becker, J., Luber, W., Flight Control Design Optimization with Respect to Flight- and Structural Dynamic Requirements, 6 th AIAA/ NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Bellevue, Washington, September AIAA Schweiger, J., Sensburg, O., and Berns, H.J., Aeroelastic Problems and Structural Design of a Tailless CFC- Sailplane, International Symposium on Aeroelasticity and Structural Dynamics, Aachen, Germany, April Hönlinger, H., Schweiger, J., and Schewe, G., The Use of Aeroelastic Wind Tunnel Models to prove Structural Design Methods, 63th Meeting of the AGARD Structures and Materials Panel, Athens, Greece, September 1986 Schweiger, J., Krammer, J., and Hörnlein, H.R.E.M., Development and Application of the Integrated Structural Design Tool LAGRANGE, 6 th AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Bellevue, Washington, September AIAA Sensburg, O., Schweiger, J., Gödel, H., and Lotze, A., The Integration of Structural Optimization in the General Design Process of Aircraft, 17th Congress of the International Council of the Aeronautical Sciences, Stockholm, Sept Lonsinger, H., Günther, G., and Schweiger, J., Enhanced Fighter Manoeuverability Aircraft (X-31A) Wing and Thrust Vectoring Vane Design, 11 th American Society of Mechanical Engineers Winter Annual Meeting, Dallas, Texas, Nov Schuhmacher, G., Multidisziplinäre, fertigungsgerechte Optimierung von Faserverbund- Flächentragwerken, Dissertation, Universität- Gesamt-hochschule Siegen, FOMAAS, March TIM-Bericht Nr. T Eschenauer, H., and Weber, C., Stiffened CFRP- Panels Under Buckling Loads - Modeling, Analysis, Optimization, DE-VOL. 82, 1995 Design Engineering Technical Conferences, Volume 1 ASME 1995, pp Weiss, F., Schweiger, J., and Hönlinger, H., Flutter Flight Test of the RANGER 2000 Aircraft, Meeting of the AGARD Structures and Materials Panel, Rotterdam, The Netherlands, May Hörnlein, H.R.E.M., Overview of Benchmark Problem MBB Fin, Final Report of the GARTEUR Action Group on Structural Optimisation SM(AG13), Volume 3, Section C, Defence Evaluation and Research Agency, Farnborough, United Kingdom, February Fornasier, L., HISSS - A Higher-Order Panel Method for Subsonic and Supersonic Attached Flow about Arbitrary Configurations, Panel Methods in Fluid Mechanics with Emphasis on Aerodynamics, Notes on Fluid Mechanics 21, Vieweg Verlag Braunschweig/Wiesbaden, Schneider, H., Krammer, J., and Hörnlein, H.R.E.M., First Approach to an Integrated Fin Design, 72nd Meeting of the AGARD Structures and Materials Panel, AGARD Report 784. Stettner, M., and Basso, W., Multi-Site Coordinated Aeroservoelastic Subtask Optimization, 7th AIAA/USAF/NASA/ISSMO Multidisciplinary Analysis and Optimization Symposium, St. Louis, Missouri, September AIAA ISIGHT Designer s Guide, Engineous Software, Inc., Raleigh, North Carolina, American Institute of Aeronautics and Astronautics

36 Multidiscipline Design as Applied to Space Charles F. Lillie*, Michael J. Wehner and Tom Fitzgerald TRW Space & Electronics Group One Space Park, Redondo Beach, CA Abstract The objective of this paper is to look at the spacecraft design process and see how that process balances desired spacecraft features within an imposed set of operational and cost constraints. The constraints often show up as competing multidiscipline interactions, which in their resolution lead to practical spacecraft designs. This paper gives examples of how the design process was implemented in a feasibility design study for NASA's proposed Next Generation Space Telescope (NGST), and describes how the project organization was used to effectively deal with multidiscipline design. Orbit selection, spacecraft propulsion, station keeping, and overall mechanical and thermal subsystem designs are discussed as examples of multidisciplinary design optimization. The final section is an across-the-board discussion of multidiscipline design optimization, what its benefits are, what are the negative points and what can be done to improve the process. Introduction This paper deals with work performed by the TRW-led study team under National Aeronautics and Space Administration Cooperative Agreement No. NCC5-137, awarded May 24, 1996 by the Goddard Space Flight Center, for research entitled: Next Generation Space Telescope Feasibility Assessments. The report *Senior Member AIAA Copyright 1998 by TRW, Inc. Published by the American Institute of Aeronautics and Astronautics, Inc. with permission. was presented to the NGST Integration Team at GSFC on August 20, The study was to involve industry, universities and/or non-profit organizations in the early planning for the NGST in a search for the best ideas for accomplishing the mission. The NGST project office felt that it would be necessary to go beyond simple parameter trades to non-linear thinking in order to break the current cost-aperture paradigm to achieve the $500M goal for NGST development, with a total life-cycle cost of $900M in 1996 dollars.. This paper describes some of the major features of our approach to developing the NGST spacecraft, launching it, and operating it for 10 years. The paper includes the mission requirements which we derived from the Dressler Committee s HST and Beyond report, and examples of the trades and analyses which we performed to develop a mission concept and baseline configuration for the NGST, a development plan for enabling technologies, a cost estimate and a recommended management approach. Figure 1 shows the organization of our study team and each team's responsibilities. Our organization paralleled that of the ongoing government study to facilitate the integration of our results with those from the other teams. During the study the Integrated Product Teams (IPT's) responsible for the Optical Telescope Assembly and for the Science Module worked closely together to define an integrated payload 1 American Institute of Aeronautics and Astronautics

37 with an optimum partitioning of functions between the two assemblies. The Spacecraft systems team was responsible for the classical subsystems as well as thermal shields, vibration control, and the fine pointing system. The Operations team was responsible for the end-toend data flow, including the ground system architecture and partitioning flight and ground system functions. The System Engineering team had responsibility for design integration as well as requirements definition, mission analysis, and interface definition B. Marcus, TRW LOB Manager S. Savarino, TRW Marketing NGST Study C. Lillie, TRW Cost Modeling Science Advisors/Working Group E. Wood, WW Payload Optical Telescope Assembly Optics Light Baffles Structure Mechanisms Cryogenics Materials Figure Control Science Module Detectors Cryostat Cryocoolers Cameras Spectrometers Wavefront Sensors Deformable Mirrors Steering Mirrors Spacecraft Systems Electrical Power Communications C&DH ACS Propulsion Structure and Mechanisms Thermal Control Vibration Control Operations Systems Ground System Design Staffing Data Reduction and Analysis Planning and Scheduling Contingency Operations Normal Operations Systems Engineering Systems Requirement Definition Mission Analysis Interface Definition & Control Optical, Electrical, Mechanical, & Thermal Design Integration Contamination Control Launch Vehicle Interface N. Wallace, TRW T. Fitzgerald, TRW K. Biber, TRW D. Werts, TRW M. Wehner, TRW Figure 1. Study Organization The responsibilities of the study team member organizations are summarized in Figure 2. TRW personnel led the NGST study IPTs and took the lead in the system engineering, design integration, science module, spacecraft bus and operations activities. HDOS led the optical design activities and supported the NGST study in requirements development, materials selection, performance modeling, active optical systems, and mirror assembly concepts. Swales personnel supported our NGST study in thermal design, contamination control, structure/ mechanism design, science module design, and operations. Swales worked closely with personnel from Goddard Space Flight Center with experience in optics, structures, electromechanical devices, thermal control, cryogenics, contamination control, instrument design, and operations, who were members of our IPTs and supported our study activities. Additional support to the IPTs was provided by scientists and engineers from the Langley Research Center with expertise in analysis and control of flexible structures, active structures, active materials, isolation systems, and spacecraft analysis and modeling. The study was also supported by scientists from several universities who worked with their industrial counterparts to define the system requirements, develop conceptual designs for the instruments, assess system performance and review the outputs of our study. 2 American Institute of Aeronautics and Astronautics

38 Most interaction between team members was accomplished by weekly telecons and individual phone, fax, and communications. We also established an Internet homepage for the study team to facilitate the flow of information, including direct file transfers. This approach worked reasonably well, once the tools were in place and face-to-face introductions of team members had been accomplished. Team TRW HDOS GSFC/SWALES LaRC/Science Team 1 System Engineering Lead, system requirements, trades, analysis, design integration Requirements Development, optical performance modeling Thermal design, Contamination control Science team models system performance for typical targets 2 OTA, Including structures/ mechanisms Lead, deployable structure, mechanisms Optical design, material selection, modeling, assembly concepts Support for structure and mechanisms design LaRC supports active structures design, technology roadmap development 3 Science Module Lead, system design, payload accommodation, Wavefront sensor, fine guidance sensor, active optics Instrument design Science team supports instrument design 4 Spacecraft Bus Lead, classical bus design, vibration control, fine pointing Identify Enabling technologies, alternative designs, attitude control LaRC supports vibration control, spacecraft analysis and modeling 5 Operations Lead, ground system. design, mission operations. planning Operations plans and scenarios, communications link trades and analyses Science team supports mission scenario prep., MO&DA planning 6 Science/ MO&DA Coordinate science advisor, working group activities Science Support Figure 2. Team Responsibility Matrix Science team reviews study results, Opening a website at TRW to external team members required the development of new network security procedures, which were successfully implemented midway through the study. Once established, this website was very useful for the disseminating data to the team and archiving the results of the study, as well as providing pointers to other relevant information on the Internet. NGST System Design Process We used our proven system engineering process on this project in defining mission requirements, deriving system requirements and developing system concepts. Several of these processes are iterative. The design features are balanced against the cost, risk and complexity of the concepts to produce a baseline concept. As the concept evolves the system requirements are finalized. The final product is a baseline NGST design and the associated technology development necessary to implement the design. Design Reference Mission We developed a Design Reference Mission based on the Dressler Report and our Science Team's expertise in astronomy. The NGST system was optimized to provide high quality information for investigating the early universe formation (using a large aperture and IR imaging). NGST would also continue the Hubble telescope role of determining the Hubble constant via Cepheid variables and other techniques. NGST would have very significant capabilities in ordinary astronomy involving stellar evolution, galactic structure, planetary astronomy, etc. 3 American Institute of Aeronautics and Astronautics

39 Top-down requirements definition and bottoms-up technology application procesess produce an optimized design for NGST Program Requirements Cost Schedule Science Requirements Wavelength Aperture Requirements and life cycle cost targets allocations Requirements Mission/Observatory Requirements Design life Launch vehicle Revised requirements/cost allocation Concept Assessments Performance Science return Requirements Integrated modeling LCC Cost drivers Risk Schedule Cost Performance Advanced instrument technologies Technology Precision deployable technologies System Trade Studies Payload Observatory Spacecraft Orbit Launch vehicle Ground station Instrument studies technologies results Primary mirror technologies Advanced spacecraft subsystem technologies Mission concepts Outputs a) b) c) d) e) f) g) h) i) $ Performance NGST design(s) SI and mission operations requirements Architecture models Performance assessment Technology roadmap LCC estimate and descope options Development plan Alternative approaches Technology development Figure 3. System Design Process Early Universe Investigation (Z ~4 to 10) ~50% of NGST observing time 100 to 200 survey fields at high galactic latitudes Integration times ~10e3 to 10e5 sec Foreground Galaxies (Z ~0.5 to 3) ~20% of NGST observing time Observation of Cepheids, supernovae, etc. (Hubble Constant) Integration times ~10e3 to 10e4 sec Local Galaxy (including Local Group) ~10% of NGST observing time Stellar evolution, brown dwarfs, etc. Integration times ~10e3 to 10e4 sec Solar System Objects ~10% of NGST observing time Planets, comets, asteroids, Kuiper Belt objects Integration times ~10 to 100 sec Targets of Opportunity ~12 to 24 hour response time Figure 4. DRM Mission Requirements Based on the DRM and our Science Teams guidance, we developed a set of Mission Requirements for NGST. These requirements are essentially concept independent, demanding only that NGST be a large aperture, imaging and spectroscopic IR optimized space telescope. Note that there are four graduations of importance in the requirements: 1) required, 2) highly desired, 3) desired and 4) goal. These are guidance to the concept designers as to the importance of these requirements. We placed some emphasis on targets of opportunity. Our design incorporates features dedicated to this. We believe that such flexibility is essential to provide data on comets and transient targets, such as supernovae. 4 American Institute of Aeronautics and Astronautics

40 The Dressler report and the DRM are directly responsible for the quality requirement on this page. Early universe objects are highly redshifted, which reduces the need for visible light observations. Therefore, we designed the NGST for diffraction limited performance at 1 µm. Note also the required bands correspond to the Dressler reports recommendations, but it was considered advantageous for NGST to exceed this band range if possible and cost effective. Slit spectrometers are required. It was also desired that an imaging spectrometer be added, if feasible. We did not want NGST to be limited in stare time by design features. Therefore, a very long (~28 hours) requirement for stare time was included. Lifetime 10-year Mean Mission Duration (MMD) (required) 13-year design life (required) Targets High redshift objects (required) Local area galaxies, clusters (required) Milky Way objects (required) Solar system objects Planets (desired), outer solar system objects (highly desired) Near-earth comets/asteroids (goal) Targets of opportunity within Field of Regard Observations Multi-color imaging (required Spectroscopy (required) Polarimetry (highly desired) High speed photometry (desired) Astrometry (desired) Response times Scheduled observations: 1 month (required Targets of opportunity: 24 hours (required; 12 hours (goal) Aperture 6 m (required) 8 m (highly desired) Quality Optics have diffraction limit (1/14 wave RMS) at 1µm (required) Nyquist sampled at lower end of each octave range except for bands < 1 µm Imaging Spectral Bands 1 to 5 µm (required) 0.5 to 10 µm (highly desired) 0.5 to 20 µm (desired) 0.35 to 40 µm (goal) 2-D Spectrometer Bands (Slit Spectrometer) l/ l = 1000 selected imaging band (but no greater than 0.5 to 20 µm) (required) l / l = in 0.5 to 20 µm band (highly desired) The agility requirement of 30 in 15 minutes is expected to not be stressing from a design viewpoint, and to provide a reasonably small loss in total observing time. Given that the majority of observations are long exposures (~2 hours based on the DRM), this implies that the telescope is repositioned ~10 times per day, resulting in down-time of 2.5 hours out of 24, which is roughly 10% down-time. Field of view of the imager has been a parameter much discussed. Larger is of course better, but has significant cost implications in requiring large numbers of pixels and stresses the optics design. The value chosen is the same as the current Hubble Wide Field camera (if the square was filled). 3-D Spectrometer Bands (Simultaneous 2-D Spatial Spectroscopy) l/ l = 50 in all bands (required) l / l = 1000 in 0.5 to 20 µm band (desired) Stare Time No system limitations up to 1E5 sec (required) Sufficiently short such that bright targets not over exposed (required) Agility Slew and settle a nominal distance (30 ) within 900 sec (required) Sufficient to follow planets and outer solar system objects (required) Sufficient to follow fast moving comets (e.g., Comet Hyakutake) (highly desired) 0.5 arcsec/sec (highly desired) 2.0 arcsec/sec (goal) Pointing Stability Total short-term jitter and long-team drift during exposure results in 20% larger diffraction image (note that is dependent of diffraction limit selected) (required) Imaging Field of View 2.5 x 2.5 arc minutes (required) 4 x 4 arc minutes (highly desired) Spectroscopic Field of View 2D slit 30 arcsec (required) 3D array covering 0.5 x 0.5 arc minutes (desired) Coverage 4 steradian coverage of the celestial sphere (required) Coverage of any solar system object greater than 1.5 au from the sun, when projected onto the ecliptic plane (required) Field of Regard 1 steradian (required) 2 steradian hemisphere centered 180 from the sun (hemisphere zenith pointing anti-sunward) (highly desired) Figure 5. Mission Requirements 5 American Institute of Aeronautics and Astronautics

41 Coverage is defined as the region which can be viewed by NGST over an extended time (like one year). Field of Regard (FOR) is the region which can be viewed by NGST over a short time (like one day). Field of View is the region that can be viewed by NGST instantaneously. With the coverage requirement defined, NGST will be able to view all parts of the celestial sphere and the outer parts of the solar system. The highly desired FOR enables target of opportunity detection over half the celestial sphere at any one time. The required FOR corresponds to a 20 annulus perpendicular to the sun vector. This is commensurate with an NGST design without an elevation gimbal. Baseline Concept When stepping from the realm of mission requirements to system requirements, it is necessary to have a baseline system concept. This chart and the one following show the NGST baseline as of the conclusion of the three month study. In this paper we show the key trades and requirements flowdown which led to this baseline. NGST is in a Lissajous orbit at the Lagrangian L2 point, placed there by an Atlas II AS (specified by the government) which follows an Earth-Moon flyby trajectory. Communication to earth is via X-Band. Lissajous Orbit Visible IR Telescope Space Vehicle X-Band Transponder/TT&C 2 to 4 kbps 11 m Antenna L2 Point X-Band High Gain 10 Mbits/sec Space Vehicle Visible IR Telescope Moon Atlas II AS To Sun 6000 lb Space Vehicle SA043 Figure 6. Mission Concept A small (11 m) X-band antenna on the ground will provide low cost support to the NGST Space Vehicle (SV). A dedicated ground station would schedule and operate the SV. Figure 7 presents the configuration which we developed for the NGST space vehicle. Note the sun and thermal shields are cut away for clarification. The spacecraft bus is located at the center of the shields, separated from the instrument module and telescope by a boom. The space vehicle is kept oriented such that the shields shade the telescope from the sun and earth. An optional shield sized to shade the telescope from the moon was considered, but rejected (shield size approximately doubled, from ~200 m2 to ~400 m2). The thermal load 6 American Institute of Aeronautics and Astronautics

42 from the moon is negligible; the impact of sunlight reflected off the moon needs further investigation. The shields are supported by struts, attached to the spacecraft. Note the symmetry of the shield. This is to counteract solar pressure. Note also the placement of electrochromic patches, which are used as trim tabs to balance the pressure with the space vehicles center of gravity. The telescope primary mirror is deployable using TRW s HARD (High Accuracy Reflector Development) technology. The telescope is coarsely pointed with an elevation gimbal. After thermally stabilizing, fine pointing is achieved by nodding the space vehicle and rotating in azimuth about the sun line. A fine pointing mirror provides final pointing and tracking of the targets. As an illustrative tool and as a guide to our trade space, we present the key trades we performed throughout this study. Note that some of the options are in italics and lined out. These are potential solutions that were rejected. The highlighted options have been baselined. Key trades Spectral Band Options: It was decided that a UV capability for NGST would be costly and not in keeping with the Dressler guidelines. Fabricating UV optics is expensive, and coupling that with deployable optics was considered too extreme. Similarly, to achieve Primary & Secondary Tip/Tilt Deployable Secondary 10 Tilting of SV for Fine Elevation Pointing Rotate SV for Azimuth Control Elevation Gimbal Steering Cables for Elevation Gimbal Passively Cooled FPAs Passively Cooled Telescope f1.25 ~8 m Primary Deployable Boom Separating Hot and Cold Regions Deformable Primary and Wavefront Mirror 4 Thermal Shields H2 Resistojets for Stationkeeping Biprop for Transfer Orbit Silvered Teflon Sun Shield Shield Cp Balanced with Cg Electrochromic Patches for Momentum Dumping Smart Strut Booms Twist For Propeller Momentum Dumping Imbedded Amorphous Silicon Solar Array Deployable Struts Rigidly Support Shields SA043 Figure 7. Key Design Features 7 American Institute of Aeronautics and Astronautics

43 ±10 SV Tilting 360 Azimuth Pointing 0 to 80 Elevation Gimbal Figure 8. Payload Pointing 40 µm capability, we found that the optics would have to be cooled below reasonable levels (next figure). Later we will show that due to cost reasons, the 20 µm band was also rejected. Transfer Orbit Options A number of options are available to deliver the space vehicle to L2. The selected baseline, lunar flyby with phasing loops, offers a large launch window with good throw weight. Direct transfer is advantageous as it has a large launch window, but has the least throw weight of any of the options. Direct lunar flyby has the same throw weight as the selected option, but has a very short launch window. Integral propulsion is attractive as it NGST Trade Tree (1/3) Spectral Band Options µ m 1-10 µ m µ m 1-20 µ m µ m 1-40 µ m Cold optics, FPAs Orbit Options L2 Lissajous Drift Away L2 'Exact' L4,L5 Orbits L2 Halo 3 AU Heleocentric L1 Orbits.1-.3 Heleocentric L2 Lissajous Orbit L2 Transfer Orbit Options Direct Transfer Lunar Flyby Lunar Flyby with Phasing Loops Integral Propulsion + Lunar Flyby Transfer Orbit Contamination Control Propulsion Options Material Selection Bi Prop Propellent Selection Mono Prop Active Cleaning Cold Gas None Stationkeeping Propulsion Options None Hydrazine Bi Prop Arcjets Pulsed Plasma Resistojets Solar Sailing Figure 9. Key Trades 8 American Institute of Aeronautics and Astronautics

44 has the best throw weight of the options, but requires a large amount of propellant. Due to launch vehicle size constraints, we do not have the room to accommodate this additional propellant. Figure 10 illustrates why NGST was not designed to operate at 40 µm. Operating at this point would require very cold mirror temperatures, which are beyond a reasonable design capability. We allocated to thermal control the objective of passively cooling optics to ~30 K. This preserves the option of including a 20 µm band. The cost of achieving this temperature is very modest, only requiring the inclusion of an additional thermal shield layer. The requirement for cold optics drives the SV configuration Passive Optics Cooling Feasible Assumptions f/15 telescope Zodiacal spectral radiance 10e-11 W/cm2 µm Sr Bandpass: 0.1 µm Irradiance: 3.5e-15 W/cm2 Mirror emissitivity: Cutoff Wavelength, µm Figure 10. Temperature vs. IR Wavelength Orbit Options Orbit Selection Summary L2 Lissajous requires no insertion ²V, low stationkeeping ²V Low meteoroid, solar flare flux Negligible thermal from earth and sun Good launch window, throw weight with Lunar Assist + Phasing Loops transfer orbit L2 halo requires insertion ²V L2 exact orbit requires high stationkeeping ²V L4/5 have very long communication ranges (1 AU) Drift-away orbit limits life; long communication range 1 AU heliocentric orbit needs further investigation 3 AU heliocentric orbit has lower throw weight; not needed for our bands Near-Earth (and moon) orbits have a stressing thermal environment. Therefore, only orbits some distance from the earth were considered. The Lissajous L2 orbit was baselined. Attractive features of this orbit are: short range to the earth, low station keeping requirements, and no insertion DV to enter the orbit. L1 orbits have no advantages and the disadvantage of higher solar flux and having the earth shining in the telescopes field of regard. The drift away, L4/L5 and 3 AU heliocentric orbits are at long ranges from the earth and have minimal 9 American Institute of Aeronautics and Astronautics

45 advantages in the primary band of interest (1-5 µm ). Halo and L2 exact orbits have high station keeping and transfer DV requirements. The 1 AU Heliocentric orbit located AU from the earth is still under investigation. This orbit may be able to be station kept at a reasonable earth distance. One of the advantages of the selected Lissajous orbit is that no burns are required to enter, and it requires low DV to maintain. Also, this orbit is very large (300,000 km by 600,000 km axes), and only needs maintenance occasionally. The DV required to meet this the station keeping requirements is 2-4 m/sec/year, or m/sec over the mission life. Station keeping at L2 Considerations L2 is an unstable point, so station keeping is required Serious contamination concern due to cold optics temperatures Station keeping Requirements Delta V: ~2 m/sec/year Station keeping maneuver timeline 3 months Contamination Concerns Contamination is a major concern in cryogenic optical systems Acceptable contamination levels have not yet been determined for NGST Water, oxygen, argon, nitrogen, etc. can freeze out on cold surfaces Contamination control approaches Select low outgassing materials for construction Exercise contamination control pre-launch Protect optical surfaces during launch and during early time on-orbit Perform vacuum bakeout and use molecular absorbers to reduce outgassing rates Minimize vapor and gas flux to cryogenic surfaces Periodic heating of surfaces to remove contamination A major potential source of contamination is the propulsion systems Prudent selection of the propulsion systems will reduce contamination issues An additional source of contamination is from launch vehicle fairing during ascent Contamination Concerns Contamination concerns have driven our selection of the propulsion systems for NGST. As detailed design progresses, contamination concerns will significantly affect material selection and will require designing in vent paths and baffles. Our ~30 K optics will be cold traps for volatile materials to condense on. Of particular concern are the effects from propulsion systems. Some propulsion systems are very dirty. Others are relatively clean, but produce by-products such as water which can condense onto the cold optics. On the following charts we present the propulsion trades and explain how contamination concerns were a driver. Transfer Propulsion Trades A number of options were considered as a transfer orbit propulsion system. Such a system, 10 American Institute of Aeronautics and Astronautics

46 assuming a lunar flyby with phasing loops trajectory, requires ~ 100 m/sec DV (including margin). Multiple burns are required, extending over weeks after launch. Due to contamination concerns, we considered first using a cold gas with no contamination concern, such as hydrogen. However, we found that due to the low ISP and large DV required, it was not possible to package this system in the allowable volume. Electric propulsion was considered and rejected, mainly due to low thrust levels that were not compatible with the mission. Solids were rejected as too dirty and impractical due to restart requirements. Liquid propulsion was selected, specifically a dual mode system. Weight of the system is ~170 lb., using available thrusters. Contamination products are mostly water. This led us to delay deployment of the telescope and sun/thermal shields until after the transfer burns were completed. This would allow time for the propulsion system products to disappear. Transfer Propulsion Trades Propulsion system requirements for lunar assist with phasing loops transfer orbit ~100 m/sec total ²V Phasing maneuver ²V at launch + days Mid-course maneuver ²V at lunar flyby + weeks NO ²V REQUIRED FOR L2 INSERTION Low contamination system required System Advantages Disadvantages Cold Gas No contamination with right gas Inexpensive Heavy, very large storage tanks needed Low ISP, thrust Solid Liquid Electric Propulsion Simple High thrust High ISP Restart capability High thrust Very high ISP Serious contamination potential No restart; multiple engines required Contamination control must be considered Very low thrust High power requirements Station keeping Propulsion Options Contamination was the driving concern in selecting the station keeping propulsion system which led us to reject the liquid system used for transfer orbit. This is unfortunate, as only a few extra kilograms of fuel would suffice to provide station keeping over the mission life. The products (water, etc.) would likely be major contaminants on the cold mirror and other surfaces. Therefore, only non-contaminating fuels were considered further. Cold gas systems are attractive due to their simplicity. However, the low ISP means that hundreds of kilograms of H2 would be needed over the mission life. There is not enough weight margin or volume to accommodate such a system. Electric propulsion (resistojets, arcjets, Hall effect thrusters) is attractive, but often entails significant cost and requires high power. However, resistojets are a simple electrical system with great promise. This technology is flight proven, and TRW has past experience with these systems. Resistojets are very small (couple of inches long) and light weight (only ~10-20 kg of H2 needed). They use ~ 250 W of power each, and have a high ISP. As will be seen in the Space Support Module (spacecraft) discussion, resistojets make a lightweight attractive system. Operationally, due to low thrust, they would have to burn for hours. This 11 American Institute of Aeronautics and Astronautics

47 would probably mean shutting down observations, but as burns are only needed every several months, this is not an issue. Note the location of the resistojets on the concept description chart. Thrusters should operate though the Cg of the space vehicle. The resistojets are located on the boom at the approximate Cg of the system. Our early baseline contained a cryostat (for instrument cooling) of solid Hydrogen. Interestingly, the amount of H2 needed in the cryostat for a ten year mission is about the same as needed for station keeping. We expended some effort to try to utilize the cryostat boiloff as fuel for the resistojets. Unfortunately, the H2 in the cryostat is at very low pressure (<<1 psi), and we could find no practical way to pressurize this gas to the 10s of psi required. Lack of synergy with the resistojets contributed to the demise of the cryostat. Stationkeeping Propulsion Options Options Mono or Biprop Cold Gas Arcjet Hall Effect Resistojet Solar Sailing Advantages Synergistic with transfer orbit propulsion system Very simple system No contamination concerns - H 2 condenses at 5 K - He condenses at <<1 K - N 2 condenses at 30 K Can use H 2 or hydrazine Very high ISP Can use H 2, N 2, Zenon (inert gasses) Very high ISP Can use H 2, N 2, Zenon High ISP Utilizes our sunshade No contamination Disadvantages Serious contamination concerns Requires 100s of kg of gas Very large tankage required Complex system Requires high power (>1 kw) Complex system Requires high power (~1 kw) Requires moderate power (~500 W) Tilting increases shade size Very low thrust. Sufficient? Launch Vehicle Capabilities This list of current and anticipated expendable launch vehicles potentially suitable to the NGST mission indicates the relative performance parameters and fairing volume constraints. The foreign vehicles are listed for completeness and comparison, and could be of interest should the program become an international effort. The capabilities of future systems are listed with public performance specifications to protect competition sensitive contractor actual estimates. The trend of all planned future vehicles is increased performance at reduced costs. Fairing dimensions are inside payload usable volume. Approximate (~) performances are not based on specific mission estimates but are extrapolated from GTO capability. All estimates are for optimum inclination for each launch vehicle and launch site. The Atlas IIAR and Delta III vehicles currently under commercial development with contractor funds and are planned for first flight in Although details are still considered propriety, both contractors have plans to expand these vehicles into a family with increased capability. It is reasonable to expect the commercial market to stimulate substantial performance improvements in the medium and heavy class before NGST is ready for procurement. 12 American Institute of Aeronautics and Astronautics

48 Launch Vehicle Capabilities Launch Cylinder Vehicle GTO (kg) C3=0(kg) C3=-2.3(kg) Dia (m) Length(m) Length(m) Atlas IIAS Atlas II AR 3900 ~2850 ~ Ariane ~4980 ~ Delta III ~ Delta II 1800 ~1200 ~ EELV Heavy >12247 ~8970 ~ Unknown H IIA (initial) 4700 ~3450 ~ H IIA (growth) 9900 ~7250 ~7600 Unknown Unknown Unknown Long March 3B 4800 ~3500 ~ Proton D1e Proton M 7100 ~5200 ~5450 Unknown Unknown Unknown Zenith 3 SL Notes: 1) Fairing dimensions are inside payload usable volume. 2) Approximate (~) performances are not established values but are estimated. 3) Performance is for optimum inclination for each launch vehicle site. 4) Atlas is currently doing design trades to develop a 5-meter diameter (outside) fairing for the Atlas IIAR series and the above. For special unique missions they could change the existing fairing ring and stringer design to get to a ~3.8-meter inside payload usable diameter. 5) Atlas IIAR series performance is assumimg a 3-foot stretch of the fairing as indicated. NGST Trade Trees (2/3) The following figure provides a roadmap through additional trades used to define our baseline. Here we concentrate on issues related to space vehicle design. Key to concept development is the realization that we have a very limited volume to package a very large structure. The launch vehicle constraints and the thermal considerations drove our configuration. NGST Trade Tree (2/3) Expandability Desirement Atlas II AR Atlas II AS Arianne 5 Delta II Launch Vehicle Options Delta III EELV Heavy H IIA (initial) HIIA (growth) Long March 3B Proton D1e Proton M Zenith 3 SL Spectral Band Options µm 1-10 µm µm 1-20 µm µm 1-40 µm Cold optics, FPAs Optics Packaging Options Fold Up/Down 'HARD'* Stacking Modified 'HARD' Stacking Telescope Thermal Options Parasol Shield Piggyback Shield Payload-on-a-Stick Optics f# Options f 0.9 primary mirror f 1.25 primary mirror Secondary Mirror Fixed Secondary Deployed Secondary Sun/Thermal Shields MLI Shields Single Sheet Shields Boom Stabilized Inflatable Shields Secondary Support Single Strut Two Struts Three Struts *HARD: High Accuracy Reflector Development Solar Pressure Compensation Momentum dumping by turning SV Momentum dumping by tilting shield Control tabs Symmetric shields Electrochromic panels Boom twist for anti-propeller 13 American Institute of Aeronautics and Astronautics

49 SA SA043 Deployable Mirror Concept The small fairings available in the Atlas class drove our selection of the deployable mirror. Two general classes were considered, foldable and stackable. The fold up-down is attractive as it is simple. However, it wastes a great deal of fairing volume, limiting the room left for the spacecraft. Packaging studies indicated that we had insufficient volume left for the spacecraft and instruments. The alternate concept, based on the TRW developed HARD deployment Stacked Versus Fold Up-Down Mirror Configuration Designs Space vehicle packaging trade hinges on the mirror configuration Fold Up-down is potential simpler mechanically, but has limited volume, also has smaller growth potential HARD concepts package more efficiently, increasing useable fairing volume Has significant growth potential Fold Up-Down Concept HARD Concept Atlas IIAS Fairing Atlas IIAS Fairing (399.96) Mirror Deployment 14 American Institute of Aeronautics and Astronautics

50 concept, is much more compact, and leaves the lower part of the fairing free for spacecraft and instrument packaging. TRW has demonstrated the HARD concept for large deployable RF antennas. Another very attractive feature of this concept is that it is expandable (see next chart). We have baselined the HARD concept. Support of Secondary Mirror The support structure for the mirror secondary has evolved significantly throughout our study. The first concepts had three fixed struts holding the secondary. Unfortunately, due to height limitations in the fairing, this required a very fast (f 0.9) primary mirror, which was considered very difficult to build and too sensitive to mechanical disturbances. Once the decision was made to have a slower mirror (f 1.25), we went to a single deployable boom holding the secondary. Analysis showed that the allowable deflections in the secondary location were very small (55 µm perpendicular to the optical axis, 300 µm in axis). Dynamically, when the telescope slewed, we were very concerned that vibration and hysteresis effects would exceed these values. While the secondary has five axis position control, it is desirable to not have to recollimate after every slew. Additionally, even with a very low CTE material, we found that temperature differences had to be kept at ~ 1 F both across the boom diameter and along the boom length. The temperature deltas along the length is considered challenging. We considered supporting the secondary better by placing the boom in tension and adding guy wires. Deployment of the wires was difficult, and dynamically not much stability was added. Two struts were considered briefly. They were found to offer little additional stability. Three struts is the current baseline. Two of the struts fold out of the way during mirror deployment and then fold back up to catch the secondary. This provides a rigid tripod structure. Thermal considerations remain, which is the primary reason for only moving the elevation gimbal periodically. At a constant gimbal angle, even with the SV tilting 10, the thermal environment is stable. HARD Mirror Concept Expandability The HARD technology allows easy expansion to much larger surfaces. With hexagonal petals, two rings of petals can be deployed. The entire stack of petals pivots about one corner of the last petal deployed and then drops into place. The remaining petals now pivot about the new petal, continuing the process. Generic Options for Space Vehicle Design We examined three generic concepts for the Space Vehicle design. The first two, parasol and piggyback, have the spacecraft behind the sun/thermal shields. Operating a spacecraft in a ~30 K environment is beyond the state of the art. The payload-on-a-stick concept permits the spacecraft to stay warm while the instrument compartment and telescope are behind the shade, staying cold. We examined options for the boom separating the regions. Able has a FASTmast that looks acceptable. The mast is collapsible into a compact package one foot in height, and is stored in within a 47" canister in the spacecraft central cylinder. As it is deployed, the longerons, diagonals and battens snap into place. The boom can be constructed of low CTE material such as T300 graphite, resulting in only ~70 milliwatts conduction from the Spacecraft to the instrument module. Dynamically, the boom is rigid and stable. Even after a slew the boom returns to position very accurately - errors between the star trackers (located on the S/C) and the fine guidance sensors (located on the P/L) are ~arcseconds. 15 American Institute of Aeronautics and Astronautics

51 HARD Mirror Concept Expandability Generic Options for Space Vehicle Design Parasol Shield Piggyback Shield Payload-on-a-Stick Advantages : Integral spacecraft-payload Lightweight shield Disadvantages: Operation of spacecraft at cryo temp Heat sources near SI and OTA Science Instruments Advantages: Compact design Simple structures Disadvantages: Limited FOR Spacecraft heat sources near OTA and SI Spacecraft Advantages: Easier spacecraft thermal No heat sources near payload Disadvantages: Complicated dynamics Predicted Temperature Distribution The following chart presents the NGST temperatures with the telescope located at an elevation of 0. Note that the mirror temperatures are <30 K, the desired value. The left side of the instrument compartment, where the IR instrument passive radiator is located, is at 25 K, adequate to cool the FPAs to ~ 30 K for near infra-red (NIR) imaging. 16 American Institute of Aeronautics and Astronautics

52 Predicted Temperature Distribution 5 Assumptions Instrument Module dissipation of W Parasitic heat load of 0.1 W Q = 4 MW 46 Q = 1.1 W SA043 Sun/Thermal Shield Design Options The baseline is a sun shield of two mils silvered Teflon, followed by four shields of 1 mil mylar with vacuum deposited aluminum on both sides, with an angle of 5 between the shields. This permits the cavity between the shields to radiate to deep space. Deployment of the shields was a major issue. Early versions had inflatable shields. However, we had serious concerns over the additional weight of the bladders, gas for inflating, and how to rigidize the structure. Outgassing and deployment were other issues of concern. We baselined a strut deployment which would then pull out the sun and thermal shields. The size of the shields is sufficient to prevent either the sun- or earth-shine from striking the telescope and to accommodate a 10 tilt in the entire SV for pointing. Early versions of our shields had an asymmetric design (since the telescope gimbals in only one direction) to minimize shield size. Unfortunately, we found that the reaction wheels would saturate in ~11 hours due to unbalanced solar pressure. This led to the present symmetric shield. Eventually residual torque will spin up the wheels anyway, so methods of dumping the momentum were developed. We considered trim tabs on the edge of the sun shields, but it is difficult to keep the telescope from seeing the hot tabs. An option that looks promising is to use panels covered with electrochromic materials that change reflectivity based on the voltage applied. This changes the resultant momentum by a factor of ~ two. Issues remain on material selection. Another effect that must be compensated for is spin momentum buildup. Any mismatch in shield symmetry will cause it to act like a propeller. This could be stopped and the wheel momentum dumped by twisting the struts to change the pitch of the propeller. 17 American Institute of Aeronautics and Astronautics

53 Sun/Thermal Shield Design Options Multi-layer insulation was first considered as shields Weight of spacers between layers added considerably to mass Analysis showed that single sheets with an angular difference between them was as efficient and saved considerable weight Inflatable shields were considered and rejected Added weight for the inflated portions (double thickness) and inflation gas Concern on how to ridigidize the inflated spokes and rims Concern that UV hardening required thermal shields that could withstand direct solar heating Concern that hardening compounds might outgas Concern on rigidity of structure after tilting or twisting TRW has demonstrated deployable booms/arrays Booms can be easily applied to this task Wire rigging can pull out the shields Other Key Trades We point the telescope coarsely by moving the elevation gimbal, and then by tilting the SV and rotating the entire SV about its axis. Reaction wheels will accomplish this. We examined the moments of inertia of the system and found that the required 30 slews can be accomplished in well under the 15 minutes required (30 Az slew in ~8 minutes, 10 El pitch in ~9 minutes). Additionally, we examined the vibration modes of the system and found that the lateral bending modes of the spacecraft/mast/payload are about 1 Hz. The sunshield modes will likely be lower Other Key Trades (3/3) Ephemeris, Pointing, Control & Guidance Spectral Band Options µm 1-10 µm µm 1-20 µm µm 1-40 µm Fine Guidance Sensor Fields of View Fine Guidance Sensor Hubble-like Mechanical CCD Arrays Hubble GSC (14.5 mag) New 19th Magnitude GSC Instrument Cooling Passive Cryostat Cryocooler 18 American Institute of Aeronautics and Astronautics

54 in frequency. These are anticipated to damp out quickly, and any residual motion can be accommodated by fine pointing mirror in the optical train of the telescope. Reaction wheels are biased to spin at 10 Hz or higher. Fine Guidance Sensor Options The mission requirements state that pointing must be stable enough to not increase the diffraction blur by <20%. At 1 µm, this corresponds to an AIRY disk diameter of 0.03 arcsec, and with 20% jitter, requires a pointing error of less than 6 milli-arcsec. Since a practical blur centroiding algorithm will provide location to ~1/5 of a pixel, this leads to a fine guidance sensor pixel size of 30 milli-arcsec. Given a FOV of 2x2 arcmin (see next chart), this results in an array size of 4000 x 4000 pixels, an easy value to achieve, with 18th magnitude, adequate signal-to-noise ratio exists to permit centroiding. Three Fine Guidance Sensor options have been considered. One is like Hubble, which used a large field of regard field of regard but few pixels. Hubble used a mechanical arm to move a very small field of view within the. Given the limited Field of regard that we need at 18th magnitude, and given that we can readily buy enough pixels to cover this field of view, we rejected the Hubble concept. Separate guide Fine Guidance System Sensor Requirements Mission Requirements Diffraction limited optics at 1 µm (1.2 l/d) Pointing stability 20% of diffraction blur Pointing System Requirement Diffraction blur: 1.2 x 1e-6/8 = 0.15 µrad = 0.03 arcsec Allowable jitter/drift: 6 milli-arcsec With adequate SNR, can use centroiding to locate a star ~1/4 to 1/10 of the FGS pixel size Assuming 1/5 => FGS pixel size is ~30 milliarcsec Given FOV requirement of 2 x 2 arcmin (see previous chart): 4000 x 4000 pixels required Adequate SNR exists Flux from 18th magnitude star: 58,000 photons/sec (8 meter telescope) Image blurred to cover ~4 pixels: 14,500 photons/sec/pixel SNR (1 sec): ~sqrt (14,500) = ~120 SNR (0.1 sec): ~sqrt (1450) = ~40 (Note: Quantum efficiency of pixels assumed to be ~1) Fine Guidance Sensor Options Hubble-Like 5"x5" mechanical Use outer edges of main telescope FOV pickoff mirror Operate in visible Use mechanical pickoff mirrors to locate guide stars 69 arcmin2 FOR Relay starlight to an interferometer FOR of FGS magnitude dependent (see following chart) Main FOV Large Arrays Use outer edges of main telescope FOV Operate in visible with 19th magnitude guide star catalogue Pave a sufficiently large area with FPAs such that high probability that star is in FOR - ~3x3 arcmin FOV FGS FOV Main FOV Main Mirror Separate Guide Telescopes Two 45 cm Cassegrain visible light telescopes 4 x 372 x 372 arcsec FOV (~150 arcmin 2 ) 14.5 magnitude guide star catalogue required Located at right angles to each other and to the main telescope axis FGS Telescopes 19 American Institute of Aeronautics and Astronautics

55 telescopes were considered and sized. We rejected this concept based on limited volume in the fairing and the potential for misalignments between telescopes. Instead, the Large Array concept uses the existing main telescope field of view. Multidiscipline Design Optimization. Our paper describes the process used in the aerospace industry to develop design concepts for space science missions, using our Next Generation Space Telescope Feasibility Assessment Study [1] as an example. The process begins with articulation of the need for a mission, a definition of its objectives and an estimate of the funding which is available. For NGST, the need and objectives were provided by the report of the "HST and Beyond" committee [2], while the funding level was determined by the savings which NASA could achieve by discontinuing HST maintenance activities after the 2003 servicing mission. A mission concept and spacecraft design are then developed by a multi-disciplinary team organized by function or spacecraft element into Integrated Product Teams. These teams identify design options which meet the mission objectives, and select the most promising alternatives through a series of trades and analyses. Their selection criteria include system performance as well as cost and risk. If no design solution is found, the requirements are modified and new technologies [3] are introduced until an "optimum design" is achieved. Design optimization is an iterative process, with more detailed designs and analyses generated during each iteration. For the NGST CAN study we used relatively simple thermal, dynamic and optical models to assess system performance and utilized existing spacecraft designs wherever possible. Much more detailed models and designs were generated during our current mission architecture study, including an integrated model to assess the end-to-end optical performance of our baseline design in the dynamic and thermal environment predicted for NGST. The use of highly integrated system performance models for design optimization is a new trend in spacecraft design, made practical by recent advances in computer technology. Ideally, integrated models can be used to determine the sensitivity of our design to key parameters and find an optimum configuration. To date, however, high fidelity simulations are best obtained by linking existing stand-alone "industrial-strength" software tools with special purpose "translators". And building a detailed system performance model is a labor-intensive process which can only begin when a detailed design of the spacecraft is available. Low fidelity integrated models using linked spreadsheets running on PC's are now being used by integrated design teams at many aerospace companies and government laboratories. It is important to have a well developed set of mission requirements and well defined mission concept before going to a design center; however; since a typical design effort a week of effort by highly skilled engineers and scientists. The use of multidicipline design teams is a powerful tool for exploring the design space to find a optimum solution, since experts in all of the relevant areas are readily available. They must be used judiciously, however; to control costs. Powerful analytic tools are available for design optimization, but more work needs to be done to link them together. Before a design centers or integrated models can be used effectively, much effort must be expended to refine the mission requirements and "zero-in" on a feasible mission concept and baseline design. 20 American Institute of Aeronautics and Astronautics

56 Summary The objective of this paper was to look at the spacecraft design process and see how that process balances desired spacecraft features within an imposed set of operational and cost constraints. The constraints often show up as competing multidiscipline interactions, which in their resolution lead to practical spacecraft designs. This paper gives examples of how the design process was implemented in a feasibility design study for NASA's proposed Next Generation Space Telescope (NGST), and describes how the project organization was used to effectively deal with multidiscipline design. Orbit selection, spacecraft propulsion, station keeping, and overall mechanical and thermal subsystem designs were discussed as examples of multidisciplinary design optimization. The final section discusses multidiscipline design optimization, what its benefits are, what are the negative points and what can be done to improve the process. Acknowledgments This work was supported by the National Aeronautics and Space Administration under Cooperative Agreement No. NCC References 1.TRW-Led Next Generation Space Telescope Feasibility Assessment Study Results, ed. C.F. Lillie, TRW, Exploration and the Search for Origins: A Vision for Ultraviolet-Optical-Infrared Space Astronomy, Report of the "HST and Beyond" Committee, ed. A. Dressler, AURA, The Next Generation Space Telescope, ed. P.Y. Bely, C.J. Burrows, and G.D. Illingworth, STScI, Visiting a time When Galaxies Were Young, ed. P. Stockman, STScI, American Institute of Aeronautics and Astronautics

57 AIAA MULTIDISCIPLINARY DESIGN PRACTICES FROM THE F-16 AGILE FALCON * Michael H. Love Lockheed Martin Tactical Aircraft Systems ABSTRACT An advanced version of the F-16 called the Agile Falcon was studied and a preliminary design was developed in the late 1980 s. Multidisciplinary design issues were addressed through trade-offs at the conceptual and preliminary design levels. Trade studies and associated approaches from a perspective of how they effected the course of the design process are discusssed. The interest of the Agile Falcon was directed at a balance of multirole capability. The results of the studies focused the airframe toward an F-16 type trapezoidal wing. Ensuing studies involved optimization of the wing to maximize the multirole capacity while constraining/minimizing impact to existing hardware. The redesign of the wing touched all aspects of the airframe and subsystems. INTRODUCTION In the early 1980 s General Dynamics Fort Worth Division (now Lockheed Martin Tactical Aircraft Systems) conducted studies to investigate the incorporation of advanced technologies into an F-16 with a larger wing. The interest was directed at maintaining a balance of multirole capability. The results of the studies focused the F-16 variant, called Agile Falcon, toward an F-16 type trapezoidal wing. Ensuing studies involved optimization of the wing to maximize the airplanes multirole capacity while constraining/minimizing impact to the fuselage and empennage. The redesign of the wing however touched all aspects of the airframe and subsystems. Multidisciplinary, multi-objective design issues drive aircraft design. For example, the Agile Falcon program was focused to enhance the F- 16 s current state of agility. The agility measure includes multi-objectives of maneuverability and controllability. Difficulties in design decisions arise from the uncertainties of what one might categorize as the weighting factors of a systemlevel, multi-objective function. In other words, priorities of the multiple objectives in a system design are usually not clear. The Agile Falcon program 1 attempted to address these issues in a systematic approach in the predevelopment stage prior to full scale development. Figure 1 depicts the Agile Falcon at the end of its predevelopment phase in Figure 1 Agile Falcon At Completion of Predevelopment Program Methods used in the data development to support the Agile program have since evolved. For example, a combination of computational fluid dynamics analyses (CFD) and wind tunnel testing would be used in lieu of extensive wind tunnel testing for performance and stability and control data acquisition. In this paper, methods and processes used in the Agile program are examined and compared to those that might be used if the Agile Falcon were being developed today. Agile Falcon Objective The F-16 was born in the 1970 s from the light weight fighter program. Over the last 20 years it has provided the Air Force both air-to-air and * Copyright 1998 by Lockheed Martin Corporation. Published by the American Institute of Aeronautics and Astronautics, Inc. with permission. Engineering Specialist Senior, AIAA Senior Member American Institute of Aeronautics and Astronautics

58 AIAA air-to-ground combat capability. Its light weight and efficient aerodynamic design have provided outstanding agility characteristics. Advanced versions of the F-16, however, are less agile than its earlier versions. Increased capabilities in areas such as pilot awareness have led to increased vehicle weight. Studies were initiated in the 1980 s to regain F-16A agility. Many papers in the 1980 s discussed the topic of agility 2,3 In reference 1, agility in a fighter aircraft sense was defined as performance needed to win and survive close-in combat. Furthermore, maneuverability and controllability as they are related to agility are discussed as shown in Figure 2. Maneuverability is the quality that changes the flight path vector of an aircraft. It results from the sum of forces (lift, weight, thrust, and drag) that cause a change in the speed and direction of the flight path. Controllability is the ability to guide flight path changes. Maneuverability leads to such measures as turn rate, acceleration and deceleration. Controllability leads to such measures as rates and accelerations of aircraft states. Together, controllability and maneuverability in a fighter aircraft allow its pilot to win dog fight encounters with opposing aircraft. A pilot will Figure 2 Characteristics of Agility call on the aircraft, for example, to turn, accelerate, turn again, decelerate, fire a missile, and accelerate suddenly to gain the advantage on another aircraft and win a multi-bogey engagement. In order to address maneuverability and controllability, the Agile Falcon program focused on the development of an advanced wing and wing/strake/fuselage integration. Trade studies were performed to develop information measuring agility as defined through controllability and maneuverability metrics as related to geometric variations of the wing and wing/strake/fuselage integration. DEVELOPMENT APPROACH A predevelopment program was executed to improve turning performance, increase the AOA capability, maintain adequate controllability in the roll axis throughout the AOA envelope, and minimize impact to existing systems on the F-16. The turning performance and AOA capability are consistent ingredients to maneuverability. Controllability in the roll axis was emphasized at high AOA to allow sudden changes in flight paths while allowing maximum maneuverability. All existing systems on the F-16 were evaluated to constrain/minimize cost impact from wing/strake/fuselage modification. American Institute of Aeronautics and Astronautics

59 AIAA Two of the airframe studies will be used to illustrate how agility was addressed during the Agile predevelopment phase. One study involves the overall synthesis of a baseline wing/strake/fuselage configuration; the second illustration encompasses development of the wing design within the context of the baseline configuration. Baseline Wing/Strake/Fuselage Configuration Prior to the predevelopment program, concept sizing studies were performed to define a neighborhood for potential Agile Falcon solutions. These studies included traditional parametric databases for weight, costs, and aerodynamics. These databases were founded on the F-16 and provided stable measure for sensitivity studies. The study-results led to selection of a matrix of wings and strakes to build a more accurate parametric space and provide refinement to a baseline wing/strake/fuselage configuration. The selected configurations are depicted in Table 1 and Figure 3. This matrix of configurations included 3 strakes in combination with 7 wings. The Baseline wing was derived during the aforementioned synthesis study. Data was developed for these configurations with regard to agility characteristics and structural integration. The agility characteristics were studied through the combination of wind tunnel tests followed by analyses. The structural integration studies included airframe layout studies combined with preliminary level aeroelastic synthesis evaluation. The data developed in these studies was combined in a qualitative evaluation. Table 1 - Candidate Wing Configurations Config. Span (ft) Area (sq ft) Sweep # 1 # 2 # 3 # 4 # 5 # 6 Baseline Span Trade Area Trade Sweep Trade Figure 3 Three Planform Trades Agility Characteristics Figure 4 presents the flow of wind tunnel tests and analyses performed in the matrix study. Two series of tests were performed to provide a screening process for the later more expensive transonic tests. The configurations tested were full-up F-16-like models (1/9th scale). As seen in the figure, the first set of tests concentrated on an understanding of characteristics in extended regions of AOA where basic lateral directional stability and American Institute of Aeronautics and Astronautics

60 AIAA Low Speed Low Speed & Transonic Aeroanalysis Polar Shape Aeroanalysis Flap Sched. Trim C L MAX Drag C L MAX Wing/Strake Selection Trim C L MAX Drag Improv Configuration Selection 7 WINGS x 3 STRAKES CG AOA Stability and Control Aft CG Limit AOA Limits Lat/Dir Stab. Compromise AOA & Polar Mid & High AOA Polars Good High AOA Stab. CG AOA Stability and Control Aft CG Limit AOA Limits Lat/Dir Stab. Polar Improvement Highest C L MAX Good High AOA Stab. Figure 4 Aerodynamic and Stability & Control Screening Process CL MAX could be evaluated. These parameters are key in the maneuverability and controllability area. A Taguchi experiment was performed during the wind tunnel testing to reduce followon low speed and transonic testing. From the results of the first tests, a down-select to one strake/4 wings was made for the follow-on combined low speed and transonic testing. In the testing, no one configuration provided superior performance in combined CL MAX and stability in extended AOA. However a cluster of 3 configurations seemed to be the best performers: 2, 3, and 6. General conclusions from a stability and control viewpoint included (1) minimizing span and (2) moving the wing aft for balance. Conclusions from an aero/performance viewpoint included increasing L/D with span and increasing CL MAX with area. Both disciplines also recommended continued tailoring of the wing/strake area as key. Structural Integration Structural evaluation of this matrix involved quantitative and qualitative studies. Structural sizing issues needed to be evaluated as well as system integration issues. Benefits from any aerodynamic configuration selected should not be impeded by structural weight increases, wing deformation characteristics, or system changes. The Wing Aeroelastic Synthesis Procedure, TSO, was used to evaluate structural sizing issues 4,5. All of the parametric variations in wing span, wing area. and wing sweep were studied. Design optimization was performed in each case for a variety of objective and constraint functions. In addition to the planform variations, a study of wing t/c and material properties was included. Typical optimization results for varying concepts of aeroelastic tailoring are shown in Figure 5. The wing box skins were designed in each configuration for three different design goals/concepts. A minimum weight Strength Sized design was achieved with three aircraft simulated maneuvers (two symmetrical pull-ups and one asymmetric rolling pullout). In the second concept, a flutter requirement and an aileron roll control effectiveness requirement were added to the strength requirements ( Aeroelastic Sized ). The third concept added an aeroelastic twist requirement to the strength and aeroelastic requirements. The aeroelastic twist provides lift-to-drag efficiency at the simulated turn maneuver point. American Institute of Aeronautics and Astronautics

61 AIAA AIRCRAFT SKIN WT (LBS) A/C SKIN WT (LBS) DRAG SIZED AEROELASTIC SIZED STRENGTH SIZED WING SPAN (FT) SKIN WT DRAG WING SPAN (FT) Figure 5 Optimization Study Examined Weight, Design Concepts, and Performance The top part of Figure 5 displays the sensitivity of the wing box skin weight with respect to the concepts and span. The span study (shown above) provided the greatest sensitivity while the sweep (not shown) provided the least. The bottom part of Figure 5 provides the sensitivity of the aeroelastic drag to the wing skin weight for the Drag Sized concept. Interestingly, the area study (not shown) indicated that as area increased, the weight decreased to a point before beginning to increase. This observation was rationalized by the increase of wing depth for a fixed t/c allowing for gains in structural efficiency up to a point. Therefore, Configurations 2 and 3 provided interest for further study. CL MAX Wing Area (Sq. Ft.) LIFT-INDUCED DRAG COEFF. Airframe layout studies were performed to examine system interface issues. Considered in these studies were landing gear placement, engine and engine accessories placement, interface of fuselage-based wing control surface actuation subsystems, interface of wing/fuselage fuel systems, and wing/fuselage interface loads. Structural arrangements studies involved placement of wing spars and ribs as well as fuselage carry-thru bulkheads. Qualitative assessments were made with regard to ease of integration. Configurations 2 and 3 were the highest ranked. Quantitative assessments were made in terms of mass properties estimation for each configuration. Although these estimations were parametrically based, the aforementioned TSO studies (a subset of the estimates) substantiated the findings. The results were provided to various analysis groups to evaluate performance and stability. Selection of New Baseline Configuration Derivation of a new baseline from this information was performed through a qualitative analysis. Stability and Control considerations led to the conclusion that the baseline span of 37.5 feet needed to be reduced. Aerodynamic performance considerations lead to the conclusion that although increased span over the F-16 provides substantial improvements in L/D, increased span with increased area might provide enhanced stability with no degradation in L/D. Figure 6 illustrates this in showing the sensitivity of CL MAX and CD at CL MAX. The increased area provides for the aft shift of aerodynamic center for stability considerations while allowing the increase span for L/D CL MAX Wing Area (Sq. Ft.) Figure 6 Sensitivity of CL MAX With Wing Area American Institute of Aeronautics and Astronautics

62 AIAA performance. Figure 7 shows data from the TSO study indicating that an increase in area with fixed t/c could offset an increase in span in terms of structural weight. AIRCRAFT SKIN WT (LBS) SPAN WT (LBS) AREA WT (LBS) SWEEP WT (LBS) SPAN (FT) AREA (SQ.FT.) SWEEP (DEG.) Figure 7 Weight for Area Increase at Fixed Span Offsets Weight for Span at Fixed Area Increase These pieces of information coupled with the system interface studies led to a new configuration baseline. The process for determining a new configuration involved an integrated product team approach considering the positives, negatives and sensitivities of the aforementioned studies. While the system integration studies are not shown, they provided indications to ease of design and manufacturing assembly, as well as costs of the Agile Falcon. The new configuration was determined through a combined selection of wing-span, wing-area, wing-sweep, strake, and wing-placement with respect to the fuselage. Impact of Design Technologies On Approach While the study to establish a refined baseline involved development of multidisciplinary sensitivities, the number of data points established was few; and the ability to establish an accurate parametric connection of the data to agility was not there. For example, each of the wings studied in the matrix allowed for integrated computation of turn rate performance, which involves L/D, CL MAX, and airframe weight. There was not enough time or information, however, to integrate controllability measures. Time history maneuvers would have allowed characterization of the vehicle s full agility. Finally, three points in sweep, three in span, and three in area as considered in the wing matrix study, allowed characterization of a second order curve of information. However, there was always question on information distant from any of these points. With the current capability of computational fluid dynamics, enough wing/strake/fuselage combinations could be evaluated and transformed into response surfaces to allow consideration of a design space, rather than a sampling of the space. Similarly, the ability to develop structural finite element models and perform ASTROS-like design optimization studies 6,7 would allow structural evaluation on a finer level. Response surface techniques lend to design of experiment approaches 8. Given such methods, syntheses can be performed that allow examination of many configurations approximated through the response surface. Agility metrics involving controllability and maneuverability could be evaluated and factored into battle scenarios. Parametric modeling of aerodynamics and structural configurations is imminent. Design of experiment approaches may occur in an automated fashion in the future. A missing link is the development of techniques for control law modeling to allow parametric time history evaluations in rapid fashion. In the case of an active aeroelastic wing, redundant controllers can be used with augmented control objectives where force imbalance constraints are combined with maneuver load control metrics to achieve control surface gearing per maneuver 9. A generic control approach 10 may also provide initial through-put for DOE in the design of airframe. The issue lies in the overall vehicle synthesis, its mission scenarios and overall vehicle class (e.g. subsonic attack vs. supersonic air superiority). Often the metric for design is not clear. The question to be answered is how a vehicle will be used and how it will respond in a combat environment. To perform such simulation, integrated measures of agility are required. Response surfaces can allow rapid evaluations of inputs to the agility measures such as turn rate over a wide range of geometric variables. American Institute of Aeronautics and Astronautics

63 AIAA Much of the data developed with regard to system integration was qualitative, requiring man in the loop to evaluate the many possibilities. Genetic algorithms combined with object oriented modeling languages may serve to automate systems integration. Object oriented approaches to conceptual design are being explored 11,12. Not presented here is any approach to bring affordability into the decision process. This metric is a function of many discrete decisions that are linked to materials and manufacturing processes. Historically, we have relied on weight-based cost. It is conceivable that object oriented approaches may enable rapid evaluation of activity based costs as functions of geometric parameters and inclusion of such data as an independent variable. Wing Design The wing design integrated three studies toward enhanced agility for the Agile Falcon. An aerodynamic performance study focused on the development of the wing twist and camber distribution for maximum maneuverability. The objective of the study centered on a balance in high-g turn objectives and 1g acceleration objectives. Controllability studies focused on definition of the control suite of the wing to satisfy low speed (high AOA) and high speed (structural flexibility) handling qualities. An outboard aileron was considered in addition to the F-16 baseline flaperon (inboard trailing edge surface). The structural studies included an assessment of aeroelastic tailoring strategies that would best complement the maneuverability and controllability initiatives. The evaluation criteria for the three studies consisted of measurement in (1) turn rate, (2) roll performance, (3) structural weight (wing and fuselage), (4) impact to fuselage structure and fuselage based systems, and (5) airframe producibility. The present discussion of the wing design is presented from the bias of the structural studies and where they interfaced with the aero/performance and stability and control studies. Focus on Structural Studies The baseline material for the Agile Falcon wing skin was advanced graphite composites. Extensive material trades were performed. Within these trades was a study of aeroelastic tailoring. Three concepts were derived: (1) Washout - minimum weight including a constitutive tendency of the wing to twist negatively with positive bending; (2) Washin - minimum weight including a constitutive tendency of the wing to twist positively with positive bending; (3) Strength - minimum weight with the requirement that the wing only meet general strength integrity. The objective of the study was to find the aeroelastic tailoring concept most suited to benefit the aero/performance and controllability studies. Included in the sizing were detailed requirements such as buckling, bolted joints, fuel pressure, and wing skin producibility. The process of sizing and evaluation is shown in Figure 8. The TSO program 13 had been used in the context of internal loads development for over ten years at the point of this application. Interface tools were developed to allow the mapping of TSO results to a finite element model. The MODGEN program was tailored to the quick development of wing finite element models. The process of a TSO skin development study and a wing finite element model at this time was approximately an eighty hour task. The wing model was attached to a stick fuselage representation allowing fast evaluation of flexible aerodynamics in the FLEXLODS code 14. A critical loads study was performed for some time on the Agile program, so therefore, identification and mapping of a critical loads case simply involved derivation of the aeroelastic tailoring concept and associated aeroelastic increments to the model. Each concept was then uniquely sized with an in-house tool known the Composite Panel Analysis Package (CPAP). A new set of aeroelastic analyses were conducted for the resized concepts. Aeroelastic deformation data was provided to the aero/performance group allowing integration of aeroelastic increments to the drag polars developed for candidate rigid wing distribution shapes (rigid camber and twist). Flexible-to-Rigid ratios were provided to the stability and controls group and applied in a 6- DOF simulation. The aeroelastic tailoring concepts were selected for detailed study for various reasons. The Washout concept American Institute of Aeronautics and Astronautics

64 AIAA CONCEPT TSO Skin Optimization DEVELOPMENT FLEXLODS Flexible Aerodynamics EVALUATION MANEUVERABILITY High g Turns, 1g Accel MODGEN Internal Arrangement LODSUM Critical Loads Selection CONTROLLABILITY 6-DOF Simulations NASTRAN Stiffness Generation NASTRAN / CPAP Internal Loads & Sizing SYSTEM INTEGRATION Weight & Producibility Figure 8 Aeroelastic Tailoring Concepts Were Systematically Evaluated demonstrated, in the Validation of Aeroelastic Tailoring program through wind tunnel tests, a 23% reduction in lift-induced drag over rigid aerodynamics. The Washin concept is noted for its propensity to maximize lift and control surface effectiveness. The Strength concept allows for minimum weight and presumes that enough control effectiveness is available through redundancy. Each concept has valid benefits. The ranking of the concept results in the study is presented in Table 2. The Washout concept provides the best overall performance to the design metrics. Table 2 Ranking of Aeroelastic Tailoring Concept Results Concept Maneuver Control Weight Producibility Washout Washin Strength In the Maneuverability category, analyses were performed for loiter, maneuver, and acceleration. Wing deformation information was provided in a semi-empirical, linear superposition code that was tuned to rigid wind-tunnel data. Therefore, analysis credit was acquired for aeroelastic increments. The distinguishing characteristics involved the negative bend/twist coupling of the Washout concept, allowing minimum jig-shape camber and twist. The Washout concept then excelled in sustained turn rate and acceleration. The distinguishing feature of the Washout wing in the Controllability metric is its relief of roll damping while retaining roll control. The roll control of the Washin and Washout is comparable. The damping behavior of the Washout and Strength concepts is comparable. Figure 9 illustrates the difference in roll rates for the three concepts in 1-DOF simulation. The data are normalized to the Washout concept. The project also compared the Washout, Washin, and Strength concepts in 6-DOF simulations. Other 6-DOF simulations were performed for configurations with outboard aileron combined with the inboard flaperon. These controllability studies were performed at high speed / high dynamic pressure, and the results were considered in combination with low speed handling quality studies where wing flexibility is not the issue. At the time the Agile Falcon program was canceled, the baseline configuration consisted of a single inboard flaperon with the Washout concept. The weight metric includes the wing weight and impact to fuselage weight. Considering wing weight alone, the Washout concept is the heaviest. However, due to the load relief and distribution of load at the wing/fuselage interface, the Washout concept surpasses the Washin concept in minimum weight. The load relief and load distribution of the Strength concept is similar to that of the Washout concept and is the lightest weight concept to begin with. American Institute of Aeronautics and Astronautics

65 AIAA Roll Rate Fraction of Washout Altitude (1000 ft) 0.9 Mach Mach Washout Washin Strength Roll Rate Fraction of Washout Altitude (1000 ft) Washout Washin Strength Figure 9 Roll Performance of Aeroelastic Tailoring Candidates Producibility is measured by the gradient of thickness changes per orientation over the entire wing skin. For manufacturing, the wing skin needs to be dividable into areas or zones of constant thickness per orientation. The Strength concept was derived from the gradient-based optimization of TSO, and it was the most complicated laminate wing skin definition. While the Strength concept was developed through design optimization, a more structured approach of pre-zoning might be taken to improve its producibility. The same might be said for the Washin and Washout approaches. The Washin design has the fewest number of zones because its percentage of thicknesses per orientation remains approximately constant throughout the wing skin. The Washout concept could be broken into a producible number of constant percentage zones and overall thicknesses. The Strength concept, as it was derived, would require a large number of constant percentage zones. Impact of Design Technologies On Design Approach Like the vehicle synthesis phase of the Agile Falcon program, the approach to achieve integration would probably be the same today as in The differences in the overall process would be in the tool selection for developing the data and the amount of data generated to perform the needed evaluations. Recent directions in development of ASTROS 15 and NASTRAN 16 allow that there is little need for TSO in this phase of design. Design optimization with nonlinear aerodynamics (such as CFD-based pressures) is becoming a reality. However, the aeroelastic increments would still be computed with linear aerodynamic influence coefficients. Codes such as ISMD from Boeing North American 9 even make it possible to consider the aerodynamic design of wing camber in the structural design process. The computation of accurate lift induced drag is complex, however, and the trends at best are the only thing believable. A design-of-experiments approach could be used with a modal- based design optimization 17 to arrive at optimal camber and robust structural design 18. In addition to deriving optimal camber, ASTROS and ISMD could be used in an active aeroelastic wing approach to evaluate interaction with control laws with redundant control effectors. In the Agile Falcon approach, only the wing structure was sized per concept. The load distribution at the wing/fuselage interface was considered qualitatively in a weight measure for the wing skin concepts. However, the true measure is in the sizing of the fuselage structure. The wing is a very small percentage of the basic design flight gross weight. Saving weight is important, but the center fuselage is densely packed with systems and loads. It is important to be able to quantify the benefits of redistributing loads across the fuselage, which aeroelastic tailoring accommodates. Today s technology allows for this. Maneuverability evaluations could be developed today in the CFD realm with aeroelastic deformations superpositioned on the rigid geometry and the trim state provided at 6-DOF trim conditions to create a rigid CFD configuration for analysis. These shapes could be used for CFD-based drag computations. Of course, the test-anchored linear superposition American Institute of Aeronautics and Astronautics

66 AIAA approach could be used again. There still appears to be no tool that can adequately handle an iterative CFD-based nonlinear aeroelastic solution for a full aircraft configuration, although many are pursuing such a tool. The process for Controllability studies would be little different today. The time to achieve this analysis would be shortened, and the number or conditions evaluated would be greater. Designs in the near future might aggressively pursue an active aeroelastic wing approach, which would necessitate a tight connection between the structural design and the control law design. In other words, the robustness of the control system would depend on the robustness of the structure 18, since an active aeroelastic wing approach consists of a strength concept for composite tailoring. The design of the structure is tightly coupled to the assumptions of the control laws. There is currently little feedback of requirements from the control law group until after the structure is designed. Today, conservative assumptions are made to ensure the structure covers all reasonable usage of control effectors in the development of loads. Minimizing loads and minimizing structural weight drives the control laws to a tentative state. A key area of technology development is a process and tools for performing controls/structures feedback early in the design process that allows the designer to focus on robustness issues. Affordability is the metric of the day, and it typically factors in producibility. ASTROS and NASTRAN have design variable definition options that allow the user to maintain control of thickness gradients over the topology during design optimization. The design results would then be mapped to electronic CAD datasets for further evaluation. Tools such as PICASSO 19 were developed during the Agile Falcon era to begin to address these issues. PICASSO maps zones of constant percentages and thicknesses into composite ply tables that interface from zone to zone. This tool allows the rapid deployment of tailored laminates to producibility evaluation tools. In addition, a study today would include mapping the manufacturing data back on the internal loads model for an analysis iteration prior to sizing convergence. As we look further to the future, parametric and associativity concepts will allow us to consider more items simultaneously in the design study. Structural arrangement versus system integration may play greatly into the structural weight computations. As was mentioned, in the Agile Falcon approach, the load distribution at the wing/fuselage interface was considered qualitatively in a weight measure for the wing skin concepts. In the future, resizing of the fuselage structure could be considered for various structural arrangements that accommodate subsystems in the overall configuration. SUMMARY / CONCLUSIONS The Agile Falcon program was a program focused on multidisciplinary design optimization. The objective was to maximize the agility of the F-16C while minimizing cost to do so. The objective was decomposed into developing a design focused on enhancing maneuverability and controllability while minimizing impacts on aircraft weight and subsystems. This paper examined two central studies performed in the course of the program; (1) refinement of a wing/strake/fuselage configuration, and (2) development of the wing design including structures definition, aerodynamic jig shape, and selection of the control effector suite. These studies required coordinated efforts to bring data together at key decision points. Decisions were made in the configuration development on the basis of quantitative and qualitative assessments. No formal recomposition of the design metrics was performed to evaluate whether an optimum was achieved. However, it was determined that the product concept was improved at the completion of the predevelopment program. If the design were being performed today, the emphasis on higher resolution would drive the number of data points considered. Computational capacity continues to grow in terms of accuracy and turn-around. Tighter integration is evident in many areas, allowing closer evaluation of multidisciplinary couplings. However, it seems that to truly use multidisciplinary design, a system level evaluation must be maintained to recompose sublevel studies into system level payoffs. American Institute of Aeronautics and Astronautics

67 AIAA Although it is obvious, one would be remiss to not make a statement on the importance of culture. The nature of the Agile Falcon and the personalities involved allowed the program approach. Integrated design is a conscious effort of tasking processes to develop essential knowledge allowing strategic decisions that account for all design requirements. It is mission dependent. For instance, a design more prone to flutter requires more flutter analyses during the course of design. It relies on trade studies. The LMTAS integrated philosophy is to ensure that essential requirements are considered during the trade study process. The strength of LMTAS integration is derived historically from the coordination skills of our Design function 20. New design technologies may well redefine Design, but they will not be accepted until the culture accepts them. ACKNOWLEDGEMENT The efforts reported in this paper were supported under Air Force Contract Number F C CCP 4563 titled F-16 Agile Falcon / MLU. The author gratefully acknowledges the support of the U.S. Air Force. REFERENCES 1) Franks, J.M., Timpson, K.G., F-16 Agile Falcon / MLU Final Report, Volume I, Airframe / Subsystems Studies, Air Force Systems Command, F-16 Systems Program Office, 90PR064, 11 December ) McAtee, T.P., Agility - Its Nature and Need in the 1990 s, presented at the Society of Experimental Test Pilots Symposium, September ) Hodgkinson, J., Skow, A. et al, Relationships Between Flying Qualities, Transient Agility, and Operational Effectiveness of Fighter Aircraft, AIAA Paper ) Lynch, R.W., Rogers, W.A., and Braymen, W.A., An Integrated Capability for the Preliminary Design of Aeroelastically Tailored Wings, AIAA Paper No , Aircraft Systems and Technology Conference, Dallas, Texas, September ) Love, M.H., Bohlmann, J.D, Aeroelastic Tailoring in Vehicle Design Synthesis, presented at the AIAA/ASME/ASCE/AHS/ASC 32nd Structures, Structural Dynamics, and Materials Conference, April, ) Love, M.H., Barker, D.K., and Bohlmann, J.D, An Aircraft Design Application Using ASTROS, WL-TR , June ) Barker, D.K. and Love, M.H., An ASTROS Application With Path Dependent Results, presented at the AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, September ) DeLaurentis, D.,Mavris, D.N., Schrage, D.P., System Synthesis in Preliminary Aircraft Design Using Statistical Methods, Presented at 20th International Council of the Aeronautical Sciences (ICAS). 9) Zillmer, S., Integrated Multidisciplinary Optimization for Aeroelastic Wing Design, Wright Laboratory TR , August, ) Ausman, J. and Volk, J., Integration of Control Surface Load Limiting into ASTROS, presented at the 38th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, April 1997, Paper No. AIAA ) Blair M. et al, Rapid Modeling with Innovative Structural Concepts, presented at the 39th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, April 1998, Paper No. AIAA ) Zweber, J. and Blair, M., Structural and Manufacturing Analysis of a Wing Using Adaptive Modeling Language, presented at the 39th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, April 1998, Paper No. AIAA ) Love, M.H., Milburn, R.T., and Rogers, W.A., Some Considerations for Integrating Aeroelasticity in CAE, presented at the ASME Winter Annual Meeting, December, 1987, Paper No. 87-WA/Aero ) Hoseck, J.J., Lyons, P.F., and Schmid, C.J., Development of Airframe Structural Design Loads Prediction Techniques for Flexible Military Aircraft: Theoretical Development, AIAA Paper No , AIAA Systems American Institute of Aeronautics and Astronautics

68 AIAA and Technology Conference, August 1981, Dayton, Ohio. 15) Love, M.H., et al, Enhanced Maneuver Airloads Simulation for the Automated Structural Optimization System - ASTROS, presented at the 38th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, April 1997, Paper No. AIAA ) Whiting, B., and Neill, D.J., Interfacing External, High Order Aerodynamics into MSC/NASTRAN for Aeroelastic Analysis, presented at the MSC Aerospace User s Conference, November ) Karpel, M, Moulin, B., and Love, M.H., Structural Optimization with Stress and Aeroelastic Constraints Using Extendable Modal Basis, presented at the 39th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, April 1998, Paper No. AIAA ) Zink, P.S., Mavris, D.M. Love, M.H., Karpel, M., Robust Design for Aeroelastically Tailored / Active Aeroelastic Wing, presented at the AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, September ) Wang, B.P., Twu, M.J., Costin, D., and Eisenmann, J.R., and Norvell, R.G., Laminate Ply Stacking Sequence and Ply Termination Selection, presented at the 30th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, April 1989, Paper No. AIAA ) Love M.H., Integrated Airframe Design at Lockheed Martin Tactical Aircraft Systems, presented at the AGARD 82nd Structures and Materials Panel Meeting - Workshop on Integrated Airframe Design Technology (Sesimbra, Portugal), May American Institute of Aeronautics and Astronautics

69 THE F-22 STRUCTURAL/AEROELASTIC DESIGN PROCESS WITH MDO EXAMPLES Nick Radovcich Division Manager Aeroelastic Analysis Lockheed Martin Aeronautical Systems AIAA Member & David Layton Flutter & Dynamics Engineer Lockheed Martin Aeronautical Systems AIAA Member Abstract Documented experiences of Multidisciplinary Optimization (MDO) applications during the engineering, manufacturing, and design phases of fighter aircraft programs are not numerous. Documentation is even rarer for aircraft that have flown. This paper describes in general terms the overall design experience of the F-22 fighter, and rapidly focuses on the aeroelastic/structural considerations where MDO like processes were employed. Central to the design process is the Air Vehicle Finite Element Model ( A/V FEM). The A/V FEM is the common element to link design requirements and processes for loads, flutter, stress, dynamics, and control law design. Multidisciplinary aspects of the interdependent processes includes stiffness tailoring for meeting flutter requirements, control law tailoring for redistribution of external loads, flex to rigid tailoring for satisfying handling qualities, stress sizing and aeroservoelastic filter design within the general subject of aeroelastic optimization. The investment of using a controlled A/V FEM for loads, stress, flutter, dynamics, control law integration, weight estimation, etc., was to a significant measure responsible for the excellent stiffness and loads tailoring which resulted in a minimum weight design while satisfying the airplane performance requirements & allowing for the structural design parameters to be successfully iterated. The large A/V FEM was manageable in terms of configuration control, integration with specific discipline analysis processes, overall tracking/storing, and processing terabytes of data. The recovered cost of using a large model was returned many times over by savings in man-hours than if structure decomposition/back transformation methods had been employed. A very detailed loads grid, fuel tank fuel-vapor boundaries matched to maneuver attitude and g loading, and detailed internal and external pressure loading were other challenges successfully achieved to satisfy the Integrated Product Teams (IPT) requirements. The procedure for modifying panel flexible pressure loads to reflect nonlinear wind tunnel rigid pressure distributions, especially due to control surface deflections, provided a high degree of fidelity to the flex to rigid and flex loads calculations. Finally, the computer access for the users drove all the necessary MDO like processes. The computational power and ease of use provided a capability to successfully manage the terabytes of data across wide area networks and many types of computing platforms. Additionally, the storage of results in relational databases provided fast and direct answers to questions with real time qualifications. Introduction The road to a production F-22 fighter started with concept studies during the mid-1980 s and a prototype fly off under the banner of Advanced Tactical Fighter (ATF) which was concluded in December of Participants which included competing teams and multi-company collaborators had a number of role changes as the project came from behind the tightly closed doors during the concept days and into a more visible prototype days. The project is in the Engineering, Manufacturing and Development (EMD) phase. Full envelope expansion is planned to start in May 98 for ship 4001 at Edwards Airforce Base after a successful series of first flights conducted in Marietta during the third quarter of The deciding milestone for the project came on the award of the EMD contract to Lockheed in first quarter 1991 after the conclusion of the prototype flight test program. The Lockheed prototype design demonstrated adequate performance, LO, and maneuvering characteristics. With the external geometry basically fixed, the focus of the design shifted to internal arrangement and design developments to satisfy maintainability, supportability, etc. requirements with weight as the principal metric for satisfying performance requirements. Late in 1991, a number of trade studies were integrated into the design to help manage the challenging weight constraints. These studies foreshortened the fuselage by two feet and set the main landing gear configuration in the wing. There were also minor changes to the planform of all lifting surfaces and control surfaces based on refined wind tunnel force models. There are many interrelated requirements and constraints, which enters into the design process and consequently the evolution of the design. This paper will focus on the design to data development, which was required to evolve the structure concepts and design. Six areas were available to define the basis for the structural design: 1 American Institute of Aeronautics and Astronautics

70 Basic geometry; materials initial structural definition. External loads driven by Airplane Simulator Responses due to Maneuvers defined in the Loads Criteria and Weight. Flexible to Rigid Ratios. Stiffness/Mass distribution for Flutter Margin Requirements Vibroacoustics environmental definitions and high cycle fatigue design Flight Control Laws and Aeroservoelastic SSt ttaabbi iil lli iit ttyy Requirements. The integration of various disciplines represented by the foreshortened list of six is largely governed by the constraints imposed by many competing requirements. Ideally, full derivatives would be derived for aircraft performance, LO signature, weight, equipment placement, maintainability, affordability, external loads, stiffness requirements, etc. with respect to each of a very large number of design variables. Structures decided during the EMD proposal phase that an approach would be pursued which would return to the Project the greatest value for the resources expended. The core issue for this approach was the utilization of a single vehicle FEM for all derived design to data used to design the Structure: Vehicle loads (external, internal, internal pressures, etc.), Flutter and dynamics assessments, Flexible to rigid ratios, Extraction of material design allowables, Aeroservoelastic analyses. A balance in the vehicle FEM detail between accuracy and affordability was driven by the following requirements: The vehicle FEM had to have sufficient detail for internal loads definition Model size could not overwhelm: Databases for tracking and managing the many FEM configurations (symmetric, anti-symmetric, left, right, and control surface deflections) Data management and computer usage requirements for using the vehicle FEM without alternation by Flutter and Loads The summary of the process flow for structure design to data is found in Figure 1. The data flow shows that loads and flutter analyses are performed using a FEM (- 1) which is one design (model) behind the FEM (0). More importantly, there are lags up to 3 design cycles for new flexible to rigid ratios and loads tailoring data to be incorporated into an updated flight simulator. Changes like loads tailoring had to first go through control law development cycle. Stress allowables, which define fatigue life requirements, may lag the process by 2 or more cycles. As bad as this may appear, as measured by external loads, stiffness requirements, and control law developments, the process did converge. The major perturbation to the process was the changes coming from the Detail Design box. Here the variability in the sizing and model grid and element changes caused significant changes in internal loads for a near equivalent external load definition. In addition, the process was further removed from the desired MDO approach because not all of the Integrated Product Team s (IPT) budget profiles matched the requirements of the Process Flow Chart for an orderly convergence. With minimum weight requirements dominating the structural design concepts, the IPTs dependence on fine grid structural sub-models grew. Small variations in load redistribution sometimes caused major shifts in margin calculations. This was a consequence of forcing mathematical zero margins in a fine grid FEM where large derivatives of internal load changes were possible for small changes in sizing or grid definition. The efficient computing and data management systems employed in the F-22 design development may have produced a downside or two. The IPTs decided to ask for redistribution of external loads on fine grid FEM sub-models. This permitted the using of a model without going through the pain of understanding how the structure really works up through ultimate load. The computer showed how a particular FEM could be made to work without the proper controls on how well the FEM itself represented the structural concept. Good design concepts, which work on the hardware airplane, are the deciding factors for establishing an efficient structural system that are lightweight, robust, and cost effective while avoiding single criteria minimum weight solutions traps. Time lags in data availability appear due to the various processes schedule requirements and the sequential nature of the inter-related processes. In addition, some design decisions must be done early into the design process before a good definition of the structure is known, such as locating the flight controls sensors. 2 American Institute of Aeronautics and Astronautics Statement of Problem Documented experiences of MDO applications for fighter aircraft during the design development phases are not numerous. For aircraft that have flown, documentation is rare. The technical community knows the power of MDO and not having a cradle to grave example has been a continual source of frustration, as

71 voiced by AIAA MDO technical committee members over period of years. Scope and Methods of Approach This paper describes in general terms the overall design experience of the F-22 fighter, and rapidly focuses on iterative aeroelastic/structural design processes (Figure 1) to highlight MDO like processes which were used. Central to the structural design process is the Air Vehicle Finite Element Model (A/V FEM). The A/V FEM is the common element for loads, flutter, stress, dynamics, and control law design to processes. Multidisciplinary aspects of the interdependent processes includes stiffness tailoring for Flutter requirements, control law tailoring for redistribution of external loads, flex to rigid tailoring for handling qualities, stress sizing, and aeroservoelastic filter designs within the general subject of aeroelastic optimization. Finally, there are lessons to be learnt from this exercise and in particular the special requirements of a fighter where volume is a premium and structural concepts may be inherently non-optimum shapes as opposed to transport aircraft where the volume permits fundamentally optimum shapes and concepts. Team Interaction and Policies To achieve a minimum weight design while meeting the performance goals required close coordination between the customer and contractor as well as among the contracting team members. As a result of this close coordination a tailored design criteria was established to keep the design constraints specific and relevant to the F-22. This entailed defining in close concert with the customer a structural criteria document that was specific to the F-22 usage and performance. The team integration was achieved by instituting policies and guidelines that each of the tri-company team members would be required to follow. These included developing a common set of material properties, conducting analysis with common or equivalent software tools, and building an Air Vehicle Finite Element Model (A/V FEM). Additionally, significant effort was expended to ensure that the engineering design and analysis was closely integrated with ground and flight-testing. This was accomplished by developing detailed test plans in coordination with the customer that was specific to the F-22. Air Vehicle Finite Element Model The A/V FEM provides the foundation for the overall design process by providing a common basis for configuration control and analysis. The A/V FEM is the common interface for many disciplines as shown in Figure 2) to develop design to data. This single model 3 American Institute of Aeronautics and Astronautics is used to compute internal and external loads, flex-torigid ratios, flutter design requirements, and thermodynamic response. Figure 3 illustrates the size, complexity, and the number of configurations tracked for this single model. The individual super elements were built by the F-22 team member responsible for the structure and then assembled for analysis by the prime contractor Lockheed Martin Aeronautical Systems Company (LMASC). A very detailed set of guidelines was established and documented early in the program to ensure compatibility among the organizations developing the model. These included defining the numbering convention, definition of acceptable element types, and the use of defaults and parameters. Additionally, the document included definition of any requirements defined by the functional disciplines to support their independent analysis tasks. An example in this document was the requirement that the composite laminates be explicitly defined in the comment statements to facilitate aeroelastic sensitivity analysis at the composite ply level. The A/V FEM was manageable in term of configuration control, integration with analysis routines, overall tracking of the design, and storage/processing of terabytes of data. The cost of using a large model to generate aeroelastic design to data was insignificant compared to the savings in man-hours achieved by using one verified model whose configuration control and responsibility for accuracy was vested in one group. External Loads The air vehicle flight simulator drove computation of external loads for transient maneuvers defined in the loads criteria report. The rigid air loads were based on extensive wind tunnel pressure model test data. While the flexible incremental load distributions were derived using linear panel load methods, the panel loads were adjusted on component basis based on wind tunnel rigid integrated load values. The process permitted adjustments for non-linear effects especially near the control surface hinge line. Another unique feature of the load process was the computation of the fuel tank pressure distribution consistent with the fuel free surface orientation for the specific maneuver and fuel load distribution that was consistent with the load condition. Finally, hammer shock inlet pressure distributions were used based on computational fluid dynamics (CFD) analytical codes and test data. A major milestone during the first year was the release of a full set of design loads based on CFD data. The loads latter agreed with the wind tunnel data to within 5 percent. The CFD released loads were for complete set of control surface deflections.

72 Load tailoring by Maneuver Load Control was established early in the EMD design phase. How much could the ailerons be used to dump the load inboard was a function of two design considerations. The first was the effectiveness of the ailerons and the second was the impact of the increased drag on performance. The points in the sky where the maneuver load control (MLC) could be most effectively utilized, however, was almost on top of the maximum performance point. There was aggressive tailoring of the control surface gain schedule to achieve weight benefits with MLC while holding the performance degradation to a minimum. Load tailoring was achieved by minimizing adverse airplane responses during critical load s maneuvers. Close coordination with developers of flight control laws and quick turnaround for potential solutions on the flight simulation program were just two of the critical process that lead to successful closure. Load s engineers take six or more time hacks during each maneuver on the flight simulation. Critical loads are identified for reduction and the time hack and associated maneuvers are identified. Negotiations between Flight Controls and Handling Quality (HQ) engineers and Loads engineers establish proposed changes to the flight controls to tailor the loads. The cycle is complete when the changes appear in the flight simulation and a full load s analyses and a complete HQ studies show that the tailored loads have been achieved without introducing new issues for either HQ or Loads. Loads and flex-to-rigid tailoring through ply lay-up optimization was attempted after the basic design was established. Studies were conducted for the wing and vertical fin surfaces. Derivatives for each of the ply directions did not show large gains without impacting other constraints. The ply directions for the wing proved to be near optimum for basic loads. The wing layout naturally encourages efficient ply direction allocation because of the planform geometry. The zero plies run parallel to the elastic axes for the outer wing. This is also true for the vertical fins. Buckling mechanism is another significant factor for each of these surfaces. During the prototype trade studies, predominant buckling mode improvements could be achieved if ply lay-ups had non-traditional orientations of (0,45,90). This is impractical from a materials testing point of view because of the costs associated with a greatly enlarge data base requirements. In each of these areas the weight penalty due to low derivative values required other options to be pursued. 4 American Institute of Aeronautics and Astronautics Internal Loads and Margin of Safety At Lockheed-Martin in Marietta, external loads for maneuvers and fatigue were processed through the vehicle FEM and the resulting internal loads were loaded into Oracle relational database. The designer and stress analyst had immediate access not only to the current loads released but also to past releases. The analyst then could compare what changed or work on different releases of the drawings. With weight a significant factor in the design process, many parts had zero margins of safety when released. With changes in the internal loads, some of those zero margin areas could no longer support the new internal load distribution. In the course of the process that followed, the question was raised, what is the flight envelope for the aircraft with negative margin? A complex and data intensive methodology evolved where point analysis programs generated margin of safety values for some 3000 load cases and then through interpolation of flight conditions, contours of zero margin of safety were derived in the Mach and Altitude plane. Then Aircraft Operating Limits (AOL) were then determined for the aircraft within the structural capability and the derived limits based on what structural testing was completed up to that point. This margin of safety versus flight envelope methodology will be a significant aid as the airplane explores the testing envelope where critical load conditions exist. Temperature Effects Temperature distribution affects structural design in the selection of materials and in the introduction of thermal induced stresses. Material allowable for composites is a function of maximum temperature and amount of moisture saturation. Hot-wet properties for composites dominate the maximum temperatures allowed in the design. For aircraft structures constructed with dissimilar coefficient of expansion materials, such as mechanically joining of aluminum with composite components, thermal strains must be accounted for in the internal load definitions. Flutter Definition of the air vehicle flutter margin and the necessary design to data lagged the detail design by no more than a single design iteration and significant changes were brought back an iteration to implement in the aeroelastic model. Analysis metrics was established to facilitate tracking of the detail design. This included the definition of a procedure to compute, for each control axis, the total control loop stiffness, detailed weight estimates of control surface hinge-line inertia and center of gravity, and unit loads on the A/V FEM to track the structural flexibility.

73 The aeroelastic requirements were derived from sensitivity and optimization of the design parameters. The design variables consisted of three primary types: percent changes to physical properties such as crosssectional area and skin thickness; composite laminate properties such as the addition of a single ply at a given orientation angle; laminate material axis sweeps where the material axis for an entire surface is rotated. Table 1.0 lists a breakdown of the variables on a persurface basis. To facilitate defining requirements in terms of true sizing variables accurate and automated sensitivity analysis to aeroelastic parameters is required. The F-22 program utilized in-house specialized software for sensitivity analysis. Additionally, a powerful Convex computer was available with over a terabyte of disk and 10 terabytes of tape capacity. Multiple complex analysis models and optimization was utilized to determine if a synergistic solution would provide a decrease in weight or increase in performance. For example, as part of the aeroelastic optimization process a strength heuristic constraint was implemented. The heuristic approach defined the amount of material that can be removed in an area when additional material is added while not violating strength requirements. For example, if the optimization calls for adding plies to a laminate at +/-45 degree s then either 0 or 90-degree plies can be removed, the heuristic algorithm constrains the amount to be removed. Additionally the process implements rules defined in the structural policy document such as keeping the percentage of plies at a given orientation angle within specified limits. F-22 structure effected by this type of sizing includes the vertical fin and rudder. Interestingly, material added above the strength size design for aeroelastic reasons at one design iteration turned out to be necessary in some areas for strength on the next design iteration. Aeroservoelastic Aeroservoelastic stability margins were defined by running a coupled analysis of the A/V FEM, the aeroelastic mass distribution, unsteady aerodynamics, and flight control laws. This multidisciplinary task was accomplished by Flutter organization by computing aircraft responses in the frequency domain and then coupling these responses with control law s supplied by Flight Controls. Both the control laws and the aircraft responses were computed for a set of mach/altitude/fuel loading /maneuver load conditions that spanned the flight envelope with a heavy concentration in critical regions. The process did iterate and converge by Flutter defining bandpass/lowpass filter requirements for each control law release. These changes were then implemented and reflected in a subsequent release of 5 American Institute of Aeronautics and Astronautics the control laws. The sensitivities of the location of both the rate-gyros and the Nz accelerometer were examined. However, moving the sensors were not required as structural filters in the control laws provided adequate stability margins. Both open loop and closed-loop ground testing was completed prior to first flight to obtain data that could be correlated with the analysis. Minor tailoring of the filters was required after these tests. Dynamics There are two principal focuses with respect to structural dynamics. The first is the definition of the vibration environment to support the design of both airframe structure and equipment installations. The basis of this environment was flight test data acquired during the YF-22 (prototype) flight test program. Large databases of acoustic and acceleration data were assimilated into the Environmental Criteria Document to support detail design. The second focus was the vibration environment to predict and test the high cycle/low cycle fatigue life of structural sub-systems, equipment, tubing, avionics, etc. Flexible To Rigid Ratios The flexible to rigid ratios are computed by Loads Department and is forwarded to the Aerodynamics Department for integration with rigid aerodynamics database. These data are used directly by the controls department to generate inputs to the flight simulation model, which in turn is used by Loads to determine maneuvers critical to establishing design loads. DADT /Stress Allowables Crack growth analysis was the backbone for establishing durability limits for the aircraft. Parts were designed for 8000 hours of life. Durability Analysis and Damage Tolerance (DADT) established working stress allowables throughout the structure. Point analysis was performed to support MRB (manufacturing rework board) activities using the same databases and techniques established in the basic design. Detail Design The major issue in detail design was the enormous pressure to meet allocated weight targets. Continuous trade studies absorbed manpower and schedule resources and as a consequence made the task of getting FEM updated with best if not forward looking data a very low priority task. Since the FEM is the pivotal connection to all facets of generating design to data, the inaccuracies in the FEM had serious impact of the rapid convergence of the design process.

74 FEM Changes The process of building a finite element model for a complete vehicle is complex and time varying. Rapid convergence of the model configuration and properties requires the team to look into the future to where the model arrangement and the individual finite element properties will eventually converge. The challenge to be ahead of the actual detailed design is made more complex when three groups in three different companies attempt to operate as a single unit and overcome the different cultures, which by tradition operated as a single unit within each company. Significant organizational tasks were required to assemble a model with many interfaces. This integration task almost becomes an end to itself. What went into the model in so far as material properties, sizing and grid point selections was by its very nature less visible and therefore less likely to be challenged. In the end, the devil was in the details for specification of sizing data, grid point selection, and material properties. Near the end of the design iterations, the biggest variation in internal loads was in FEM property changes and not the external loads. Typical Processes During Iteration The basic design iteration was a process that essentially created data sequentially. For example, a FEM was required before basic load process could start. All external loads must be computed before internal loads could be established and loaded into the relational database. All of the internal loads were required before sizing of aircraft parts could start. And finally, the aircraft parts had to be designed before the FEM could be updated. Within this basic design loop, stiffness requirements were established using FEM and mass distributions together with unsteady aerodynamic representations, which in turn were supported by wind tunnel flutter model testing. Stiffness requirements often worked inside the basic design cycle at a rate of 2 or 3 iterations to one full design cycle iteration. The design iteration would not work practically unless each group in the design process worked with models and data that were one or more iterations behind the current cycle. Also, strategic short cuts had to be taken during some of the iterations to get forward looking models and designs to leap frog the full design iteration schedule. Additional short cuts were required when requirements had to be updated to support long lead manufacturing schedules. This required analyst to accept or specially modify what ever the vehicle system analysis maturity was available at that time. In some cases the requirements were limited to only subsystems. The actuator stiffness loop requirements were decided years ahead of the 90% drawing release dates because of the long lead times for the control surface actuator development and testing required for flight. The flight 6 American Institute of Aeronautics and Astronautics controls development was planned for late software releases because handling qualities was dependent on extensive wind-tunnel testing and the integration of structural flexibility effects into the simulation model from which the processes of control syntheses so heavily depended. But external loads was committed to using maneuvers from the same HQ simulation model to determine in-flight loads as they occurred and not arbitrary maneuvers based on specific criteria such as maximum control surface deflections. The process flow of specific tasks was more like a quilt than a simultaneous interacting derivation of design to data. Figure 1.0 illustrates the basic interactions and the box show the iteration cycle lags that some of the process-generated data entered into the design. The complete design iteration cycle included external loads to internal loads to design update to the FEM update for the next iteration. The initiation of complete cycle which included fatigue design to data generation was major commitment of program resources. During this major design cycle, there was many timely injection of stiffness requirements. The stiffness and high cycle fatigue requirements often short circuited the outer loop with 2 or more updates within one overall large loads, design and FEM update cycle. Another iteration loop, which operated inside the main loop, was load tailoring. This was particularly true during the last phases of the design development. Load tailoring will probably continue during flight-testing. Rather than being a well ordered sequence of events, the team injected updated design to data where the leverage to impact the design had the most benefits in terms of the resolving next most critical milestone. In this role, the team interpreted what the program requirements were, and even if a moving target, provided design to data with the best rate of return and still remain within the budget constraints of each IPT/Design to data function support. Vehicle Level Results Stiffness Requirements The control loop actuation stiffness requirements for each of the flight control surfaces namely the rudder, horizontal stabilizer, aileron, flaperon, and the leading edge flap was directly imposed on the IPTs. The definition of how to compute the loop stiffness for each control axis was defined in an Interface Control Document. This metric was used to allow the IPT s to determine the minimum weight design that satisfied the stiffness requirement. Typically, three IPT s were required to determine the stiffness allocation among the main surface, actuator, and control surface. Table 2.0 lists the breakdown in stiffness for each control axis.

75 Loads Tailoring With the design drawings basically released to manufacturing, load tailoring via control laws surface scheduling changes provided the tool to keep the existing design within the existing structural capability box while retaining the performance and HQ requirements. Design To Data Structure organization provided 90% of the design to data for the F-22. The effective management of internal load data permitted the controlled phased releases of drawings with manageable audit trails. The process provided flexibility when design updates required to release two different airplanes designs known as Block 1 and Block 2. The process kept the airplane design weight within the contract performance specifications. Design to data as issued from the Flutter organization consisted of defining true design data such as percent changes to physical properties such as cross-sectional area and skin thickness, and composite laminate properties such as the addition of a single ply at a given orientation angle. Figures 4.0 illustrate how data was transmitted to the appropriate Integrated Product Team. The important point here is that the Air Vehicle FEM was used as the vehicle to transmit design to data. This allowed for checking the design as to the incorporation of the requirements and for keeping a history of the requirements. Aeroelastic sizing requirements were defined for the horizontal stabilizer skins, vertical fin skins, rudder skins and substructure, flaperon skins, and wing mounted pylons.. Prior to transmission of the design to data coordination and agreement was reached between the functional organization and the IPT that these design changes could be accommodated. iterations. The large A/V FEM was manageable in terms of configuration control, integration with specific discipline analysis routines, overall tracking, storing, and processing terabytes of data. The recovered cost of using a large model was return many times over by savings in man-hours as compared to decomposition/back transformation approaches. The common basis for communication and changes to the model made the MDO like processes affordable and more to the point, feasible. A very detailed load grid, fuel tank fuel-vapor boundaries matched to maneuver attitude and g loading, and detailed pressure loading were other challenges successfully achieved to satisfy the IPT s requirements. The procedure for modifying flexible panel pressure loads to reflect non-linear wind tunnel pressure distributions especially due to control surface deflections provided a high degree of fidelity to the flexible to rigid ratios and flexible loads calculations. Finally, the computer access for the users drove all the necessary MDO like processes to successfully provide and manage the data across wide area networks, using many types of computing platforms, relational database storage of results for fast and direct answers to questions with real time qualifications. Summary of Important Conclusions The investment of using a controlled A/V FEM for loads, stress, flutter, dynamics, control law integration, weight estimation, etc., was to a significant measure responsible for the excellent results for stiffness and loads tailoring for minimum weight design while satisfying the airplane performance requirements. The structural design was successfully iterated during four major design cycles. For this type of aircraft, rapid convergence was achieved by: 1) satisfying external load strength and life requirements; 2) then iterate for stiffness and dynamic sizing requirements. These procedures generated critical design to data, which was required by the analyst and designer to provide insight into the available design space and the direction for moving the design. These studies provided data for uncoupling certain design parameters during the design 7 American Institute of Aeronautics and Astronautics

76 -2 Control Laws Dev. -3 Minimum Weight Design LO Constraints Equipment Packaging Maintainability Life Cycle costs Manufacturing Process Flow Loads Tailoring Flight Simulator Flex/Rigid Ratios -1 FEM External Loads FEM Internal Loads 0 Detail design Stress; Stability Life ; Stiffness Material Flutter Dynamics Stiffness -1 Requirements Stress Allowables Mission Profiles External Loads FEM Internal Loads Usage Spectrum Life Assessment -2 Element Changes Grid Point Changes FEM UPDATE Sizing Changes 0 8 American Institute of Aeronautics and Astronautics

77 AIR VEHICLE FEM FUNCTIONAL DISCIPLINES FLUTTER & DIVERGENCE AEROSERVOELASTICITY EXTERNAL LOADS INTERNAL LOADS FLEX- TO-RIGID RATIOS DESIGN TO DATA INTEGRATED PRODUCT TEAMS (IPT s) MID FUSELAGE WING AFT BODY COCKPIT EMPENAGE FORWARD FUSELAGE EDGES LANDING GEAR Figure 2 Discipline / IPT / FEM Relationship Figure 3 Air Vehicle FEM Figure 4 Communicating Design To Data 9 American Institute of Aeronautics and Astronautics

78 Surface Required Loop Stiffness (in-lb/rad) Frequency Range (Hz) Loop Requirement Impact Allowable Freeplay (Degrees) R.S.S. Stiffness/ Freeplay Driver At Life Stabilizer Pins Classical Flutter Weight = 79 Lbs Bearings LCO Rudder Weight =42 Lbs Buzz LCO Flaperon Weight = 6.0 Lbs Classical Flutter LCO Aileron N/A Buzz LCO Number of slices Classical Flutter Actuator # < Leading & Backup Stiffness LCO Edge Actuator # Backup Stiffness < LCO Flap Actuator # Backup Stiffness < LCO Actuator # Backup Stiffness < LCO Actuator # Backup Stiffness < LCO Fin See Rudder N/A Weight = 60 Lb. N/A See Rudder Table 1.0 Loop Stiffness Impact & Freeplay Requirements Surface Type Quantity Rudder Skins 118 Spars 6 Ribs 6 Vertical Fin Skins 138 Spars 10 Ribs 5 Flaperon Skins 132 Aileron Skins 72 Tail boom Skins 19 Horizontal Stabilizer Skins 162 Spar 15 Wing Skins 195 Spars 8 Total = 886 Table 2.0 Design Variable Distribution 10 American Institute of Aeronautics and Astronautics

79 AIAA A COLLABORATIVE OPTIMIZATION ENVIRONMENT FOR TURBINE ENGINE DEVELOPMENT Abstract A MDO scenario for the design and manufacturing process of gas turbine engine disks is developed. Highfidelity engineering analysis and process simulation tools are integrated into an optimization environment. While different formal MDO approaches are discussed, a sequential optimization approach seems to be best suited or this specific problem. The forging optimization results in a minimum-weight forgeable disk that meets all constraints in terms of process parameters. The optimization of the heat treatment process reduces residual stresses while maintaining required cooling rates through the modification of surface heat transfer coefficients. Optimization of both the forging and the heat treatment process individually has been successful, but the complete MDO scenario still faces a number of obstacles. Parametric CAD tools are not as robust for complicated geometry as it would be necessary in an automatic optimization environment. The same applies to the interface between CAD and CAE tools. Computational resources constitute another bottleneck - formal MDO algorithms tend to be slow in their convergence behavior, which makes them less well suited for problems requiring high-fidelity analysis codes with their long execution times. Despite all these obstacles, though, progress towards a comprehensive disk MDO environment is apparent. Introduction The design and manufacturing of gas turbine engines is a highly coupled multidisciplinary process involving design of the thermodynamic cycle, flow path and airfoil design, rotordynamics, and thermomechanical design for life prediction. An important aspect is the design and optimization of the manufacturing process of the mechanical components, requiring detailed simulation of forging, heat treatment, and machining processes. With the economic pressures which exist today, the need to develop affordable, high- * Staff Engineer, Member AIAA Manager, Mechanical Design Methods and Processes Program Copyright 1998 by P. Röhl, B. He, and P. Finnigan. Published by American Institute of Aeronautics and Astronautics, Inc., with permission. Peter J. Röhl *, Beichang He *, Peter M. Finnigan General Electric Corporate Research and Development Schenectady, NY performance defense systems, with shorter product development cycle times has never been greater. Propulsion systems are no exception considering their intrinsic complexity and strong system coupling with their associated aircraft or launch vehicles. The successful development of integrated propulsion systems is critically linked to our ability to perform system, subsystem, and component-level simulations of the design and manufacturing processes. Today, the problems are compounded because of the geographically distributed intra- and inter-company partnerships, including second and third tier suppliers, which are formed out of economic, technical, and product necessity. The ability for industry to develop, and cost-effectively deploy these systems, is predicated on its ability to rapidly simulate both products and processes to achieve globally optimized designs. To that end, there are a number of key technologies which are being developed and demonstrated under the DARPA-funded RaDEO (Rapid Design Exploration and Optimization) program 1 as part of the propulsion scenario. Under the RaDEO contract, the GE Research and Development Center is teamed with Engineous Software, Inc. (ESI) to develop a collaborative optimization environment based on isight 2, Engineous Software s optimzation framework. One focal point is the development of an optimization toolkit which enables the user to easily formulate an MDO problem and cast is into the form of one of the formal MDO algorithms supported by this toolkit. Another is the extension of the isight environment to facilitate the integration of CAD and CAE systems with the help of two toolkits, the Product Modeling Toolkit (PMTK) and the Discrete Analysis Modeling Toolkit (DMTK). The engine disk design problem is one of the application demonstrations to be addressed in this project. The Engine Disk MDO Problem The individual steps of the disk design process, broken down into the mechanical design and process/manufacturing aspect, are shown in fig. 1. Each of the five steps in the process can be further subdivided into a number of individual sub-steps with analyses at varying levels of complexity. The thermo-mechanical design, for example, starts with a simple 1-d analysis to obtain a rough thickness distribution of the disk. As knowledge about the design increases, more complex analysis models are created up to a full 3-d finite 1 American Institute of Aeronautics and Astronautics

80 AIAA Design Manufacturing Requirements Process Parameters Die(s) Billet Near-net Shape Disk Forging Process Parameters Mechanical Design Forging Heat Treatment Material Properties Finished Part HCF/LCF Data Life Prediction Geometry Material Finished Part Machining Residual Stress Part Life Residual Stress Distortions Process Parameters element analysis with tens of thousands of elements. A thermal transient analysis is performed on the disk to supply the mechanical design group with thermal loads for the different points in the design missions. These thermal loads are iteratively adjusted as the design progresses. Objective during the mechanical design phase is first and foremost the determination of the final disk shape, as early as possible in the design timeline in order to be able to release the forgings which tend to require a long lead time. A shape is to be determined that meets mission requirements at minimum weight and/or minimum cost. A detailed simulation of the manufacturing process is necessary in order to determine both residual stresses and final distortions of the finished part after machining operations. These residual stresses, in turn, are used in the subsequent life prediction of the part. Objective during the simulation of the forging process is the determination of the die shape on the one hand and of an optimum forging process on the other that ensures proper die filling without compromising mechanical properties of the disk through the violation of stress, strain, strain rate, or temperature limits. The subsequent heat treatment process is designed to generate acceptable mechanical properties in the forged disk. A simulation of the machining process results in the final disk shape with accurate residual stresses and distortions. If the distortions are within acceptable limits, an accurate life prediction of the part will be performed. Otherwise, the Fig. 1: Engine Disk Design and Manufacturing Process heat treatment or forging process need to be improved in order to achieve acceptable distortions. If that is not possible, the finished disk shape needs to be changed and the mechanical design - at least in parts - be repeated. The same applies in the case that the design does not meet life requirements. As this description demonstrates, an integrated procedure that addresses both mechanical design and manufacturing processes is absolutely necessary because of the iterative nature of the process and the prohibitive costs involved if changes become necessary once actual parts are being produced. Simulation tools for each individual stage are available and widely used. But opportunities for mathematical optimization of the individual process steps are currently not fully utilized, and an integrated procedure which is the ultimate goal of this research is missing altogether. If we try to recast the disk design problem in the form of a formal MDO problem, weight can be considered as the overall system objective, and the different objectives of some of the individual subsystems can be formulated as constraints. Weight here would be the billet weight of the forging, which, of course, also includes the weight of the final part, both of which need to be minimized. Since the forging billet weight is inherently much larger that the final part weight, a linear combination of the two in the following form could be considered as the system objective: 2 American Institute of Aeronautics and Astronautics

81 AIAA Mechanical ( α) F = α Wfinal + 1 Wbillet (1) Thermal Forging opt. Heat Treatm. Machining Fig 2: Multi-Discipline Feasible Formulation Mechanical Thermal Forging opt. Heat Treatm. Machining Fig 3: Individual Discipline Feasible Formulation In a multidiscipline-feasible type scenario (fig. 2), each of the disciplinary analyses would contribute a number of constraints to the system level optimization problem. In an individual discipline-feasible type scenario (fig. 3), the feedback loops from life analysis to mechanical design and from thermal analysis to mechanical design are severed at the cost of additional system level constraints accounting for the interdisciplinary discrepancies introduced. Both of these standard formulations are not very satisfactory for this type of problem out of several reasons. First, a large number of system level constraints would be introduced which are purely disciplinary in nature. It makes no sense for the system level optimizer to be bothered with all the intricacies of the forging optimization problem, for example. Additionally, the heat treatment problem is an optimization problem in itself, but it does not directly contribute to the overall objective, weight, but rather addresses producibility and the satisfaction of constraints for distortion and material properties. Therefore, the disk design problem calls for Life Life an approach where the optimization itself is distributed, and where each disciplinary optimization problem does not necessarily contribute directly to the overall objective. Both the Concurrent Subspace Optimization (CSSO) 3 and the Collaborative Optimization (CO) 4 methods have been looked at as possible solutions, but it seems that neither one of them really captures the salient features of the disk design problem. CSSO assumes a common objective that each discipline is somehow contributing to, and requires an approximation of the non-local states in each discipline. This means one would have to create an approximation of the forging problem inside the heat treatment problem and so on, which is not very practical. CO introduces artificial non-physical objectives for the disciplinary optimization problems so that for the designer it is somewhat difficult to follow the progress of the optimization from a disciplinary point of view. Besides, slow convergence rates in conjunction with long analysis times (in the order of several hours per analysis for the forging problem, for example) render this approach impractical. Therefore, it seems that in this case a sequential optimization within an integrated framework seems most promising (fig. 4), where we start with the mechanical design problem and simple 1- D and 2-D axisymmetric tools to obtain an initial disk shape, use this to design a near net shape forging process, then optimize the heat treatment process, and finally perform the machining and life analyses. opt. Mechanical Thermal opt. Forging opt. Heat Treatm. Machining Fig 4: Sequential Optimization Approach In subsequent loops, full 3-D analysis tools are used in the mechanical design phase. This sequential approach is possible in this specific case because the near-net shape forging optimization will not compromise the thermo-mechanical minimum weight design, and the optimum heat treatment process has no influence on either one of the two. Life 3 American Institute of Aeronautics and Astronautics

82 AIAA Simulation and Optimization Tools Optimization Framework The basic framework for the optimization environment under development is isight, a software product developed and marketed by ESI. isight is conceptually a follow-up product to Engineous 5,6, the optimization framework developed at GE CR&D during the 1980s. Both products facilitate easy integration of both commercial and company proprietary software into an overall optimization environment which makes use of the concept of interdigitation 7 where the user has a suite of optimization tools available, including gradient based and heuristic search techniques, genetic algorithms, and simulated annealing, which can be used in any combination during the optimization process. Experience over the years has shown that one optimization strategy alone is often unable to solve a problem, but that a combination of different strategies leads to improved results. isight enables the user to formulate a sequence of different optimizers and then apply this sequence to the optimization problem. Another strong point of isight is the ease with which analysis programs can be integrated into the framework, including large-scale engineering applications like finite element codes. These codes can reside on their respective platforms, irrespective of where isight is installed, an important point with respect to software leasing and maintenance cost for software which may be licensed only on a certain workstation. A number of toolkits are under development in conjunction with the RaDEO project, among them the Product Modeling Toolkit (PMTK) to support product data modeling and the interaction with commercial CAD software, and the Discrete Analysis Modeling Toolkit (DMTK), which facilitates the interaction of analysis models of different disciplines and levels of fidelity. Both of these toolkits are heavily leveraged in the engine disk design scenario. Process Simulation Nowadays advanced process simulation tools are becoming more and more available for all stages of the disk design and manufacturing process. Simulation tools such as DEFORM 8 and ABAQUS can accurately predict the mechanical behavior and properties during the manufacturing process. Therefore, these tools have become the state-of-the-art and are widely used. In combination with numerical optimization techniques, these tools offer the opportunity to improve individual steps in the overall process 9. In this application, DEFORM was chosen as the tool to be applied in the forging and heat treatment optimization procedure. CAD Tool The CAD tool of choice is Unigraphics 10, developed by EDS, which is the adopted CAD software at GE Aircraft Engines. Parametric master models control the geometry and engineering analysis views which support analyses at different levels of fidelity. These analysis- views - or context models - are defeatured models capturing the essential geometry for the respective analysis. They can also contain additional information necessary to generate the analysis models like boundary conditions and load and mesh information. PMTK will allow the user to graphically pick geometric design variables from the CAD model and automatically link them with the optimizer for topology optimization. Mechanical Analysis Finite element analyses are performed using ANSYS, with model preparation done partly in ANSYS and partly in PATRAN. PATRAN s P/THERMAL module supplies the required heat transfer data and temperature boundary conditions for the stress analyses. Different approaches are being evaluated for automatic analysis model generation from the CAD representation. One is the use of tags in the CAD model, where the CAD model would house all the information necessary to generate the analysis model. Another is the use of scripts that are reusable. This approach relies on a constant topology of the geometric model and entity consistency of the geometry import into the CAE tool. MDO Algorithms Current Status Implementations of both the CSSO and CO algorithms inside isight have been developed and tested 11,12. Since convergence of the CO algorithm tends to be very slow, its usefulness in detailed design applications requiring high-fidelity engineering analysis remains doubtful. One promising possiblity is the combination of the CO algorithm with response surfaces in order to reduce the number of analyses at the subsystem level. An initial implementation of the CSSO algorithm has been validated both with standard textbook-type example problems and with two more realistic problems representing a welding design and an idealized turbine blade. This CSSO implementation is currently being evaluated in connection with the disk design problem. 4 American Institute of Aeronautics and Astronautics

83 AIAA Forging Shape Opitmization A procedure has been developed to address the forging shape optimization problem, integrating Unigraphics and DEFORM with isight, leveraging functionality of the product modeling toolkit. Reference 13 describes the system in greater detail than is warranted here. The objective of the forging shape optimization problem is the design of a minimum weight forged shape that satisfies constraints on both forging press capacity, strain and strain rates, die filling, and minimum coverage of the final part shape. In the present study, forging is modeled as a timedependent, plastic-deforming, either isothermal or nonisothermal process. Since the forging simulation is conducted in an optimization environment, some of the process and geometry parameters are modified in each DEFORM run. Therefore, it is necessary to regenerate the mesh and redefine the boundary conditions. Furthermore, it is necessary to post-process the analysis results and extract information on optimization objective and constraint functions. Several modules have been developed that drive DEFORM to accomplish following tasks: import geometry and regenerate die and billet meshes, create appropriate boundary conditions, start DEFORM simulation in batch mode, monitor DEFORM runs, and postprocess simulation results to extract maximum press load, strain, temperature, etc. Each of these modules acts like a separate executable, or simcode in isight terminology. isight executes these simcodes in a pre-defined sequence, including potential looping and branching. Consider the forging shape optimization of a generic turbine disk. A cylindrical billet is forged into a disk of the shape shown in figure 5. The die geometry is captured in a Unigraphics parametric model. Several fillet radii R 1 -R 6 have been chosen as design variables. Both invalid geometry and intrusion into the minimum coverage over the so-called shipped shape, the intermediate shape in which the forging vendor supplies the part, and which is used for testing purposes, can be prevented by putting simple bounds on the design variables. It should be noted that simple bounds may not be sufficient to guarantee geometric validity in a more general situation. They work in this case because there is no coupling among the selected design variables. R6 R2 Figure 5: Turbine disk and its cross-section R4 R5 R1 R3 Thus, the optimization problem is formulated as min V, s.t. Rilb Ri R iub (i = 1, K, 6), P Pub, where V is the volume of the work-piece, P and P ub are the maximum press load and its upper bound, respectively, and R ilb and R iub are given lower and upper bounds of the fillet radii, respectively. The most aggressive shape, which corresponds to the lowest volume V, has been chosen as the initial design. It is relatively easy to get this shape from the specified disk design by adding a minimum cover. However, the press load constraint is usually violated for this design, and thus the fillet radii R i have to be increased which results in a larger volume. Subject to the press load constraint P ub, the optimizer will choose the optimal values of design variables Ri. As it is pointed out in the previous section, isight provides a suite of optimization algorithms. The modified method of feasible directions from ADS [14] is employed in this study. Since analytical design sensitivities are not available, the gradient information has to be obtained through finite differencing. 5 American Institute of Aeronautics and Astronautics

84 AIAA In the example we consider a time-dependent, plastic deforming, isothermal, closed-die forging process. The top and bottom dies are assumed to be rigid. The maximum load P normally occurs at the end of the forging stroke as the dies fill out and the material starts to move into the flash region. The load changes rapidly with the stroke at this stage of the process. Therefore, it is difficult to accurately compare the loads at the end of the stroke from different die designs due to the inherent noise in the load predictions. For this reason we artificially set P to be the stroke-averaged load in between 98-99% of the final stroke. A good estimate on the real maximum press load may be obtained by multiplying P with a correction factor. There are about 1600 quadrilateral elements on the workpiece, and automatic mesh regeneration is enabled to accommodate the large deformation that is inevitable in the forging process. Four design variables R 1 - R 4 are used in this application, and the time step is taken to be t = 0.1s. Due to repeated remeshing during the forging simulation, non-smoothness is introduced in the finite element solution. Therefore, we chose a 10% perturbation on the design variables during sensitivity analysis using finite differencing to smooth out the design space. Although the design sensitivities so calculated may not be very accurate locally, they provide the optimizer with the right search directions in a global perspective. 100 initial shape final shape design variable values number of simulations Figure 6: Initial and final shapes (left), and design variable values versus the number of simulations (right) for isothermal the forging process volume of the turbine disk number of simulations forging press load number of simulations Figure 7: Disk volume and press load vs. the number of forging simulations for the isothermal forging process The initial and final shapes of the disk are shown in Figure 6 (left). The history of design variable values against forging simulation runs is given in Figure 6 (right). The objective (volume) and constraint (press load) function values versus simulation runs are shown in Figure 7. All numbers have been normalized. The results suggest that the optimization is close to convergence after 15 simulation runs. There are some 6 American Institute of Aeronautics and Astronautics

85 AIAA downward spikes in the figures. The smaller ones are the result of finite difference perturbation, while the larger ones are due to line search of the optimizer. Since the abscissa shows the number of simulation runs as opposed to the number of optimization iterations, the results of both finite differencing and line search have been included. The upper bound of the press load P ub = 77.8 is shown as a dashed line in Figure 7 (right). It is apparent that the forging press load far exceeds this limit initially. As a result of the optimization, the press load drops from 96.9 of the initial design to 77.8, which is the upper bound, a 19.7% reduction. The volume, however, has been increased by 12.4% from 82.4 of the initial minimum-weight shape to 92.6 of the final optimized shape. In addition to the single step process described here, a multi-step forging process is presented in ref. 13. This work can be extended in several aspects: first, new interprocess communication mechanisms may be introduced to improve data passing between processes; second, a more comprehensive forging simulation should be conducted that includes the effect of heat loss during transport of the billet and positioning of the tools; third, a larger design space may be explored by incorporating more geometric parameters as design variables; finally, additional constraints, such as those on strain rate and temperature, should be considered to model more realistic situations. Heat Treatment Optimization The purpose of the heat treatment process is to develop the necessary mechanical properties in the forged part. This is achieved by heating the part to solution temperature and then cooling it rapidly. During the cooling phase residual stresses are introduced. In the case of Ni-based superalloys that are considered here, a certain minimum cooling rate has to be maintained to generate the needed creep and tensile properties. On the other hand, the faster the cooling process is, the higher are the resulting residual stresses which can lead to excessive part distortions after machining to the final shape. Traditionally, an oil quenching process has been employed which ensures fast cooling and thus a high cooling rate, but the oil quenching process introduces high residual stresses, and, from a process optimization point of view, offers very little room for improvement as there are very few parameters which can be controlled. Therefore, fan cooling is gaining larger acceptance where it is possible to control the airflow on individual sections of the part and thus influence the local surface heat transfer coefficients. Obviously, the heat transfer coefficients that can be achieved with fan cooling are lower than those for oil quenching, so that for thick parts it may not be possible to satisfy cooling rate requirements, but for moderately thick parts fan cooling offers clear advantages. For very thin parts like engine seals, where machining distortions due to residual stresses are especially critical, fan cooling may be the only process that produces acceptable parts at all. The challenge here is to formulate a fan cooling optimization problem without actually having to execute a combined heat transfer-stress analysis each time the optimizer needs a new design point. An accurate heat transfer analysis requires small time steps in the simulation, and a stress analysis, in turn, requires a fine finite element grid, therefore the combination of both is the most computationally expensive analysis possible. In general, though, the stress analysis is much more time consuming than the heat transfer analysis alone. Since it is known that spatially uniform cooling reduces residual stresses, the idea is to formulate an objective function that penalizes non-uniform cooling and at the same time ensures fast cooling at or above the target cooling rate. These are obviously two conflicting objectives since fast cooling always means uneven cooling as the heat can only be extracted at the surface of the part. Therefore, the objective function for the heat treatment optimization problem is formulated in a quadratic form that penalizes the deviation from the cooling rate target: obj = nodes ( target ) ( 1 ) ( target ) w t& 2 t& if t& < t& target w t& 2 t& if t& t& target (2) W is a user-defined weighting factor between 0 and 1 that penalizes under- and over-achievement of the target cooling rate differently. A value close to one (but less than one, of course) seems to give the best results. The target cooling rate is also a material-dependent value. Design variables are the surface heat transfer coefficients, h i, which can be related back to a certain airflow produced by the fan cooling apparatus. A total number of up to ten or twelve design variables seems to be in the range of what can be controlled by current fan cooling fixtures. The procedure developed here gives the user a choice in terms of optimization constraints. He can impose a hard constraint on the cooling rate: 1 t& t& if t& < t& target target ccr = nodes nodes 0 if t& t& target (3) This constraint has a discontinuity at zero, exactly where it is active, and will never assume a value less 7 American Institute of Aeronautics and Astronautics

86 AIAA than zero, that is satisfied and not active, caused by the if in the constraint formulation. This discontinuity leads to problems with gradient-based optimizers, which will always see a zero constraint gradient for a satisfied or active constraint, therefore in the case of constraint satisfaction the constraint value of zero is replaced with the difference of the target cooling rate and the minimum of all nodal cooling rates: c = t& t& cr target min (4) In this fashion at least the sign of the constraint gradient that the optimizer sees above and below a constraint value of zero will be equal. An additional constraint can be placed on the nodal fraction that fulfills the cooling rate target which has to be equal to 1.0 if the target is met everywhere. The two constraints may seem somewhat redundant, but depending on the optimization strategy used, one or the other or a combination of both lead to the best convergence. The heat treatment optimization procedure described above was applied to a generic turbine disk. Figure 8 shows the heat treatment geometry and the distribution of the nine design variables employed. h9 h8 h7 h6 h5 comparison of the initial and final cooling rate distribution (fig. 11 and 12), normalized with respect to the target value, indicating a much more uniform cooling than at the starting point. Constraint Value Cool Obj Iteration Fig. 9: Objective History Iteration Fig 10: Constraint History Ccr 1-Cnf h1 h2 h3 h4 Fig. 8: Turbine Disk Geometry and Fan Cooling Variables In order to cut down on analysis time, the optimization was started with all heat transfer coefficients linked to only one design variable. This problem was executed for six iterations, using the sequential linear programming technique from ADS inside isight, until both constraints were active. The full convergence history is depicted in figure 9, and the constraint history is shown in figure 10. Negative constraint values indicate a satisfied constraint. At this point, all nine design variables were activated, and the new optimization problem converged within seven more iterations, that is 13 total. For this segment, the modified method of feasible directions, also from ADS, was chosen as the optimization technique. The deviation function was initially reduced from a value of 1.4 to about 0.6 and then further down to under 0.2. These numbers as such have no physical meaning, but the significance can be seen in a Fig. 11: Initial Cooling Rate Distribution 8 American Institute of Aeronautics and Astronautics

87 AIAA Fig. 12: Final Cooling Rate Distribution The question still to be answered is what effect this optimization procedure, which is based on heat transfer analysis only, has on the residual stresses of the part which is what we are ultimately interested in. Therefore, a combined heat transfer-stress analysis was performed on both the starting configuration and on a disk with the final heat transfer coefficient distribution. For comparison purposes, an analysis of a typical oilquenching process was also performed. Fig. 13 through 15 show the resulting hoop stresses for the three cases, all normalized with respect to the maximum tensile stress of the oil-quenched part. The stresses are highest for the oil-quenched disk, closely followed by the non-optimized fan-cooled disk with uniform high fan blowing all around. The residual stresses for the optimized disk, in turn, are considerably lower, almost by one order of magnitude compared to the oil-quenched part in terms of tensile stresses. The reductions in compressive stresses are not quite that large, but still by a factor of between six and seven. These results clearly show the advantage of a numerically optimized fan cooling process compared to the traditional oil-quenching. Ref. 15 describes the heat treatment optimization process in greater detail. These findings were confirmed during multiple runs with different starting points on actual geometries which are of proprietary nature and cannot be shown here. The formulation of the objective function as a quadratic clearly aids in this behavior. Fig. 13: Hoop Stress, Oil-Quench Process Fig. 14: Hoop Stress, Starting Point Fig. 15: Hoop Stress, Final Configuration 9 American Institute of Aeronautics and Astronautics

88 AIAA Thermo-Mechanical Design The mechanical design and engineering analysis portion of the integrated process is currently lagging behind the efforts on the processing side. This has several reasons, one being that the development of fully parametric master models proved to be more timeconsuming than anticipated. But a major bottleneck is the automatic generation of high-fidelity finite element analysis models complete with loads and boundary conditions which update with parametric changes of the model. Several pilot projects have been ongoing since the last year, evaluating different concepts of relating analysis-related information to the geometry. One approach is the tagging of the geometry, applying basically CAE-type information on the geometry on the CAD side. A major hurdle here is reluctance from the side of analysis engineers who rather want to work within their CAE tool of choice instead of the CAD system. Also, the processing of tags inside the CAE tool has proven not to be very robust. Another approach is the use of scripts for the CAE tool, where the engineer prepares the model once manually and then saves the session log file for subsequent reuse. This approach demands entity-consistent import of the geometry from the CAD tool into the CAE system, which again is not robust at the moment. This approach certainly breaks down in the presence of topological changes. Before the issue of reliable, repeatable automatic generation of analysis models for complex 3- D-geometries is resolved, any effort to use optimization on the mechanical design side beyond conceptual studies is premature. Outlook The plan is to complete one full manufacturing process exercise by the end of the year. How fast the developments on the mechanical design side will be able to catch up remains to be seen and depends largely on external factors beyond GE CRD s control. In order to reduce analysis times for the forging optimization, the use of approximate models and response surfaces will be investigated. The machining simulation will be integrated with the heat treatment optimization package, so that the final machining distortions will be available automatically without manual intervention. Once the system is in place for the complete process simulation and process optimization, the question of the applicability of formal MDO algorithms will be revisited. In parallel, various strategies will be further investigated on how to capture analysis model information and make it reusable in a robust fashion so that analysis models for complex geometries will finally automatically update without human intervention. Once this obstacle has been cleared, 3-D-shape optimization during the mechanical design phase can be addressed, probably initially limited to relatively simple features comparable in complexity to the 2-D-forging shape optimization discussed earlier. Computer resources continue to be a problem in conjunction with the long analysis times required for the solution of industrial size problems. A forging simulation as it is considered here may take 6 to 7 hours on an SGI workstation. Finite differencing could potentially be done in parallel, but there are the problems of software licensing and maximum number of processes one user is allowed to run at any given time. It seems clear that the computer resource issues will remain a major bottleneck for the application of MDO to industry problems. One of the highlights so far in this project has been the optimization and integration framework itself, isight, which has performed very well, although still under development. It fits with GE s paradigm shift away from proprietary software development to the use of commercially available CAD and CAE tools, which require a loose and non-intrusive coupling of the individual analysis modules. References [1] A Collaborative Optimization Environment (COE) for MADE, Technical Proposal, General Electric Corporate Research and Development and Optimum Technologies, Inc., August 1995 [2] isight Version 3.0 User Manual, Engineous Software, Inc., Raleigh, NC, 1997 [3] Wujek, B.; Renaud, J.E.: Design Driven Concurrent Optimzation in System Design Problems Using Second Order Sensitivities, 5 th AIAA/NASA/USAF/ISSMO Symposium on Multidisciplinary Optimization, Panama City, FL, September 1994 [4] Braun, R.D.; Kroo, I.M.: Development and Application of the Collaborative Optimization Architecture in a Multidisciplinary Design Environment, Aug [5] Engineous User Manual, General Electric Corporate Research and Development, Schenectady, NY, 1995 [6] Lee, H.; Goel, S.; et al.: Toward Modeling the Concurrent Design of Aircraft Engine Turbines, Presented at the International Gas Turbine and 10 American Institute of Aeronautics and Astronautics

89 AIAA Aeroengine Congress and Exposition, Cincinnati, OH, May 1993 [7] Powell, D.J.: Inter-GEN, A Hybrid Approach to Engineering Optimization, General Electric Technical Report, Feb [8] Design Environment for Forming (DEFORM), Version 5.0, Online Users Manual, Scientific Forming Technologies Corporation, Columbus, OH, August 1997 [9] Kumar, V.; German, M.D.; Srivatsa, S.: Design Optimization of Thermomechanical Processes with Application to Heat Treatment for Turbine Disks, Presented at the Manufacturing International Conference, Atlanta, GA, 1990 [10]Unigraphics V13 Online User Documentation, EDS, Cypress, CA, Oct 1997 [11]Tappeta, R.; Nagendra, S. et al.: Concurrent Sub- Space Optimization (CSSO) MDO Algorithms in isight; GE CRD Technical Report, January 1998 [12]Conversations with S. Kodiyalam, Engineous Software, Raleigh, NC [13]He, B.; Röhl, P.J. et al.: CAD and CAE Integration with Application to the Forging Shape Optimization of Turbine Disks. To be Presented at the 39 th AIAA/ASME/ASCE/AHS/ASC Structural, Dynamics, and Materials Conference, Long Beach, CA, April 1998 [14]Vanderplaats, G.N.: ADS - A FORTRAN Program for Automated Design Synthesis, Version 3.00, VMA Engineering, March 1988 [15]Röhl, P.J.; Srivatsa, S.K.: A Comprehensive Approach to Engine Disk IPPD. Proceedings of 38 th AIAA/ASME/ASCE/AHS/ASC Structural, Dynamics, and Materials Conference, pages , Kissimmee, Florida, April 7-10, American Institute of Aeronautics and Astronautics

90 AIAA BOEING ROTORCRAFT EXPERIENCE WITH ROTOR DESIGN AND OPTIMIZATION Frank Tarzanin * Darrell K. Young The Boeing Company Philadelphia, Pennsylvania Abstract This paper reviews 12 years of progress in applying optimization to the helicopter rotor design problem. This involves multiple disciplines, multiple objective functions, a large number of design variables and irregular design space. The initial step was to develop a single interdisciplinary analysis to evaluate the objective function. By understanding the problem, approaching it incrementally and learning how to adapt optimization techniques, dramatic progress has been made. Numerous optimization techniques have been tried, including: gradient-based methods (with finite difference and automatic differentiation), biological models, surface approximations and direct search. Each of these methods had to be properly adapted to the problem. Initial progress was made using a gradient-based method along with numerous prodding techniques to avoid local minima. Though successful, it required extensive labor hours. In search of more efficient methods, a scaled down representative problem was defined and multiple derivative free optimization (DFO) methods were investigated. All this has led to a hybrid approach that we are currently using in rotor design. Introduction 1 elicopter rotor design is a complex interdiscipli- process. Optimization was applied to this Hnary process with two major objectives in mind. First, to define a rotor with improved characteristics (lower loads, longer life, reduced weight, lower vibration, better aerodynamic performance) and second, to automate the rotor design process to reduce labor hours and design cycle time. Achieving these objectives requires many steps. As a first step, we chose to focus only on the lower vibration aspect, which is an ambitious starting point with large potential benefits. The plan was to incrementally build upon this base, adding more complexity at each step. Historically, a major problem in the rotorcraft industry has been vibration. The primary cause of this vibration is the hub loads coming from the rotor. The transformation of the rotating vibratory hub loads into the fixed system causes a selective cancellation and addition. This results in fixed system vibratory hub loads at frequencies that are integer multiples of the number of rotor blades times the rotor speed. This frequency is represented as NP, where N is the number of blades and P represents the frequency of rotation. The fixed system vibratory vertical (Fz), longitudinal (Fx), and lateral (Fy) forces along with the roll (Mx) and * Manager, Dynamics and Loads Senior Technical Specialist 1 Copyright 1998 The American Institute of Aeronautics and Astronautics Inc. All rights reserved. pitch (My) moments at the rotor hub excite the fuselage causing vibration. The resulting vibration annoys and fatigues crew and passengers, cracks structure, and fails components and electronics. Collectively, this contributes significantly to operating cost and safety. To keep vibration reasonable, though still at undesirable levels, devices are added to most helicopters. These include absorbers in the fixed and rotating system, isolation and active force generators together with fuselage structural tuning. All these devices add cost, complexity and weight. As a result, substantial research has been performed to reduce the inherent vibratory hub loads that cause aircraft vibration. The Ref. 1 research and unpublished wind tunnel testing showed substantial potential for reducing rotor vibratory hub loads by more than 50 percent when the blade tip was swept. However, the number of design variables, the interaction between the five different hub load components (vertical force, inplane forces and inplane moments), the real design constraints, and four years of trying convinced us that a trial-and-error, follow-the-logic approach would not work. Only computer-automated optimization could efficiently juggle all the variables and find its way through the conflicting requirements. The objectives of this paper are to describe the steps taken thus far in the development of our rotor design tool. We will describe the various optimization techniques tried to date and show how they are being used to design low vibration rotors (LVR). We will present our experiences, including lessons learned, as applied to 1 American Institute of Aeronautics and Astronautics

91 AIAA using the various optimization techniques. The results from wind tunnel model rotor tests are included to show the benefits achieved from the design process. We will also briefly describe recent activities undertaken with various researchers applying derivative free optimization (DFO) techniques to this problem. Finally, we describe some of our future plans. The Rotor Problem The helicopter rotor represents the classic aeroelastic problem. Figure 1 plots angle of attack versus Mach number for different blade stations. Each loop in the figure represents the travel of one blade station through one rotor rotation. The blade encounters transonic flow, stall, reverse flow (the angle of attack exceeds 180 degrees) and unsteady effects, including dynamic stall (since the blade performs multiple revolutions each second). As the blade rotates, the large changes in dynamic pressure and angle of attack result in large variations in lift. This, in turn, results in trailed and shed vortices leaving the blade as shown in Figure 2. Blades that follow run into this complex wake, referred to as non-uniform downwash, resulting in further lift variations. In addition, since the rotor blade is long and slender, there are substantial elastic deformations, including nonlinear structural dynamics such as radial shortening, Coriolis forces and bending-torsion coupling. Therefore the airloads are functions of the aircraft flight condition, the non-uniform downwash and the elastic deflections of the blade. Clearly, there is no hope of predicting rotor behavior with a loosely coupled analysis. Figure 3 shows the close coupling required to perform a complete rotor analysis. Historically, the aerodynamics, flying qualities, dynamics and acoustics departments develop and maintain Local Mach Number % Span 50% Span Blade Root Blade Tip Stall Figure 1. The challenge. Instantaneous Angle of Attack (deg) separate simulation codes for performing their tasks. The aerodynamics department is responsible for rotor performance and aero-acoustics, and developing new technology for airfoils, non-uniform downwash prediction and blade/vortex interaction. The dynamics department is responsible for rotor vibratory loads and stability, and developing aeroelastic models (blade coupled dynamic response and unsteady aerodynamics). The flying qualities department is responsible for the flight control laws and developing full aircraft trim theory. We all are trying to solve the same problem, but with different emphasis. Each simulation has to contain most of the problem elements, but not necessarily all or the best. For aeroacoustic predictions, the blades were assumed rigid; for performance and trim predictions, approximate blade deflections were used; and for vibratory loads, simplified (quick running) downwash models were used. In the late 1980 s the development of code configuration management tools (like DSEE 2 and later ClearCase 3 ), increased computer power, and relentless cuts in development budgets forced a consolidation. The aerodynamics, acoustics and dynamics departments then combined their best technology into a single interdisciplinary rotor code 4. Code configuration management tools allowed each department to continue to develop and enhance their traditional areas of expertise and be able to utilize a simulation code that had all the best technology and was superior to any of the previous simulations. Faster computers and the proliferation of affordable workstations lessened the need to simplify portions of the theory to reduce run time and turnaround. Program options allow less rigorous, quicker running versions to be used when needed. Figure 2. Trailed and shed vortices. 2 American Institute of Aeronautics and Astronautics

92 AIAA CALCULATE WAKE FIXED ROTOR RESPONSE FIXED CONTROLS INDUCED WAKE - AIRLOADS - FLEXBEAM DEFORMATION - DETERMINE RESPONSE FIXED AIRLOADS FIXED CONTROLS NON-LINEAR FLEXBEAM - CONTROL MOTION - END LOADS CHECK AIRLOAD CONVERGENCE TO PROCEED - DOWNWASH - AIRLOADS LOOP TRIM CHECK AIRLOADS LOOP - CONTROLS - DETERMINE CONTROLS FIXED ROTOR RESPONSE FIXED DOWNWASH Though flying qualities was not part of the initial simulation consolidation, provisions were made to make the interface with the trim model more robust. By satisfying rotor trim forces, instead of postulating control inputs, we are assured that the fuselage force and moment balance is maintained. We plan to link the combined interdisciplinary rotor analysis with the trim analysis in the future. Therefore, our present function evaluator is a single, tightly coupled, interdisciplinary rotor analysis. An iteration method is used to satisfy compatibility among all the disciplines. The Optimization Problem Our first step was to prove that the optimization process worked by defining a rotor with significantly reduced vibratory hub loads, building a Mach scaled model and performing a validation test. Once validated, the second step was to obtain a better design with acceptable risk and cost. Since there are so many conflicting intangible requirements like manufacturing, total ownership cost, tolerance to variability, etc., we needed to define the design space so that the design team could find an acceptable compromise. Performing multiple point optimizations to define the local design space as a function of key variables would do this. For our first attempt, we linked the rotor analysis, (to define the objective function), with a gradient-based optimization code, NPSOL 5. This code is what we will refer to as the gradient optimizer throughout this paper. The rotor blade is typically modeled with 25 structural elements. There are six design variables for each element, which are listed in Table 1. Hence, there is a total of 151 available design variables (there is one extra ROTOR RESPONSE MAIN ITERATION LOOP AIRLOADS Figure 3. Rotor analysis. ROTOR RESPONSE CHECK RESPONSE CONVERGENCE END - HUB LOADS - ROTOR RESPONSE - NON-LINEAR LOADS - HUB MOTION LINEAR FUSELAGE RESPONSE NON-LINEAR BLADE COUPLING design variable for the control system stiffness). The objective function (OF) is made up of a weighted linear sum of the five hub load components as follows: OF = W F + W F + W F + W M + W M where (1) 1 x 2 y 3 z 4 x 5 y M F = f (2) N, D n, D, C N, D = m (3) n, D, C W i is a coefficient for weighting the hub load components, so as to account for fuselage response due to each hub load. F and M are the fixed system hub forces and moments at N times rotor speed (where N is the number of blades), in D directions (x, y, z). Equations 2 and 3 represent the transformation of the rotating system blade root forces and moments, (f and m), in direction D, at frequency n, and flight condition C, into the fixed system forces and moments (F and M). Due to this transformation of rotating hub load components into the fixed system, there can be a shift in the frequency of one times the rotor speed. Therefore, the rotating frequency n may be at a frequency of (N-1), N, or (N+1) times the rotor speed. This objective function formulation results in very complex design space. Since each component of the objective function has a different trend, due to a design variable change, the design space will have many peaks and valleys. Therefore, finding the lowest valley is a demanding challenge. 3 American Institute of Aeronautics and Astronautics

93 AIAA Symbol m cg EI β EI ζ GJ Λ K z Table 1. Rotor design variables. Description section mass section chordwise center of gravity section flap bending stiffness section lag bending stiffness section torsion stiffness built in sweep angle between sections control system stiffness (only one value) Initial Optimization Using Gradients One major complication with the optimization process is the large demand for computer resources. Since finite differences are used to determine derivatives and there are 151 design variables, an optimization would require thousands of function evaluations. With run times of 20 to 30 minutes for each evaluation (on a HP 715/100), and questions of numerical noise, we decided to use a simple, less costly approach. The reason the function evaluation is so computer intensive is that the airloads are a function of both the aircraft flight condition and the rotor blade elastic deflections. The elastic deflection with the largest influence on the airloads is the blade elastic twist. It was hoped that by fixing (not varying) the design variables that influence elastic twist, such as the torsional stiffness, chordwise center of gravity, aerodynamic center and chord sweep, the elastic effect on the airloads would be minimal and could be ignored. This would mean that the airloads could be assumed to be only a function of the flight condition. Therefore, the airloads could be prescribed and the rotor blade structural properties optimized to minimize the resulting vibratory hub loads. Bending-torsion coupling would still be accounted for, but changes should be minimal, so that airload changes resulting from this coupling would be small and not prevent us from finding a good dynamic response optimum. A new, simpler function evaluator was made from the rotor blade dynamic response portion of the rotor analysis. The airloads were read into the simpler function box as a prescribed forcing function. The vibratory hub loads were calculated from the new function evaluator. Since the airloads were held fixed at the initial distribution in the optimization, the blade geometry aerodynamic configuration was also fixed. Eliminating the torsion degree of freedom from consideration reduced the number of design variables to the section mass, flap stiffness and lag stiffness at 25 blade stations. It turned out that the chord stiffness did not vary with the optimization process for reasons we do not understand. So effectively, there were only 50 design variables. This simplification allowed the function evaluator to run in seconds. However, the optimizer still gave lackluster results. It would run through a few optimization iterations and proclaim victory, but usually the reduction in hub loads were less than twenty percent. It was clear that the gradient-based algorithm was getting stuck in local minima. The problem is that a gradient optimizer cannot find a solution far from the initial design if the design space resembles the Rocky Mountains. There was no mechanism for a gradient-based optimizer, which follows a steepest decent, to search on the other side of a response peak, (which is perceived as first going up hill). To resolve this problem, numerous techniques were developed to encourage the optimizer to avoid local minima. These techniques are described in more detail in the following subsections. Different Starting Frequencies Blade properties were changed to get different starting frequencies. By making random variations to the physical properties, new starting designs were found for the optimizer. These new designs were generated in hope of forcing the optimizer to follow a different search path. This path would either lead to the same local minimum, a different local minimum, or to the global minimum. Large Range of Design Variable Values By changing the range between the upper and lower bounds of the design variables, it is possible to encourage large changes in the design value. These large changes would often cause the optimizer to explore a new design space, which resulted in finding a more global minimum. Once a good solution was found, we would then squeeze the range down until we achieved a solution, which was the best compromise between hub load level and ease of manufacturing the rotor blade. Apply Constraints Incrementally This technique goes hand-in-hand with the large range of the design variables described above. By allowing the upper limit of a constraint, such as the total rotor weight, to be large at the start, it is possible to get into another region of the design space. Just as described above, once a good solution is found, the constraint would be squeezed to slowly force the solution into the desired design space. 4 American Institute of Aeronautics and Astronautics

94 AIAA Adjust Objective Function Weighting Values Another technique that can be used to foster new solutions is varying the relationship of the weighting coefficients in equation (1). For example, if one of the hub load components is resistant to change, all of the other coefficients can be set to zero and the problem rerun. Once the optimizer has been forced into a new region, the original weighting coefficients can be used again to continue exploring the design space. Another approach is to increase or decrease the importance of a given hub load over that of the others to encourage further improvement. Recalculate Constant Airloads As described above, the airloads are a function of both the aircraft flight condition and the blade elastic deflections. The initial optimization process did not allow the design variables that influence elastic twist to vary and the airloads were held constant. Our practice was to verify any design solution obtained from the optimizer in our full interdisciplinary rotor analysis. While the assumption that the effect of bending-torsion coupling would not prevent us from finding a good dynamic response was true, there were times where a still better solution was found by simply updating the airloads and continuing the optimization process. Competitions This technique uses the different solutions, which have been generated by the above prodding techniques, to compete against each other. Individuals were given different starting designs and tried to improve the optimum. Weekly meetings would share lessons learned, eliminate the worst and continue refining the best. The comparison included items such as the objective function value, how well the design satisfied the constraints, and how realistic the blade section properties were. Identify Related Designs One observation is that as the number of potential designs increases, there will be promising designs with similar characteristics. By grouping similar designs together, not all of the competitions will need to be performed. This is important when time and computer resources are limited, since it is easier to eliminate a design then to perform the competitions and determine which ones to keep. Optimizer Restart When the optimizer terminates, the history of the objective function is reviewed. Usually this history shows an initial rapid reduction followed by a gradual leveling out. However, some times the objective function would still be declining when the optimizer would stop. There would not be the typical leveling out. When this occurred, the optimizer would be restarted and usually continued reducing the objective function. We suspect that the premature termination of the optimization is due to contamination of the Jacobian. Since the Jacobian is built from a finite difference process and uses current and historical data, noise in the numerical gradients could cause the contamination. Restarting allowed a new Jacobian to be generated and the determination of clear direction for the process to proceed. Multiple Flight Conditions We wanted a blade design that was robust over the whole aircraft flight regime, not just a single design condition. This is important since the rotor must operate over a wide range of airspeeds, altitudes, ambient temperatures and gross weights. By performing complete airspeed sweeps at multiple gross weights, we were able to select up to five critical flight conditions to include in the objective function. This virtually insured that the optimum would lower vibration over the whole flight regime. Typical selections included cruse at two gross weights, transition, and the corner of the flight envelope. Initial Wind Tunnel Model The procedure described above was developed and refined by applying it to the design of a Mach-scaled, four-bladed, fully-articulated, ten-foot diameter wind tunnel rotor which was fabricated and tested in our V/STOL wind tunnel 6. The wind tunnel test allowed the gathering of steady-state vibratory rotor loads necessary to validate the low vibration rotor concept. The goal was to develop a rotor, which would substantially reduce the fixed system 4P vertical hub load and the fixed system 4P roll and pitch hub moments. Accomplishing this goal required the design and fabrication of two rotor blade sets a reference rotor and a low vibration rotor. Both rotor blade sets would then be tested backto-back in the wind tunnel. Both rotor sets had identical blade radius, chord, twist, and airfoil shape distributions, as well as the same blade and hub attachment points. The only parameters that differed were the spanwise and chordwise distribution of the rotor mass and elastic properties. The reference rotor is a scaled version of the Boeing Model 360 experimental rotor, which flew to over 210 knots in level flight on an all-composite tandem rotor demonstrator aircraft. This rotor was designed by using the traditional approach of adjusting the rotor properties to provide adequate frequency separation from the harmonic aerodynamic forcing. The low vibration rotor 5 American Institute of Aeronautics and Astronautics

95 AIAA was designed using the optimization techniques as described above. A comparison of the measured normalized 4P hub loads, obtained from dynamically calibrated balances, for the reference rotor and the low vibration rotor (LVR) is shown in Figures 4 and 5 for a level flight condition corresponding to a nondimensional rotor lift, C T '/σ of 0.07 and a nondimensional rotor propulsive force, X, of (The prime symbol is used throughout this paper to indicate a deviation from the classical definition of the marked quantities). The forces have been normalized by the nominal rotor thrust and the moments have been normalized by twice the nominal rotor thrust times the dimensional flap hinge offset. The hub loads are plotted versus rotor advanced ratio, µ, (which is defined as the free stream velocity divided by the rotor tip speed). Figure 4 shows that a 67 percent reduction was achieved in the 4P vertical hub load in the low airspeed transition region (µ' 0.10 or about 39 knots), and a 56 percent reduction was achieved in the high airspeed region (µ' 0.43 or about 183 knots) for a 3.4 percent increase in total rotor flapping weight. Figure 5 shows that a 45 percent reduction was achieved in the measured 4P overturning hub moment in the low airspeed transition region (µ' 0.10), and a 77 percent reduction was achieved in the high airspeed region (µ' 0.43). The overturning hub moment refers to the magnitude of the vector sum of the roll and pitch hub moments. The initial wind tunnel model design was a success. It had meet our goal of proving that the optimization process worked in defining a rotor with significantly reduced vibratory hub loads. It also showed us how labor intensive the optimization process could be. While the gradient-based approach had been successful, it left us looking for a better way of finding the global minimum. We were just getting started on the literature search when a new opportunity came along. We were asked to apply our optimization techniques to defining an advanced rotor for the CH-47 Chinook. A Real Rotor The Mach scaled wind tunnel test results were so encouraging that funding was found to apply the optimization to an advanced CH-47 Chinook rotor. The development of a full-scale low vibration rotor was undertaken to understand and evaluate the rotor design/optimization process needed to satisfy all the full scale requirements. This included considerations like 4P Vertical Hub Load (ND) 4P Overturning Moment (ND) Reference Rotor Advance Ratio, µ' LVR Figure 4. Measured 4P vertical hub load Reference Rotor Advance Ratio, µ' LVR Figure 5. Measured 4P overturning hub moment. blade tie down fittings, track and balance hardware, fatigue life, tooling and manufacturing requirements. In addition, the optimization problem was reformulated to include additional hub loads and constraints. Another wind tunnel test 7 using the previously defined LVR showed that the 8P hub loads could be measured and predicted well enough to warrant design optimization to reduce these loads as well. The improved optimization method was applied to the design of the advanced Chinook rotor 8. It involved working with the designers to define realistic minimum and maximum limits for each design variable. Iterating with manufacturing was required to insure that the final design was buildable. In addition, the same prodding 6 American Institute of Aeronautics and Astronautics

96 AIAA techniques, described above, were used with the same gradient-based optimizer. Since rotor design is a high cycle fatigue problem, the stress group periodically checked the stress/strain levels. To insure that the rotor had an infinite life, a conservative strain allowable was adapted. This strain was not to be exceeded during normal level flight. Whenever the strain was too high, the minimum blade section stiffness and weight was adjusted to lower the strain. As the design/optimization progressed, this iteration between the optimum design, blade loads, stress and adjusted minimum stiffness and weight proved fruitless. Each time the optimizer defined a significant vibration improvement, the stress proved too high and the design constraints were adjusted. This process was increasing both our design time and cost. We either had to proceed with a less than optimum design or modify the optimization process. Therefore, the optimization process was modified to include a maximum strain constraint. In addition, a relationship between the blade section stiffness and weight was also provided as a nonlinear constraint. This simulated the design process of strengthening the blade when the stress was too large. When additional strength was needed, the optimizer automatically added the correct weight. This made a real solution possible. As shown below, we achieved both lower vibrations, at both 4P and 8P, with a reduced blade weight. Another issue was the determination of local design space. This would allow the design team to perform a tradeoff between total rotor weight, vibration and strain. Point optimizations were performed where the total rotor weight and strain constraints were incrementally decreased while satisfying all other constraints. By plotting the optimization results as a function of vibration versus constrained blade weight and allowable strain, the tradeoff between weight, strain, and vibration could be more clearly understood. Using this data we could choose the best compromise. Figure 6 shows the 4P blade vibration index versus nondimensional blade weight for the design strain level and for a 30 percent larger strain level. The 4P vibration index is a normalized measure of the calculated 4P vertical force, roll moment and pitch moment, times the pilot vertical vibration response to hub loads as measured from an aircraft shake test. Hub loads from both the forward and aft rotors at 20 and 150 knots were used. Two baseline rotors are shown. The reference model rotor (solid square) has a weighted vibration index based on calculated hub loads and is normalized to unity. The full scale Model 360 nondimensional Weighted 4P Vibration Index New LVR Wind Tunnel Baseline Full Scale Model 360 Design Strain Limit 30% Larger Strain Limit Original LVR Weight Blade Weight Thrust (@C /σ =.07) x Scale Factor T Figure 6. Weighted vibration index versus blade weight trend for two strain levels. flapping weight is included for reference to show how close the scaled weight of the model and full scale rotors are. The nondimensional weight of the original LVR model rotor (previously discussed) is also provided for reference. This rotor is 3.4 percent heavier than the reference model rotor. Using this design space definition, a blade weight at the knee of the curve for the lower strain was selected. This represents a flapping weight that is 7.5 percent lighter than the reference rotor and 11.9 percent lighter than the original LVR. Observe that if desired, a new material with a higher strain allowable could be identified and qualified, or a finite blade fatigue life defined. This would result in further reduced rotor weight and/or lower vibration, but with increased cost and development risk. The final rotor properties were Mach scaled and a wind tunnel test was performed in the same manner as the previous tests. The improved LVR used a hub with a coincident elastomeric bearing. Due to model elastomer bearing size limits, it was not possible to get the model flap hinge at the same offset as the previously described reference rotor. Therefore, to compare with the reference rotor hub loads the improved LVR measured hub moments are scaled to account for this difference. Figures 7 and 8 show the measured normalized 4P hub loads, obtained from dynamically calibrated balances, for the reference rotor, the LVR, and the improved LVR at the same flight condition. Compared to the reference, the improved LVR shows that the 4P vertical hub load is 74 percent lower in transition and 69 percent lower in cruise for a 7.5 percent decrease in total rotor flapping weight. The 4P overturning hub moment is 88 percent lower in transition and 55 percent 7.5% 2.7% 3.4% 7 American Institute of Aeronautics and Astronautics

97 AIAA P Vertical Hub Load (ND) Reference Rotor Advance Ratio, µ' LVR ILVR Figure 7. Measured 4P hub load for the reference rotor, LVR and ILVR. 4P Overturning Moment (ND) Reference Rotor Advance Ratio, µ' ILVR LVR Figure 8. Measured 4P overturning hub moment for the reference rotor, LVR and ILVR. lower in cruise. The 8P hub loads (shown in Ref. 8) had a 1 to 68 percent reduction in vertical hub load and a 53 to 79 percent reduction in overturning hub moment Solve the Whole Problem We achieved our objective of proving the optimization process works with a simplified function evaluator. A rotor that significantly reduced vibratory hub loads was defined and validated in a wind tunnel test. It was now time to improve the process. This involved several enhancements. First, the full interdisciplinary rotor analysis code was used as the function box, allowing us to investigate the full aeroelastic optimization problem. Now the additional design variables that cause elastic blade twist, which leads to changes in the airloads, could be exploited by using optimization. This increased the number of design variables from 50 to 151. The second enhancement reduced optimization turnaround time. A typical function evaluation with a prescribed set of airloads (not changing due to blade response) was a few seconds. When the full interdisciplinary rotor analysis was used (with compatibility between the blade response, airloads and rotor wake), the time increased to about 20 or 30 minutes. Hence, nearly all of our processing time would be spent evaluating the finite differences. To perform a single optimization using the full theory would require months of run time. Two developments that helped overcome this computer time problem were the continuing workstation speed increase and the use of parallel processing to evaluate each gradient independently 9. The third enhancement focused on non-gradient based optimization methods. As pointed out above, several prodding techniques were needed to encourage a gradient-based optimization method find a global minimum. This was very time consuming and labor intensive. It was hoped that non-gradient methods would prevent getting stuck in local minima by providing a diverse set of potential optimum solutions. These potential solutions would be found by exploring the whole design space, instead of being limited to the local space of the initial design, like gradient methods. The best non-gradient designs would then be refined using gradient methods. This approach is equivalent to flyingover the Rocky Mountains to identify the most promising valleys, then sending in explorers to search for the bottom of each valley. To help us explore the many nongradient-based optimization methods, a simple design problem was created. This problem was then given to various researchers so that they could apply their nongradientbased methods to the same rotor problem. They were also asked to use our enhanced function box evaluator. The problem represents a three-bladed helicopter rotor with advanced planform geometry including blade tip sweep. Early optimization efforts had shown that it was more difficult to reduce vibration for a three-bladed rotor than for a four-bladed rotor. The rotor was discretized into a model consisting of 13 bays of which the 10 outboard bays had airloads applied. Normally 25 bays are used. This problem had 56 design variables which represented the level of section mass, stiffness (in flap, chord, and torsion), and chordwise center of gravity position at different blade stations along the span of the blade. Further CPU run time reductions were obtained by prescribing the rotor induced non-uniform down- 8 American Institute of Aeronautics and Astronautics

98 AIAA wash and using only two flight conditions in the function evaluation. This simplified model was chosen since it captured the main effects of the vibration problem and still had a rather short function evaluation CPU time of a few minutes per airspeed. The objective function to be minimized was the linear combination of the weighted fixed system 3P and 6P three hub forces (Fx, Fy, Fz) and two hub moments (Mx, My). The 3P loads were weighted as being twice as important as the 6P loads and the two airspeeds were weighted equally. The only constraint limited the total rotor weight to be less than or equal to times the nominal weight. The methods explored were: 1) design of experiments (DOE) with response surfaces by Boeing, Seattle 10,11 2) evolutionary programming (EP) by Boeing, Philadelphia 9 3) parallel direct search (PDS) by Boeing Seattle, IBM, and Rice University 11,12 4) analytical derivatives using ADIFOR by NASA, Langley 13 5) derivative free optimization (DFO) by IBM 11,14 6) genetic optimization (GA) with a neural net by Rensselaer Polytechnic Institute (RPI) Table 2 compares the results obtained from each of the methods along with the results from our gradientbased method using NPSOL. Please note that the results presented here were obtained prior to the end of 1997 and that more recent results may be shown at this conference by the individual researchers. Also, we will not provide detail of how each researcher obtained their results. That too is left for the papers they will present at this conference. Note that the Table 2 results are not global minimum and need to be refined with gradient methods (except for NPSOL and ADIFOR, which are gradient methods). Even though they are not minima, three of the derivative free methods; EP, PDS, and GA have objective function values lower than the best gradient result. Table 2. Comparison of the resulting designs. Design Nondimensional Total Weight Objective Function Value Baseline NPSOL DOE EP PDS ADIFOR GA Our experience, to date, has been that a nongradientbased method by itself is not the fastest way to reach a global minim. Because the function to be evaluated is computation intensive and many function evaluations are needed, a combination of methods is required. By automating a combined process, labor costs can be greatly reduced. For now, we have selected a hybrid approach that uses our EP method and our gradientbased method. We have chosen these two for the following reasons. First, we have both codes in house and have some, albeit limited, experience in using them. Second, the other methods are still under investigation. It is possible that multiple methods may be needed. Third, Table 2 shows that the EP method gave the best results. The advantage of using a hybrid method is that the nongradient-based method provides a diverse set of solutions, which explore the whole design space without having to use prodding techniques. These diverse solutions are also automatically generated by the process itself and do not require labor intensive human intervention. Recent Design Activity Recently (last quarter of 1997), we were asked to define a replacement rotor for an existing helicopter. The new rotor would have a 12 percent larger blade chord and a 67 percent increase in blade twist but the rotor vibration could not be any higher than the existing rotor vibration. Historically, when a rotor blade has its chord increased, the section airloads increase, thereby increasing the rotor loads. In addition, increasing the blade twist also causes increased hub loads. A conventional preliminary design had been performed prior to our involvement, and the predicted vibration was substantially higher than the existing aircraft. Using the hybrid method described above along with the complete interdisciplinary rotor analysis, the evolutionary programming method defined a promising rotor. It satisfied the vibration requirement, but was heavy and did not satisfy all the constraints. This was expected, since the initial goal was to find potential candidates, not the final design. The gradient-based method was utilized to improve this design. The weight was systematically reduced and the strain constraint applied. A dramatic improvement was made while reducing the total rotor weight by 7 percent. Figures 9 to 11 show preliminary results of the normalized hub loads for a LVR compared to the existing production rotor. 9 American Institute of Aeronautics and Astronautics

99 AIAA NP Vertical Hub Load (ND) Production Rotor LVR Advance Ratio, µ' Figure 9. NP vertical hub load reduction. NP Inplane Hub Load (ND) 0.1 Production Rotor LVR Advance Ratio, µ' Figure 10. NP inplane hub load reduction. NP Overturning Moment (ND) Production Rotor LVR Advance Ratio, µ' Figure 11. NP overturning hub moment reduction. Conclusions The rotor design problem involves a large number of design variables, interdisciplinary considerations and complex design space. The function evaluator is a single, tightly coupled, interdisciplinary, computation intensive code. Steady progress has been made towards developing an effective optimization-based rotor design process. However, the process requires excessive computer resources, long calendar time and is too labor intensive. To date derivative free optimization (DFO) has shown the greatest promise in improving the rotor design process. By using these methods to explore the whole deign space, we are able to get many varied starting designs for refinement with our gradient-based method, and save substantial labor hours previously spent avoiding local minima. This hybrid approach has increased our confidence that a global optimum can be reached. This approach also lends itself to parallelization and we have been able to make excellent use of idle workstations. Future Plans Our major objectives are to define a rotor with improved characteristics (lower loads, longer life, reduced weight, lower vibration, better aerodynamic performance) and to automate the rotor design process to reduce labor hours and design cycle time. Some of the improvements described below are only notional. As we get closer to implementation, our vision will become more focused, allowing better definition of what we want to achieve. First, we want to add rotor aerodynamic performance to the objective function. To accomplish this, more design variables and constraints must be added to the problem formulation. Next, we want to continue investigating DFO methods. Which method is most robust (gives the best results in the least calendar time, uses less computer resources and fewest labor hours)? Are approximate methods most efficient, or are errors too large to give meaningful results? Will only using main effects allow substantial reductions in the number of design variables or will variable sensitivity be impossible to evaluate over the whole design space? How should the optimization control parameters be set to perform the most efficient searches? These and many other questions need to be answered. Another improvement is the development of a method for classifying the many promising designs that result from a DFO optimization. By identifying similar designs, only the best, unique (unrelated) need to be 10 American Institute of Aeronautics and Astronautics

100 AIAA refined with the gradient method, eliminating duplicate effort. Data mining is another potential source of efficiency. By adding all the previously evaluated designs in a nondimensional database, a resource can be developed for future DFO activity. Future rotor design requirements can have different emphasis on performance, loads or vibration, with different constraints. This will require a new design optimization problem. The database can be searched to rapidly define favorable designs to start the DFO process. Another application is to use the database for building response surface approximations. As more designs are investigated, the database will grow and so will the efficiencies. The whole optimization/design process needs further automation. This may use natural language to set up the optimization, run hands off until the requested task is complete, automatically display local design space for selected parameters so intelligent tradeoffs can be made, provide status data to monitor progress, and use parametric design variable ranges and constraints for initial optimization. We also want to improve the parallel nature of our codes. Currently we are doing most of our computation on a network of UNIX workstations. We need to improve the robustness of our controller so that if one node crashes (as they inevitably do), the process can continue with the remaining nodes. In addition, we want the controller to automatically search out idle computers so we can take advantage of this resource, on a noninterference basis. Automated optimization and design are critical for the future of manufacturing in developed nations. Market forces are requiring us to design, build, and get to market faster. Reality is pushing us to reduce design cost by doing more with less. It can be done! Acknowledgments The authors would like to express their gratitude to Joel Hirsh for his helpful insights and knowledge of optimization techniques. His implementation of the parallel computing has been greatly valued. We would also like to thank the many researchers, too numerous to mention by name, who have worked with us in our investigation of derivative free optimization methods. References 1. Tarzanin, F. J. and Young, D. K., Blade Tip Sweep Effect on Hub Vibratory Loads, NASA CR , Sep Domain Software Engineering Environment (DSEE) Command Reference, Atria Software, Inc., Natick, Mass., ClearCase User s Manuel, Atria Software, Inc., Natick, Mass., Shultz, L. A., Panda, B., Tarzanin, F. J., Derham, R. C., Oh, B. K., and Dadone, L., Interdisciplinary Analysis For Advanced Rotors Approach, Capabilities And Status, Presented at the AHS Aeromechanics Specialists Conference, San Francisco, CA, Jan Healy, M. J., User s Guide for the SOL/NPSOL Nonlinear Programming Library Boeing Version, Engineering Technology Applications Library Report ETA-LR-41, Boeing Computer Services, Jun Young, D. K. and Tarzanin, F. J., Structural Optimization And Mach Scale Test Validation of a Low Vibration Rotor, Journal of American Helicopter Society, Vol. 38,(3), Jul Staley, J. A., Mathew, M. B., and Tarzanin, F. J., Wind Tunnel Modeling of High Order Rotor Vibration, Presented at the AHS 49 th Annual Forum, St. Louis, Missouri, May Tarzanin, F. J., An Improved Low Vibration Rotor, Presented at the AHS Aeromechanics Specialists Conference, Bridgeport, CT, Oct Hirsh, J. E. and Young, D. K., Evolutionary Programming Strategies with Self-Adaptation Applied to the Design of Rotorcraft using Parallel Processing, 7th Annual Conference on Evolutionary Programming, San Diego, CA, March 25-27, 1998, Springer-Verlag. 10. Booker, A. J., DACE - Design and Analysis of Computer Experiments, Presented at the 7 th AIAA/ USAF/NASA /ISSOMO Multidisciplinary Analysis and Optimization Symposium, St. Louis, Missouri, Sep 2-3, Booker, A. J., Dennis Jr., J. E., Frank, P. D., Serafini, D. B., Torczon, V., and Trosset, M. W., A Rigorous Framework for Optimization of Expensive Functions by Surrogates, Technical Report SSGTECH , Boeing Shared Services Group, Applied Research and Technology, March Dennis Jr., J. E. and Serafini, D. B., Model Management, Presented at the 7 th AIAA/USAF/NASA/ ISSOMO Multidisciplinary Analysis and Optimization Symposium, St. Louis, Missouri, Sep 2-3, Walsh, J. L., Young, K. C., Tarzanin, F. J., Hirsh, J. E., and Young, D. K., Optimization Issues with Complex Rotorcraft Comprehensive Analysis, Presented at the 7 th AIAA/USAF/NASA/ISSOMO Multidisciplinary Analysis and Optimization Symposium, St. Louis, Missouri, Sep 2-3, Conn, A. and Mints, K., Derivative Free Optimization, Presented at the 7 th AIAA/USAF/NASA/ ISSOMO Multidisciplinary Analysis and Optimization Symposium, St. Louis, Missouri, Sep 2-3, American Institute of Aeronautics and Astronautics

101 THE CHALLENGE AND PROMISE OF BLENDED-WING-BODY OPTIMIZATION Sean Wakayama* Ilan Kroo The Boeing Company Stanford University Long Beach, CA Stanford, CA AIAA Abstract Multidisciplinary design optimization (MDO) is an important part of the Blended-Wing-Body (BWB) aircraft design process. It is a promising technology, but faces many challenges in routine application to aircraft advanced design. This paper describes current approaches, recent results, and future challenges for MDO as reflected in our experience with BWB design over the past four years. Current efforts have employed the Wing Multidisciplinary Optimization Design (WingMOD) code, targeting broad optimizations with large sets of design variables and constraints. These efforts have shown substantial payoffs stemming from the natural ability of MDO to handle the geometric complexity and the integrated design philosophy of the BWB. Challenges to MDO have been identified in the breadth and depth of the analysis desired to capture aerodynamic, stability, and control issues for this configuration. Future efforts include incorporating higher-fidelity codes while maintaining the breadth of scope, possibly with methods such as response surfaces and collaborative optimization. Introduction The Blended-Wing-Body (BWB) is a revolutionary concept for commercial aircraft 1-2. It requires a design approach that departs from the conventional decomposition of the airplane into distinct pieces and instead integrates wing, fuselage, engines, and tail to achieve a substantial improvement in performance. This provides an arena rich in opportunities for multidisicplinary design optimization (MDO). The high level of integration breaks the normal design process; instead of satisfying specific requirements with a distinct airframe part, an array of requirements must be satisfied with an integrated airframe. This changes the design philosophy and requires developing experience in the new way of thinking. MDO presents a solution * Senior Engineer/Scientist, Member AIAA Associate Professor, Member AIAA Copyright 1998 by Sean Wakayama. Published by the American Institute of Aeronautics and Astronautics, Inc. with permission. for these new design challenges. This paper describes some of the early application of MDO in the development of Boeing s BWB concept, focusing on the aerodynamic and structural optimization of the blended-wing planform and highlighting the opportunities for an expanded role of MDO in continuing design work. Current State: WingMOD MDO in the BWB program has been undertaken using several codes. Early conceptual and cabin layout optimization was carried out at Stanford University using both gradient-based and genetic algorithms; however, most of the current MDO work has been done with the Boeing Company s Wing Multidisciplinary Optimization Design (WingMOD) code. This code was originally developed for conventional wing and tail design, but has been adapted for use on the BWB. While this paper focuses on the use of WingMOD for BWB design, the basic conclusions regarding MDO in aircraft advanced design are more generally applicable. Basic WingMOD Analysis As described in References 3 and 4, WingMOD optimizes aircraft wings and horizontal tails subject to a wide array of practical constraints. It performs wing planform, thickness, and twist optimization, with design variables including overall span plus chord, sweep, thickness, and twist at several stations along the span of the wing. It also optimizes skin thicknesses, fuel distribution, spar locations, and control surface deflections. During optimization, WingMOD enforces constraints on range, trim, structural design, maximum lift, stability, control power, and balance. WingMOD handles structural design and maximum lift constraints at a higher fidelity level than the traditional conceptual design process. It also incorporates stability, control, and balance considerations directly in the aircraft optimization, where the traditional conceptual design process handles these constraints outside the sizing loop. By performing detailed optimization while attending wide-ranging constraints early in the design process, WingMOD identifies ways to trade and maximize interdisciplinary advantages, generating well-rounded configurations that are usually achieved at great cost with traditional design processes. 1 American Institute of Aeronautics and Astronautics

102 To provide this capability, WingMOD employs analyses that have higher fidelity than those for conceptual design, but are faster than those generally associated with preliminary design. The basic WingMOD method models an aircraft wing and tail with a simple vortex-lattice code and monocoque beam analysis, coupled to give static aeroelastic loads. The model is trimmed at several flight conditions to obtain load and induced drag data. Profile and compressibility drag are evaluated at stations across the span of the wing using empirical data with lift coefficients evaluated from the vortex lattice code. Structural weight is calculated from the maximum elastic loads encountered through a range of flight conditions, including maneuver, vertical gust, and lateral gust. The structure is sized based on bending strength and buckling stability considerations. Maximum lift is evaluated using a critical section method that declares the wing to be at its maximum useable lift when any section reaches its maximum lift coefficient, which is calculated from empirical data. For trim, section zerolift pitching moment is modified for trailing-edge deflections using empirical relations. WingMOD fits within an advanced design process as sketched in Figure 1. The process begins with configuration and cycles through the disciplines, ending with a sized baseline after performance analysis. From the baseline configuration, WingMOD generates an optimized design. The airplane is analyzed in more detail than in the process developing the baseline. This includes explicit modeling of control surface deflections for trim and explicit calculation of span loading for weight and drag assessment. The optimized design can be cycled through an optional computational fluid dynamics (CFD) analysis to verify the aerodynamic predictions in WingMOD and to generate a true outer mold line. For faster cycle time with lower fidelity, the CFD analysis could be skipped. Either way, the optimized design is passed from configuration through performance analysis to validate the weight and performance estimates. Genie Optimization Framework Optimization services for WingMOD are provided by the Genie framework. Genie, a GENeric Interface for Engineering, was originally developed at Stanford University as a shell for performing generic engineering optimization problems. The idea behind its development was to build a single interface that was powerful enough to be used for most engineering problems yet simple enough to be linked with any analysis code. The version of Genie used in WingMOD was modified at Boeing under NASA contracts to handle the requirements of several aircraft design optimization tasks. Efforts were made to develop features, which the original software lacked, that were needed on various optimization projects. Since most problems for Genie at Boeing could be cast as a single, integrated analysis, little was done to make it an integration tool with distributed computing capability; however, there are no obstacles to developing that capability. In its present form, Genie enables easy linkage between the analysis and optimizer, allows automated data calculation, provides data output in useful formats, provides information to facilitate scaling design variables and constraints, provides a selection of optimizers, allows flexible definition of optimization problems, and allows for the development of graphical user interfaces. Enabling easy integration of new analyses was important in getting Genie to be used on more than one project. Linking an analysis to Genie involves writing a trivial analysis interface and communicating design data through simple data interface commands. The analysis interface takes commands from the command interface or the optimizer and simply calls the analysis with no arguments. The data interface provides simple functions that the analysis uses to get and put information from and to the database. Since these are software subroutine calls, programming is required to link an analysis to Genie. This may seem less attractive than communicating through files; however, the programming is very simple and pays for itself in faster data transfer between analysis and framework. For an all new analysis, data interface calls can replace traditional input-output, saving programming time. Genie had automated optimization and calculation capabilities early in its development. Optimizations could be set up and run as background jobs on Unix platforms using a simple command language. To allow better visualization of the design space, the command language was expanded to allow calculations or optimizations at points in multiple dimensions to map objectives and constraints through the design space. While of limited use for wing design, this feature is very important for airplane sizing applications. A complementary development was the capability to output results in formats for special graphic programs that generate multi-dimensional sizing thumbprints. More important for wing design problems, output capabilities were added to generate data summaries that could be rapidly inserted in spreadsheet programs to create detailed graphical reports that illuminate dozens of characteristics across the wing span. 2 American Institute of Aeronautics and Astronautics

103 Aerodynamics Weights Propulsion Engine Deck Configuration Drawing Lift and Drag Polars, Buffet Boundaries, Baseline Weights, Thrust and Fuel Burn Tables Weights Iteration Performance Weights Configuration Economics Outer Mold Line Sized Weights, Engine Thrust, Fuel Burn, Block Time Sized Weights, Maximum Lift Data, Compressibility Drag Data CFD Baseline Design WingMOD Optimized Design Spanwise Coordinate (ft) Spanwise Coordinate (ft) true begin cruise fwd landing stall begin cruise end cruise ferry cruise Geometry Cabin Shape Drag Buffet Maximum Lift Structures Aeroelasticity Loads Weight Balance Trim Control Power Stability Spanwise Coordinate (ft) Spanwise Coordinate (ft) true begin cruise fwd landing stall begin cruise end cruise ferry cruise begin cruise end cruise ferry cruise begin cruise end cruise ferry cruise Spanwise Coordinate (ft) Spanwise Coordinate (ft) For detailed wing design problems, design variable and constraint scaling is extremely important for achieving timely, converged optimizations. Poor scaling can slow down or prevent convergence. The difficulty in selecting proper scaling comes from having a mix of very different variables and constraints that relate to each other in often non-intuitive ways. Very little is said about how to determine proper scales for all the variables in an optimization problem, and too often proper scaling is the result of a lot of experience by trial and error. There is a systematic approach to design Figure 1. WingMOD design process variable scaling 4, which Genie facilitates through the Non-Linear Optimizer (NLOpt). NLOpt is based on sequential-quadratic programming and was written for use with Genie. At the end of each optimization, NLOpt provides information that can be used to improve scaling for subsequent optimizations. This feature has been essential to enabling optimizations in over one hundred design variables. A motivation of using an optimization framework is the opportunity to make several optimizers available to the 3 American Institute of Aeronautics and Astronautics

104 analysis. Genie provides access to the efficient NPSOL optimizer as well as the robust NLOpt. The switching between optimizers occurs within Genie where the analysis programmer does not need to worry about it. The optimizer is connected to a goal function interface, which acts like an ordinary function with arguments to the optimizer; however, the goal function interface works with the command and data interfaces to transcribe the abstract optimizer variables into physical variables. This way, the command interface can set any database variable to be a design variable, objective, or constraint, providing great flexibility in setting up optimization problems. The complex programming to provide this capability is invested in the framework while connections between analysis and framework are kept simple. This offers a large payoff for the low cost of linking an analysis with the framework. Batch File Project File Plot File file data Command Interface Optimizer Database Genie Analysis Interface Goal Function Interface Data Interface Get(), Put() Graphical user interfaces (GUI s) provide a similar motivation for using optimization frameworks. While optimizations are run as Unix command line background jobs, Genie does have Macintosh and X- Window GUI s, which overlay the command interface. Investing in a GUI for a framework like Genie is attractive because that benefits every analysis connected to the framework. The challenge is then to create a generic GUI that can perform as well as applicationspecific GUI s for a range of analyses. The combination of optimization framework and wing analysis make the WingMOD code. As described to here, WingMOD had been applied to design of a composite wing for a stretched MD-90 5 and for studies on the MD-XX. Application to the BWB would require substantial changes. Challenges of the BWB command path data path Analysis Figure 2. Genie optimization framework. Radically different from conventional aircraft configurations, the BWB presents special design challenges. The integrated nature of the configuration is one challenge for which MDO offers a promising solution. Where the design of conventional aircraft can be divided between different disciplines, no discipline can work independently on the BWB. Where configuration can set the fuselage and aerodynamics can set the wing on a conventional aircraft, the two disciplines are forced to work together in defining a low-drag wing that adequately encloses the payload on the BWB. In that task, the large number of geometric degrees of freedom coupled with a number of geometric and aerodynamic considerations present a substantial MDO problem. Adding consideration of weight, balance, stability, and control issues turns this into an MDO challenge. Further increasing the challenge, the BWB has unique design features that require higher fidelity modeling than might be acceptable for conventional designs. To enclose the payload within the wing, the BWB has very thick airfoil sections over its body. Attaining low drag, transonically, with these airfoils is an aerodynamic challenge. In this region, the wing structure doubles as pressure vessel for the cabin, presenting flat panels that must support pressure loads over large spans dictated by the cabin arrangement. Designing and analyzing these panels and assessing a weight for them is a substantial challenge for structures and weights disciplines. To reduce drag, the design is tail-less, but this creates interesting challenges for stability and control: first, to balance the airplane and provide sufficient control power, and second, to ensure that control deflections for trim do not adversely affect the spanload and hence the drag. A final challenge lies in the aft-mounted engines and the difficulties with propulsion and airframe integration. Before undertaking a credible MDO effort on the BWB, some of these issues had to be addressed with new analysis methods. Aerodynamic Method Improvements In aerodynamics, access to rapid Navier Stokes solutions has provided tremendous insight and confidence in the aerodynamic understanding of the BWB. The turn-around time for these solutions has been adequate for wing design in the cruise condition, allowing substantial progress in the aerodynamic design of the BWB. Unfortunately, these methods are not directly used by WingMOD. To touch on disciplines such as loads, low-speed aerodynamics, stability and control, WingMOD evaluates 20 flight conditions in each analysis. To explore a broad range of design changes, optimizations include over 100 design variables. With 20 flight conditions per analysis, 100 analyses per gradient calculation, and a minimal 100 major iterations of the optimization, we end up with 200,000 aerodynamic calculations per optimization. This strongly discourages any attempt to include a highfidelity aerodynamic analysis directly within WingMOD. 4 American Institute of Aeronautics and Astronautics

105 The difficulty that severely delayed credible application of WingMOD on the BWB was the finding that the original WingMOD aerodynamics model was missing important characteristics that were captured in Navier Stokes codes. Because the flow around the center-body is three-dimensional, the center-body pressures correspond to the flow over a thinner effective 2-D section. 3-D relief is felt because the neighboring airfoils around the center-body are not as thick. This allows the thick sections that are needed to enclose the payload. In return, the outboard wing feels increased velocities because of the thick center-body and the pressures on its airfoils correspond to effectively thicker sections. These effects were modeled as described in Reference 6. An example of this effect is shown in Figure 3. Without this model, WingMOD could not produce aerodynamically feasible designs. Figure 3. Baseline effective t/c distributions. This example highlights a few of the obstacles to use of MDO in industry. First there is the reluctance to backoff on fidelity. Second is the breadth of criteria that should be considered in developing an optimal design. Coupled with the first obstacle, this either leads to prohibitively long optimization times or a substantial reduction in scope of the optimization problem. Third is a lack of intermediate-fidelity codes that can adequately substitute for high-fidelity codes at a fraction of the computing cost. The WingMOD approach tackles this third obstacle but continues to meet resistance on the issue of fidelity. Structural Method Improvements In structures and weights, a new method was employed to model the BWB center-body. The center-body is essentially wing structure, but it is pressurized and has very large rib spacing to accommodate the cabin. Structural equations were introduced in WingMOD to analyze wing skin panels as beam-columns with applied lateral pressure loads. This differs from the basic WingMOD buckling analysis, which looks only at buckling stability. Lateral pressure loads and compressive column loads from global bending moments are applied to the skin panels, generating nonlinear loads. Skin panels are modeled as sandwich structure with composite face sheets. While the core depth is set externally by manufacturability or damage tolerance constraints, the face sheet thicknesses are sized directly in the optimization to meet stress allowables. Panel stresses are evaluated at design running loads that are set in the optimization and are constrained to exceed actual running loads calculated through a wide array of structural design conditions. Stability and Control Improvements In the area of stability and control, the BWB forced the inclusion of new concerns in the WingMOD optimization, including scheduling control surface deflections and observing center-of-gravity issues. Scheduling control surface deflections is important because the airplane is trimmed with control surfaces distributed along the wing, which will impact the spanload and have first-order impacts on drag and weight. Center-of-gravity (CG) and balance issues are important because they indirectly affect the spanload by defining the trim points for the airplane. To enable optimization of control surface deflections while emulating a realizable control law structure, WingMOD was modified to accept five deflection schedules: high-speed trim, high-speed control, lowspeed trim, low-speed control, and maneuver load alleviation. These gear the control surfaces of all elements in the WingMOD model to pilot trim control, pilot maneuver control, and load factor. During optimization, control settings are set to trim the airplane and control surface gearing is selected to optimize performance. The high-speed trim gearing targets minimum trimmed cruise drag. The high-speed control and maneuver load alleviation gearings seek reduced critical loads. The low-speed gearings provide control authority over a range of conditions while preventing control surfaces from saturating or wing sections from stalling. To assess center-of-gravity issues, WingMOD was modified to track the longitudinal position of structure, fuel, payload, and general discrete masses. The array of conditions analyzed in WingMOD includes conditions that set both forward and aft CG limits. During planform optimization, the limits are matched to the actual longitudinal balance. The range for the performance cruise mission is based on trimmed drag evaluated at the calculated CG. This encourages planforms that minimize CG range. Propulsion Airframe Integration Propulsion-airframe integration is an intimidating challenge for the BWB. This has been attacked through CFD analysis and inverse design, with initial results showing promise for solving the design problem albeit through a lengthy process. With the fine detail required 5 American Institute of Aeronautics and Astronautics

106 for this work, there is little hope of incorporating this directly in a WingMOD optimization, although new approaches to course-grained distributed design are being investigated to accomplish this kind of integrated design capability 2. Designing with WingMOD With this brief description of the fundamental methodology of WingMOD and the design challenges of the BWB, we next summarize an example of the work that has been accomplished with WingMOD on the BWB. This example will hint at the detail and complexity that is needed to address an industrial aircraft design problem with MDO. This example shows the substantial gains that might be achieved on novel concepts, such as the BWB, where tight design integration and lack of design experience make the application of MDO not just a nicety, but a necessity. Critics may argue that the problem addressed in this example is not broad enough or that the analysis methods are not deep enough to satisfy the concerns of industry. More is definitely desired in both breadth and depth, and much work remains to be done to achieve these improvements; however, WingMOD optimizations are providing answers that are useful to industry now. While the BWB program has yet to study an MDO-based design in detail, the directions taken by WingMOD in seeking optimal designs have provoked thought, discussions, and conventional studies that have led to improved designs. MDO has gained acceptance in the BWB program as a tool to find ways to improve the design. This example uses a notional BWB developed under Task 18 of the Advanced Subsonic Technology (AST) program. The baseline airplane was configured and sized conventionally. The airplane mission was to carry 855 passengers 7,500 nmi at Mach 0.85, although less ambitious BWB configurations are currently under study. Further details of the optimization are given in Reference 6. Design Conditions To touch on most of the critical issues affecting the BWB, 20 design conditions were examined, as described in Reference 6. The BWB is highly sensitive to CG location because that governs the deflection of the control surfaces, the spanload, and ultimately the drag and weight. Where we can usually identify a critical CG location for each condition on a conventional airplane, the influence of control surface deflections on the spanload makes this difficult or impossible on the BWB; hence, several conditions are examined at both CG locations. This is one way the BWB stretches the breadth of any MDO effort. Even with this breadth, more conditions are desirable, with the first additions likely to be used for analyzing yaw control constraints. Design Variables Design variables are listed in Table 1. The details are discussed in Reference 6. The design variables cover both external geometry and interior arrangement of the major structural components. The boundaries of the cabin can be optimized as well as the distribution of fuel. Schedules for deflection of control surfaces and structural sizing can be handled. Optimizing these quantities results in a 134 variable problem. This number of variables is admittedly small relative to some optimization problems (e.g. detailed structural sizing and trajectories through collocation); however, the extent of the geometric degrees-of-freedom make this an ambitious MDO problem. One obstacle to the use of high-fidelity codes in MDO has been the ability to automatically handle major geometry changes. FEM models and, to a lesser extent, CFD models would offer resistance to the planform changes examined in this example. The simpler models in WingMOD allow very broad variations in geometry to be explored. This is important for the BWB because there is too little experience with the design to substantially narrow the design space. To those unfamiliar with the use of formal optimization in aircraft conceptual design, 134 design variables is quite a lot. It is more than a human would be able to sort out using conventional trade studies and exceeds the capability of most current advanced design codes. Name Number mission takeoff weight 2 chord 9 sweep 7 t/c 8 incidence 7 payload chordwise extent 10 spar location 7 fuel distribution 6 nose tank fuel 3 CG limits 2 CG location 3 trim deflection schedule 8 control deflection schedule 8 trim angle of attack 16 trim or control deflection 16 trim load factors 2 design running load 13 center-body skin thickness 7 total 134 Table 1. Design Variables 6 American Institute of Aeronautics and Astronautics

107 This is particularly important for the BWB because existing tools that size thrust and wing area do not properly handle geometric changes to the BWB or account for important BWB constraints. Constraints Constraints are listed in Table 2. The constraints cover performance, stability, control, balance, structural design, buffet, and maximum lift. They also include geometric constraints that force the wing to wrap around a fixed payload. The details are left to Reference 6, but this table should indicate the breadth of constraints that are necessary to undertake an industrial MDO problem. There are a large number of constraints, 705, but only 90 are active. The constraintbased sequential quadratic programming algorithm used in WingMOD handles large numbers of constraints very easily, so the approach taken is to include all the constraints that could possibly drive the design and to let the optimizer determine the ones that do. When the active constraints are compared against the 134 design variables, there are 44 unconstrained degrees of freedom. This is a large dimension to explore that would take a prohibitively long time to navigate with conventional advanced-design methods. Optimization Results When the optimization was carried out, the design moved from the baseline configuration sketched in Figure 4 to the optimized configuration sketched in Figure 5. Additional human design input may be used to simplify the design from the optimizer, smoothing features that add much design complexity for small performance gains. This leads to a final design such as that shown in Figure 1. Alternately, the design could be re-optimized with fewer design variables after initial optimizations reveal the most important planform breaks. The most substantial design changes were tighter packaging of the payload and the thinning of airfoils in the kink of the wing. By changing planform and thickness, the optimized design achieved a much tighter fit of the payload between the spars. The payload extent is indicated by the shading in the figures. This reduced the area of pressurized skin for a substantial reduction in weight. Thinning of the kink airfoil sections relieved compressibility drag penalties and allowed the optimized design to load the kink region for a better spanload and lower drag. This is described in more detail in Reference 6. The final performance results are shown in Table 3. Name Number Number Critical range 2 2 L/D 1 0 static margin 6 1 payload weight 1 1 payload height payload chordwise extent 20 4 spar location 12 0 minimum chord 3 3 fuel volume 2 0 fuel distribution 6 0 nose tank fuel 3 1 CG location Figure 4. Baseline 3 Configuration. 0 CG limits 5 4 control surface deflection 25 1 trim load factor trim pitching moment center-body stress 8 7 running load bounds 13 0 running load maximum lift buffet 23 5 buffet character 23 1 total Figure 5. Unmodified Table 2. Optimized Constraints Configuration. 7 American Institute of Aeronautics and Astronautics

108 Operating empty weight is reduced by better packaging of the payload. L/D is increased, largely because of better span loadings. The baseline airplane has a WingMOD-optimized span load that balances weight, drag, and control considerations. Had the baseline span load been aerodynamics-optimized, the optimized design would show little improvement or even degradation in L/D, but it would show more substantial empty weight reduction. In optimizing from aerodynamics-defined wings, MDO almost always finds ways to improve the other disciplines at a small expense to aerodynamics. This can make it difficult for MDObased designs to gain acceptance from aerodynamics, especially because the aerodynamic penalties can be captured with high-fidelity early in the design process while the projected gains in other disciplines can take months to substantiate. performance figure % change from baseline takeoff weight -6.9 operating empty weight -5.0 fuel burn gross area +0.8 average L/D +7.5 Table 3. Optimization Results The combination of weight and drag reduction results in substantial reductions in fuel burn and takeoff weight. Wing area, which is a primary design variable for conventional sizing methods, is virtually unchanged, meaning that improvements were made through much finer manipulation of the geometry. This shows a fundamental advantage of multidisciplinary optimization over conventional sizing processes. In addition, the design was accomplished in a short time, with overnight optimization runs and a few tries to perfect the optimization problem. This contrasts with the months of study that would be required to optimize the design conventionally. The design improvements and speed that MDO offers show great promise for advancing BWB design. The Promise of MDO The basic conclusion of this exercise is that the design capabilities of an MDO process can lead to substantial improvement in the design of a novel configuration such as the BWB. There are some less-visible advantages that come from MDO codes that are described below. Design Cycle Time In design studies using conventional methods, the following observations could be made. The conventional advanced design process uses 3 to 6 weeks for a BWB planform change to cycle through configuration, weights, aerodynamics, and performance analysis. Optimizing an aircraft could take several cycles (months) to optimize the aircraft. The cycle time limits the number of design variations that can be explored. Even worse, this cycle time only covers performance analysis; additional time is required for balance, aeroelastics, stability and control. In the course of this study, the advantages of the WingMOD approach could be seen. It still takes 3 to 6 weeks to model and calibrate a baseline design in WingMOD. This is comparable to the cycle time for a planform analysis using conventional methods; however, only a single run is needed to optimize the aircraft, reducing months of cycle time to an overnight job. In addition, the optimization handles many more design variations than could be explored by the conventional methods. Finally, the optimization deals with balance, aeroelastics, stability and control issues that the conventional approach leave for later analysis and revision. First-Cut Information To perform multidisciplinary optimization, coupling aerodynamic loads and structural design is almost a must. From there, it is natural to make that an aeroelastic calculation. Doing this for MDO adds the advantage that the resulting system is highly-automated, fast, and robust. An unexpected benefit is that an MDO code, like WingMOD, with grandiose expectations of planform optimization becomes amazingly useful for mundane tasks such as providing a first estimate of loads, an initial sizing for skin thicknesses, and aeroelastic stability data. While there are industrial processes in place to do all this, they are expensive, time-consuming, and have a chicken-or-the-egg problem: how do you generate loads when you need skin thicknesses to capture the aeroelastic effects, but you need loads to figure out what the skin thicknesses need to be? The fidelity of those processes justifies their expense, and we would never use WingMOD to certify an airplane, but WingMOD is perfect for getting the first cut at the loads and structural sizing from which the detailed processes can start. Individual Versus Total Good Pushing for overall airplane improvement over individual discipline improvement can be a difficult practice to incorporate in a large design team, but it is especially important for a revolutionary concept such as the BWB. Traditionally, aerodynamics has taken the lead in defining wing shape. A compelling reason for this is the speed of aerodynamic processes: a wing-only planform change can be put through CFD in as little as a few days. The other disciplines are not so lucky: a finite element model can take six months. So while 8 American Institute of Aeronautics and Astronautics

109 aerodynamics can push for a particular design with hard facts, the other disciplines can offer only qualitative objections, or the design cycle must drag on for hard numbers from the other disciplines. For conventional aircraft, this is not very critical: the wing turns out heavier and the tail turns out bigger than they ought to be, but the airplane will still work. For the BWB, this could be disastrous: the wing shape that maximizes L/D is unlikely to lead to a balanced airplane with the control authority to rotate for takeoff. The WingMOD approach looks at all the design drivers it can to offer a design that is the best compromise between the disciplines. Analyses provide hard numbers, albeit approximate, for each discipline, making it difficult for any one discipline to dominate. It is difficult to accept that WingMOD designs inevitably come in with lower L/D than aerodynamics group knows they can achieve, while offering benefits in other disciplines that cannot be immediately verified. Even within aerodynamics, WingMOD will compromise cruise performance to enable meeting low-speed lift and control requirements. Future Directions While WingMOD optimization has made promising first steps toward solving the BWB design problem through MDO, much more is desired. Problem areas specific to the BWB are identified below. Increased Breadth While the breadth of conditions examined by WingMOD is relatively well accepted, there are instances where more is desired. An example is modeling engine-out lateral control. From experience with the BWB-17 Flight Control Testbed 2, this could drive the sizing of the outboard wing and winglet chords, which affect the effectiveness of the rudders needed to control this condition. Higher-Fidelity Codes The WingMOD aerodynamics module certainly leaves something to be desired for analyzing the BWB; however, the speed of this analysis is required to cover the breadth of flight conditions that are essential to performing any multidisciplinary planform optimization. Because of their speed, higher-fidelity panel methods are the most likely next-step to improving the WingMOD aerodynamic analysis. Incorporating a true CFD analysis promises the benefit of capturing all the important aerodynamic effects and the ability to directly handle the propulsion-airframe integration problem; however, direct inclusion of CFD at this time would likely bring a WingMOD-breadth optimization to a screeching halt. The inclusion of finite element methods (FEM) is a lower priority than CFD. This is because the span time for generating adequately detailed FEM models is too long for them to be used actively in the conventional design process. Design work on the BWB uses weight estimates from parametric equations that may be calibrated to but are really independent from FEM results. The intermediate-fidelity structural analysis in WingMOD is already better than parametric weight equations, so the optimization cannot be faulted with missing something the standard approach would catch. At this stage, FEM work is very important for calibrating weights codes and verifying that there are no show-stoppers in the design, but it works too slowly to substantially impact planform trade studies. If FEM analysis had a span time equivalent to that for CFD analysis, then it would play a stronger role in the early definition of an aircraft, and there would be a greater impetus to include it in advanced-design MDO. A tantalizing prospect for increasing the fidelity of a WingMOD-type optimization is incorporation of a detailed mission analysis code. This could bring high quality to the performance figures at little computational cost. It could also eliminate many standin constraints, for example takeoff speed targets instead of a true field length constraint. The issues here include judiciously selecting a minimum number of aerodynamic analyses to provide the data required for the mission analysis and generating noise-free numbers from the mission analysis. Propulsion-airframe integration is especially important for the BWB because of the potential for either improved performance or problems with high distortion associated with boundary layer ingestion. Because of the complex, viscous, transonic flow in this region, simple models are ineffective and one is forced to rely on rather time-consuming CFD simulations for reliable guidance. The simple framework on which WingMOD is based is not well-suited to the incorporation of such methods and future work is clearly required in this area. Optimization Framework Improvements While the example optimization presented in this paper is large, many other parameters must be input to run WingMOD and this presents an often bewilderingly steep learning curve. Improvements in the way the framework handles large numbers of variables would help divide the problem to be more tractable to the user. Applying techniques for decomposition through the optimization framework would be ideal. That would provide additional capability while allowing subproblem analyses to remain unchanged and unburdened by the complexity of the overall optimization problem. A candidate project likely to help BWB optimization studies would build collaborative optimization capability into the Genie framework. 9 American Institute of Aeronautics and Astronautics

110 The Challenge of MDO The promise of MDO has been suggested by our recent experience with BWB design; however, it has also highlighted some of the generic problems and challenges in industrial acceptance of MDO. Problem Formulation As with single discipline optimization, correct and efficient problem formulation is critical to obtaining useful results from MDO. Because of the subtle interactions and interdisciplinary feedback that may be less well known to disciplinary experts, it is often more difficult to anticipate the weaknesses of analyses or the ill-posedness of a particular problem. Experience with both conventional and BWB design suggests that the problem formulation (selection of design variables, objectives, constraints, and bounds) evolves as the design is developed. It is naïve to expect that a realistic large-scale MDO problem can be fully-understood by a design team from the outset. While automatic aerodynamic optimization with a specified planform and a restricted set of design conditions can be reasonably well formulated a priori, the multidisciplinary aircraft design problem is more challenging and calls for a qualitatively different approach. One must structure the problem in such a way that changes in design variables and constraints can be made along the way. Individuals and truly integrated teams must routinely meet to evaluate the results and refine the analysis requirements or problem definition. The potential for impractical designs that reduce the credibility of the process is great without such planned intervention. Breadth Versus Depth Multidisciplinary optimization results are often criticized for being so limited in scope or fidelity as to be merely academic exercises and such criticism is often well justified. Based on the notion that a chain is only as strong as its weakest link, low-fidelity models covering many disciplines are sometimes omitted, leaving a two or (rarely) three discipline MDO problem that uses sophisticated disciplinary models. A chain with missing links is worse than one with weak links. A classic example is that aerodynamic and structural optimization without consideration of maximum lift leads to wings with absurdly small tip chords 3. The BWB design problem illustrates the large number of disciplines to yield reasonable results. On the other hand, the BWB represents an example of a design for which 2-D section analysis superimposed on a simple 3-D model fails to reveal some of the fundamental opportunities available in the BWB design space. The use of too-simple analyses might lead one to conclude that the advantages of the concept were insufficient to warrant the development of improved analyses or further consideration. This is one of the most fundamental dilemmas in MDO that will not be solved by advances in optimization theory or AI. Practical MDO will always require good engineering judgement to match the scope of the particular problem to appropriate analyses. Approximate models are often very adequate, depending on the actual sensitivities of active constraints and objectives to the particular choices for design variables. Rapidly increasing computational capabilities including parallel systems and efficient algorithms will change the selection of appropriate models, but will not reduce the importance of this step. As more sophisticated analyses become feasible, the importance and difficulty of problem formulation and integration will only increase. Optimization Analysis Requirements The breadth versus depth problem would be alleviated if high-fidelity analyses ran faster. Intriguing options for increasing CFD optimization speed are automatic differentiation and adjoint formulations, the latter promising sensitivity information for little more than a function evaluation, although the present problem involves a large number of constraints that reduce the attractiveness of an adjoint approach. The best improvements for FEM lie in automating the model generation process. Beyond speed, analyses must be robust and smooth to be used with optimization. The robustness of automatic grid generation through large planform variations is a problem. The smoothness of CFD and FEM results is also an issue. Speed, robustness, and smoothness are also an issue with mission analysis codes. While several mission analysis codes exist that admirably fill the requirements of engineering analysis, the requirements for optimization motivate the creation of new codes that are built for optimization from the ground up. Such codes could use techniques, such as collocation, that make sense for optimization but were not important for the engineering needs the existing codes were written for. Integration In the development of WingMOD little attention was given to allowing for integration of existing codes or optimization decomposition techniques: the lack or unavailability of fast, intermediate-fidelity codes made it more expedient to develop an all-new, tightly-coupled analysis, which would not benefit from decomposition. 10 American Institute of Aeronautics and Astronautics

111 As more complex aerodynamic, structural, and dynamic analyses are included in BWB optimization, the basic tightly-integrated framework on which WingMOD is based begins to become unwieldy. Several research programs are currently underway to address such problems, although applications as complex as the BWB planform design problem have not been satisfactorily demonstrated to date. This would constitute an excellent test for the industrial applications of various concepts for decomposed analysis and distributed design, Reference 7. The best near-term possibilities for bringing CFD into BWB MDO may be in the use of response surfaces and collaborative optimization. Collaborative optimization would isolate the CFD analysis in its own sub-space. Response surface techniques could map and capture the CFD analysis sub-space, which could then be included in a collaborative optimization formulation with WingMOD capturing the non-aerodynamic disciplines. Alternately, response surfaces could simply capture aerodynamic data from specific CFD runs to be laid over WingMOD aerodynamic results. A tight coupling of aerodynamics and structures for aeroelastic loads calculation combined with a loosely-coupled, higherfidelity aerodynamic performance code may solve some of the problems that involve both high dimensionality coupling and the need for very accurate aerodynamic solutions. Although various techniques for loosely coupling multidisciplinary design problems have been proposed, (e.g. concurrent subspace optimization and collaborative optimization 8-9 ), few have seen application in industry projects. We attribute this primarily to the fact that these techniques are still the subject of active research and have not matured to the point that they are easily implemented as an option in a commercial software package. The availability of such technology may reduce the need for an individual who understands both the particular design problem and the details of the optimization framework and theory. Although progress in this area continues, Reference 10, we do not expect that such a system is imminent. Validation There are very few examples of MDO-derived designs being validated to the point of being real, useable configurations. Advanced-design level optimization needs to be validated with high-fidelity analysis; highfidelity optimization needs to be validated through broad analysis checks. Reference 5 describes the use of WingMOD to develop a conventional aircraft wing configuration and the subsequent CFD validation. Achieving acceptance for MDO in industry will require more examples of validated optimized designs. No validation of an optimized BWB design has been done, but WingMOD designs are close to being assessed with CFD. Passing the challenge of validation will be most important to bringing MDO to the forefront of BWB design. Conclusions The BWB is a revolutionary concept that benefits from MDO and yet illustrates the many challenges to its use in industry. Current efforts with the WingMOD code have been stretched in depth, particularly to capture unusual aerodynamic characteristics, and in breadth, to capture stability and control issues. Introducing highfidelity analysis would be highly desirable, a prerequisite for handling propulsion-airframe integration, yet the breadth of the BWB design problem almost prohibits the direct substitution of more sophisticated codes for the current simpler models. Much progress has been made with the advanced-design level WingMOD code. Successful optimization has been made with a large, comprehensive set of design variables and constraints. Attacking this broad problem has offered substantial payoffs because of the youth of the BWB concept: current BWB configurations are not as finely evolved as conventional transports. The success in handling this broad design problem has partly been facilitated through capabilities provided by the Genie optimization framework. MDO offers much promise for improving the BWB. Optimization studies have shown potential for substantial reductions in takeoff weight. This comes from the ability of MDO to handle many more degrees of freedom and track more interactions across disciplines than conventional advanced-design processes. The BWB can benefit greatly from MDO because of the complexity of its geometry and the integrated nature of its design. In addition, the innate automation required for optimization offers significant reductions in design cycle time while handling considerations beyond the scope of the existing processes, including control surface deflections, balance, control, and aeroelastic effectiveness. Achieving the promise will involve more work. Increased breadth of analysis and optimization framework improvements will evolve naturally, although it would be desirable to accelerate those developments. Incorporating higher-fidelity codes while maintaining the breadth of scope will be a large challenge, offering opportunities to test methods such as response surfaces and collaborative optimization. While current BWB work demonstrates the potential for MDO in aircraft advanced design, it remains to verify the predicted advantages of these optimized designs using more refined analysis codes. 11 American Institute of Aeronautics and Astronautics

112 References [1] Liebeck, R. H., Page, M. A., Rawdon, B. K., Blended-Wing-Body Subsonic Commercial Transport, AIAA Paper , Jan [2] Blended-Wing-Body Technology Study, Final Report, NASA Contract NAS , Boeing Report CRAD-9405-TR-3780, Oct [3] Wakayama, S., Kroo, I., Subsonic Wing Planform Design Using Multidisciplinary Optimization, Journal of Aircraft, Vol. 32, No. 4, Jul.-Aug. 1995, pp [4] Wakayama, S., Lifting Surface Design Using Multidisciplinary Optimization, Ph.D. Thesis, Stanford University, Dec [5] Wakayama, S., Page, M., Liebeck, R., Multidisciplinary Optimization on an Advanced Composite Wing, AIAA Paper , Sep [6] Wakayama, S., Multidisciplinary Design Optimization of the Blended-Wing-Body, AIAA Paper , Sep [7] Kroo, I., Multidisciplinary Optimization Applications in Aircraft Preliminary Design Status and Directions, AIAA Paper , Apr [8] Kroo, I., Decomposition and Collaborative Optimization for Large-Scale Aerospace Design Programs, in Multidisciplinary Design Optimization: State of the Art, N. Alexandrov and M. Y. Hussaini, editors, SIAM, [9] Braun, R. D., and Kroo, I. M., Development and Application of the Collaborative Optimization Architecture in a Multidisciplinary Design Environment, in Multidisciplinary Design Optimization: State of the Art, N. Alexandrov and M. Y. Hussaini, editors, SIAM, [10]Sobieski, I. P., Manning, V. M., Kroo, I. M., Response Surface Estimation and Refinement in Collaborative Optimization, AIAA Paper , Sep American Institute of Aeronautics and Astronautics

113 AIAA A DESCRIPTION OF THE F/A-18E/F DESIGN AND DESIGN PROCESS James A. Young *, Ronald D. Anderson **, and Rudolph N. Yurkovich + The Boeing Company St. Louis, MO Abstract This paper describes the design and the design process used to develop the F/A-18E/F aircraft. It is presented here to document the state-of-the art of the design process for development of a modern high performance fighter aircraft. It is intended that this information will provide a background for researchers developing Multidisciplinary Design Optimization (MDO) processes for aircraft design. The design process itself was an advance for the F/A-18E/F in that it marked the first application of the Integrated Product Development (IPD) design process to an Engineering Manufacturing Development (EMD) program at the McDonnell Douglas Corporation. Since the F/A-18E/F's flight test program is well under way, results are available by which to judge the success of this design and the design process. Finally, some conclusions and recommendations for additional work to improve the design process are made. Introduction In 1990 the MDO Technical Committee (TC) was formed as a technical committee of the AIAA. One of the tasks that this committee undertook was to define the state-of-the-art as it existed at that time and the results of this study were published as Reference 1. Since 1990 other documents have also presented stateof-the-art approaches with Reference 2 being an excellent example. The references have done an excellent job of documenting theoretical developments. However, the AIAA MDO TC felt that more was required to transfer the MDO message from the theoreticians to the aircraft designer and for the theoreticians to have a better perspective on what is required to design a new aircraft. It was determined that a series of papers by industry documenting the current design process as used on current design programs would be an appropriate step in making this happen. This paper, which addresses the F/A-18E/F, is one of a series of papers in response to that action item. The F/A-18E/F, shown in Figure 1, represents the next step in the evolution of the F/A-18 aircraft. In addition, its development represents a next step in the evolution of the aircraft design process. The E/F was designed using the Integrated Product Team (IPT) approach and this represents a significant advance from the design process used in the development of the original aircraft. This paper presents a description of the aircraft design as well as a description of the design process. GP cvs Figure 1. F/A-18E/F Super Hornet In MDO an objective function subject to a set of constraints is defined and a mathematical process is used to minimize this objective function without violating the constraints. Sensitivity derivatives are usually computed as part of the optimization process. Reference 3 provides a good description of the mathematical process. If the above definition of MDO is applied in a strict sense, then MDO was not used to design the F/A-18E/F. However, the F/A-18E/F was designed using a Multidisciplinary Design Process. Based on results obtained from the flight test program, the aircraft is a very successful one. Thus, the current design process must also be regarded as successful. The F/A-18E/F was designed to meet a specific set of requirements rather than by optimizing a specific objective function. From the perspective of MDO, these requirements can be viewed as constraints which implies that the F/A-18E/F is a feasible design. * Director of Engineering, F/A-18 Program ** Director, Phantom Works, Assoc. Fellow AIAA + Fellow, Assoc. Fellow AIAA Copyright 1998 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. 1 American Institute of Aeronautics and Astronautics

114 Description of the Aircraft Aircraft Missions - The F/A-18E/F is a multi-mission aircraft designed for the US Navy. The concept of a multi-mission aircraft is significant for the MDO process in that there are multiple requirements that the aircraft must meet, and this complicates the definition of an objective function. For a single mission aircraft, the formulation of the objective function is a simpler task. The F/A-18E/F was designed to perform both air-toground and air-to-air missions. These missions were defined as requirements and the goal was to develop a design that satisfied them. A description of the MDO process as it applies to a multi-mission aircraft was initially presented in Reference 4. Figure 2 illustrates the multi-mission concept starting with maritime air superiority on the left and proceeding to all weather attack on the right. These mission extremes are significant in that historically they have been performed by dedicated aircraft. The F-14D performs the air superiority mission and the A-6F performs the all weather attack mission. While the F/A- 18C/D has some capability to perform these missions, it has not been optimized for them. For fleet defense the F-14 with its Phoenix missile system is superior to the F/A-18C/D. However, as a multi-mission aircraft, the F/A-18C/D still has significant capability in this area. Similar arguments can be made for the ground attack missions. originally derived from the Air Force lightweight fighter competition. Consequently, there is a great deal of history behind this configuration with the general shape of the aircraft being defined by the original YF-17. Figure 3 shows the planform view of these three aircraft and the heritage of the E/F aircraft is obvious. Table 1 summarizes some of the basic geometry data. The original YF-17 had a wingspan of 35 ft and a wing area of 350 sq. ft. For the F/A-18A the corresponding numbers are 37.5 ft and 400 sq. ft. While the basic aerodynamic concept of the YF-17 and the F/A-18A were essentially the same, the interior of the F/A-18A was completely redesigned. Most of the required changes were a result of transforming what was a lightweight fighter for the Air Force to a ship-board multirole aircraft for the US Navy. YF-17 F/A-18A F/A-18E GP cvs Figure 3. Comparison of Aircraft Planforms Maritime Air Superiority F-14D/ NATF Air Combat Fighter Fighter Escort Recce F/A-18 A/B/C/D F/A-18 E/F Close Air Support Air Defense Suppression Day/ Night Attack All Weather Attack A-6F/ A-12 GP cvs Figure 2. Hornet Spans the Mission Spec As the F-14D s and the A-6F s are retired form the fleet, they will be replaced by F/A-18E/F s. Thus, the original mission spectrum of the F/A-18C/D has been expanded even further for the F/A-18E/F as shown in Figure 2. Each of these missions has a specific set of requirements that the aircraft must meet. An MDO approach to meeting these requirements was not taken because MDO design techniques were not available at the time the F/A-18E/F was designed. However, for future aircraft design this approach may offer significant improvements if appropriate tools can be developed. History of the Configuration - The F/A-18E/F is a derivative of the F/A-18C/D aircraft, which was Dimensions YF-17 F/A-18A F/A-18 E Span (without missiles) 35.0ft 37.6ft 42.9ft Length 56.0ft 56.0ft 60.2ft Height 14.5ft 15.3ft 15.8ft Tail span 22.2ft 21.6ft 23.3ft Wheel track 06.9ft 10.2ft 10.45ft Wing area 350sq ft 400sq ft 500sq ft Weights Empty Fighter configuration 17,000lb approx. 21,830lb 30,600lb 23,000lb 34,700lb 47,900lb Maximum 51,900lb 66,000lb Table 1. Comparison of Specifications 2 American Institute of Aeronautics and Astronautics

115 At the time that the F/A-18A was under going preliminary design, the lightweight fighter competition was still ongoing. This provided a constraint on the original F/A-18A that resulted in the F/A-18A still having essentially the same size and shape as the YF- 17. For the MDO process, this is significant because it implies a constraint that would not be present if the F/A-18A were a totally new aircraft. Similar observations can be made for the F/A-18E relative to the F/A-18A. The F/A-18E configuration grew relative to the F/A-18A configuration. The span of the F/A-18E is 44.7 ft and the wing area is 500 sq. ft. However, the general shape of the aircraft has been maintained. A comparison of the F/A-18E Super Hornet to the original Hornet is shown in Figure 4. In addition to the Super Hornet being a larger aircraft with a new inlet, changes in the Leading Edge Extension (LEX) and the addition of a wing leading-edge snag are apparent. GP cvs Figure 4. Super Hornet Compared to Original Hornet in Flight Hornet 2000 Study - The evolution of this new configuration had its origins in the Hornet 2000 study, Reference 5, which was conducted in 1988 by a joint team composed of the US Navy and McDonnell Douglas. Over the life of the F/A-18A/B and F/A- 18C/D aircraft many changes were incorporated that resulted in an increase in weight and the internal space being used for new and additional avionics equipment. Because of this growth, reductions in range and other performance metrics occurred. In addition, changes to meet the increased threat that the aircraft was to face were required. It was anticipated that the capabilities of the threat would continue to increase. Quoting from the Hornet 2000 study; Major advances in threat capability have occurred since the F/A-18 was designed in the mid 70s. The original design goal for the Hornet was to have superiority over FISHBED and FLOGGER class air threats and to penetrate battlefields with SA-2, SA-3, SA-6, and SA-7 class surface-to-air threats. That threat has changed rapidly in character and capability, primarily as a result of successful Soviet efforts in technology transfer. The Soviets have demonstrated an ability to implement rapidly technologies developed domestically and acquired through legal and covert means. Through this aggressive program of modernization, the ability of the threat to confront the Carrier Battle Group has increased significantly. Since 1988, a great deal has happened to change the nature of the threat. However, while the need to deal with the Soviet threat may have diminished, new threats have emerged. The need to deal with these threats formed a significant requirement for an advanced Hornet. In addition to recognizing the need for a new aircraft, the Hornet 2000 Study identified planned improvements for the F/A-18C/D aircraft through These improvements were in three major areas: avionics, propulsion, and equipment. The avionics upgrades were to improve the F/A-18 weapon system capabilities in the areas of situational awareness, air superiority, air-tosurface attack and survivability. The propulsion upgrade consisted of replacing the baseline engines with the Enhanced Performance Engine (EPE). This engine offered significant performance improvements at higher speeds and could be incorporated without airframe changes. The equipment growth consisted of installing an On-Board Oxygen Generating System (OBOGS) increasing the aircraft cooling capacity by an ECS upgrade, and adding a bay in the left hand LEX to allow installation of additional avionics. In summary, because of the changing nature of the threat and because the basic aircraft, even with the EPE, had just about reached the limits of its capabilities, a new aircraft was required. The Hornet 2000 Study produced a set of requirements and an aircraft configuration that addressed them. This study looked beyond the 1990s to determine the requirements for the aircraft such that it could continue to meet the threat. The goal of the study was to identify high value upgrades and develop a phased incorporation plan to ensure continued F/A-18 survivability and effectiveness. This new aircraft configuration, however, had a constraint that required as much commonality as possible with the original aircraft. Even with this constraint, early in the design process, several 3 American Institute of Aeronautics and Astronautics

116 alternative configurations were investigated and a sample of these configurations is shown in Figure 5. While this study was specifically directed to upgrading the F/A-18, it is believed that it is representative of the type of trade study that would be conducted by industry and therefore should be relevant to the development of MDO to the design process. Seven potential configurations to meet the US Navy missions needs in 1995 and beyond were investigated. These configurations spanned the range from minimum changes through Block Upgrades to major concept changes that reflected canard-wing arrangements popular at the time. The configurations were built from the same baseline and took advantage of planned upgrades. They also shared common requirements for an updated weapon system, survivability improvements and increased thrust. I FY88 Baseline Plus FY90 and FY92 Avionics Upgrades Weapon System Upgrade Survivability Enhancement Enhanced Performance Engine GP cvs IV Fuselage Plugs Cranked Arrow Wing With Canards II Increased Fuel Growth II Engine Active Array Radar INEWS IIIA Fuselage Plugs Larger Wing With Increased Chord IIIC Raised Dorsal Stiffened Wing III Raised Dorsal Larger Wing With Increased Chord IIIB Raised Dorsal Larger Wing With Increased Chord and Span Fuselage Plugs Figure 5. Configuration Options Larger Wing With Increased Chord and Span Configuration I minimized the impact to the airframe. Weapon system updates were achieved within the existing space/volume. Pilot situational awareness was improved and workload decreased by upgrading the cockpit to display integrated weapon system information. Advanced air-to-air missile capability was provided along with the capability to carry air-to-air missiles on the out-board pylons. The remaining configurations incorporated changes to the airframe. Common elements include increased fuel, new Growth II engines, and an electronically scanned active array radar. Configuration II expanded mission flexibility with additional internal fuel in a raised dorsal. A configuration of this type was successfully used on the A-4M. Performance improvements were achieved with the higher thrust engines that required enlarged inlets. External stores carriage speeds were increased with a stiffened wing. Target detection range was more than doubled by adding the active array radar. Adding new electronic warfare equipment for passive missile detection and laser warning enhanced survivability. Configuration III incorporated the upgrades of Configuration II while replacing the stiffened wing with an enlarged wing for enhanced carrier suitability, maneuverability, and mission performance. Additional growth space was also provided. Configuration IIIA enhanced the transonic/supersonic flight regime by utilizing a fuselage plug rather than the raised dorsal for increased fuel. Configuration IIIB optimized the wing area growth of Configuration III with an increased wing span for improvements in mission radius and carrier suitability performance. Configuration IIIC combined the fuselage of Configuration IIIA and the wing of Configuration IIIB for enhanced transonic/supersonic flight and improved mission and carrier suitability performance. Configuration IV added fuselage plugs similar to Configurations IIIA and IIIC. However, the aerodynamic configuration was completely new and was targeted at potential co-development by the USN and an international customer. The wing was a cranked arrow wing and the stabilator was replaced by a canard. The vertical tails were also of a new design. This configuration shared the fuselage and all of the internal components of Configurations IIIA and IIIC including one of the major cost contributors, its avionics suite. A detailed discussion of the features and benefits of each of these configurations is beyond the scope of this paper. Each presents new operational benefits and, in general, as additional benefits are added so is additional cost. For the future, MDO could be used to determine which configuration best meets the new requirements for an improved strike fighter. At the time the study was conducted, MDO techniques to aid in this decision did not exist. The new engine, which was assumed for Configurations II through IV, fostered a significant multidisciplinary design integration activity. At the time of the Hornet 2000 study, this new engine was designated the F404 Growth II engine. The Growth II engine was to be an upgraded version of the F404-GE-400 engine that 4 American Institute of Aeronautics and Astronautics

117 would have significant performance improvements throughout the flight envelope. It was to provide approximately a 25 percent increase in sea level, static installed thrust. At up-and-away conditions the installed thrust increase was estimated to be up to 40 percent over the current engine. The improved performance was to be achieved through incorporation of engine components that featured advanced aerodynamics and materials. The engine also featured increased engine airflow and higher operating temperature capabilities without a reduction in the current hot section life. While a growth inlet was required for optimization of the Growth II performance, the engines fit within the current F/A-18 engine bay. The engine that is installed in the F/A-18E/F has been designated as the F414-GE- 400 engine and is an advanced derivative of the Hornet s current F404 engine family. Configurations I through IV were evaluated against the following set of criteria: carrier suitability, strike mission, fighter mission, maneuverability, fire control system, survivability, growth potential, weapon system effectiveness and cost, both recurring and nonrecurring. This evaluation was summarized in a stoplight format as shown in Figure 6 where G-greenindicates good, Y-yellow indicates marginal, and R-red indicated serious concern. It should be noted that if cost is considered, the conclusion as to which configuration is optimum is difficult to formulate. Clearly, all of the configurations represent some degree of improvement, but at some cost. All of the new configurations cost more than the baseline and all require some investment. The cheapest solution is to do nothing. On the other hand, as described earlier in the discussion of today s threat, to do nothing would put the aircraft in a situation where it would not be able to compete. The Hornet 2000 Study identified four major study paths, with seven configurations for the Hornet Upgrade. The first path, Configuration I, was attractive from a cost standpoint but had degraded aerodynamic performance and little remaining growth potential. The second path, Configuration II had impressive weapon system improvement but suffered from carrier suitability shortcomings. The third path made up of Configurations III, IIIA, IIIB, and IIIC, had significant performance, carrier suitability and weapon system Capability Carrier Suitability Strike Mission Fighter Mission Maneuverability Fire Control System Survivability Growth Potential Weapon System Effectiveness Non-Dimensional Cost Range REC NR G Y Y R R Y Y R 1.00 Y Y Y R G G R Y Y G G R G G R Y Configuration FY88 I II III IIIA IIIB IIIC IV Y G G R G G Y G Y G G R G G Y G G Good Y Marginal R Serious Concern G G G R G G G G G G G Y G G G G Y G G Y G G G G GP cvs Figure 6. Hornet 2000 Configuration Evaluation vs Threat improvements. The fourth path, Configuration IV, had Control Configured Vehicle (CCV) potential with the canard-cranked arrow wing arrangement. The Hornet Upgrade Configurations IIIB and IIIC offered the greatest increase in weapon system capability, carrier suitability and performance. They included a larger wing, more fuel, growth engine, 10 percent growth inlet, active antenna, upgraded crew station, integrated CNI avionics and an integrated electronic warfare system. The final conclusion was that Configuration IIIC was the best path for upgrade since it was considered to have the best carrier suitability performance. This discussion of the process that led to what was determined to be the best configuration provides valuable insight into the design process for MDO code developers. As stated elsewhere, an objective function that could be used to determine the optimum configuration would prove very difficult to formulate in this case. In fact, typical parameters that have been suggested as objective functions such as minimum weight or minimum cost were not the final discriminators of the selected configuration. In the final analysis, the configuration that was selected was the one that best satisfied the requirements within the constraint of retaining major F/A-18A configuration characteristics. The F/A-18E/F Program - The F/A-18E/F program, which has its origins in the Hornet 2000 program, was awarded to McDonnell Douglas on May 12, The cost of this program for the development phase was $5.803 billion in 1992 dollars. This cost number can be regarded as another constraint on the design. 5 American Institute of Aeronautics and Astronautics

118 The F/A-18E/F rolled out on September 19, 1995 and its first flight was November 29, The aircraft as it appeared at roll-out is shown in Figure 7. Ten aircraft were built to support the flight and ground test programs, seven flight test articles and three ground test articles. The flight test program began at Naval Air Warfare Center Patuxent River, Maryland on February 14, 1996 and is ongoing. However, it is estimated that the EMD portion of the program is now 90 percent complete. As of January 31, ,463 flights representing 2,239.4 flight hours, had been flown. GP cvs Figure 7. F/A-18 Super Hornet as it Appeared at the Roll-out Ceremony While the Hornet 2000 study defined the basic shape and size of the E/F, the details of the design still were to be worked out. Basic Changes - The primary changes developed during the study and the subsequent refinements are summarized here: 1) The area of the wing was increased by 25% to 500 square feet. This change was made to increase the range and payload of the aircraft. 2) A snag in the leading edge of the wing was incorporated. This design feature was part of the original F/A-18A design but was removed due to excessive loads on the leading edge flaps. It was reintroduced here to improve carrier landing handling qualities. 3) The LEX was enlarged and reshaped for better high angle of attack performance. Initially the LEX was basically an enlargement of the LEX used on the C/D aircraft. However, during wind tunnel testing the highangle-of-attack characteristics of the E/F aircraft with that LEX were not as good as those of the C/D aircraft. The new LEX shape restored the excellent high-angleof-attack characteristics that were pioneered on the F/A- 18A aircraft. 4) The wing thickness-to-chord (t/c) ratio was increased. The C/D aircraft has a t/c of 5 percent at the wing root and a linear reduction from there to 3.5 percent at the wing fold. It is constant, 3.5 percent, from the fold to the tip. The E/F has a t/c at the wing root of 6.2 percent, tapering to 5.5 percent at the wing fold and further tapering to 4.3 percent at the wing tip. The increased t/c provides an increase in torsional stiffness with no increase in structural weight. It also allowed increased fuel carriage in the wing. However, the penalty is an increase in supersonic drag. The increase in torsional stiffness completely eliminates limit cycle oscillations when the aircraft is carrying external stores as has been verified by the flight test program. 5) A third wing station was added. This significantly enhanced self escort capability and gave the aircraft additional load carrying capability of 2,300 pounds. These new wing stations can be used for either air-to-air or air-to-ground weapons. 6) The inlets were enlarged for the increased airflow required by the F-414 engines and reshaped for improved radar signature. This reshaped inlet is clearly visible in Figure 8. GP cvs Figure 8. F/A-18E/F Super Hornet Reshaped Engine Inlet There are additional changes below the skin. These include substantially new structure, new mechanical systems, and modified cockpit displays. The avionics, however, are ninety percent common between the two aircraft. The reasons behind these design changes can be related to the design requirements described in the next section. Description of the Design Process Integrated Product Development (IPD) - During the 1980s McDonnell Douglas ran several pilot programs to test what was then an innovative concept for aircraft design called Integrated Product Development and this process played a significant role in the design of the F/A-18E/F. IPD is the process of defining, designing, developing, producing, and supporting a product, using 6 American Institute of Aeronautics and Astronautics

119 a multidiscipline team approach. Note that the individuals on the team need not be multidiscipline but rather that the team has the required disciplines to perform its job. IPD, also known as concurrent engineering, pertains to the concept, analysis, and design stages of a product and provides the basis for bringing the optimum new product or product version to production in the shortest time. The word optimum as used here may not imply the same thing as one would obtain from a formal mathematical process. IPD encompasses the product life-cycle from initial concept through production and support. IPD also includes Integrated Product Definition plus product upgrades and process improvement for the life of the product. Integrated Product Definition is a subset of Integrated Product Development. IPD requires a shift from serial to concurrent process structures. Traditionally, each discipline completed its tasks and passed the results on to the next discipline resulting in a sequential, or serialized, development process which generated rework because the delivered item did not fulfill the down stream customer s requirements, was incomplete, or was changed after release. Several iterations may be required to get the product delivered, corrected, and completed. The processes involved in the definition of a product have serial tasks. The IPD process strives to take the serial processes and perform as many of them concurrently as possible. Concurrent performance of sequential tasks requires redesign of those tasks to accommodate the new processes. The IPD approach to product development has six definition phases that are shown in Figure 9. The first four phases are referred to as configuration synthesis and the last two are referred to as product/process High Level Requirements Definition Initial Concepts Configuration Baselines Conceptual Layout Assembly Layout Build/Buy/Support Packages Configuration Synthesis Product/Process Development Hornet 2000 and Pre EMD EMD GP cvs Figure 9. The Six Phases of Integrated Product Development development. At the end of configuration synthesis a conceptual layout of the aircraft is available and at the end of the product development phase, the build to / buy to packages are defined. For the F/A-18E/F, the Hornet 2000 study corresponds to the configuration synthesis portion of the IPD process. The six phases of product definition are executed during the DoD Acquisition Phases as shown in Figure 10. Each acquisition phase will satisfy certain milestone requirements before contracts are let for subsequent phases. Configuration synthesis, consisting of high level requirements, initial concepts, and configuration baseline definition phases, is executed during the concept exploration and development acquisition phase. The conceptual layout definition phase of configuration synthesis will occur during the Demonstration and Validation (DEM/VAL) acquisition phase. The assembly layout and build-to and support-to-package definition phases, for product and process development, are accomplished during the EMD acquisition phase. Phase 0 Concept Exploration High Level Reqs Initial Concepts Configuration Baseline Phase 0 Dem/Val IPD Phases Conceptual Layouts Program Phases Assembly Layout Phase 2 Engineering and Manufacturing Development Phase Build-To, Buy-To, Support-To Pre-Production Build Build Evaluation/ Production Phases Initial Flight Phase 3 Production Design Mods Low Rate GP cvs Figure 10. IPD Phases Related to the Major DoD Acquisition Phases The F/A-18E/F program hierarchical team structure followed the Work Breakdown Structure (WBS), segmenting the work into discrete elements for estimating and budget allocation, tracking, and performance as shown in Figure 11. Budgets were allocated to each product center and team, making it easier for the team leader to manage the assigned work and maintain control of budget and schedule. Each level could then be assigned the responsibility, authority, and accountability for their product. The E/F program was managed under the Cost Schedule Control System or C/SCS. This system works with the WBS defined above along with a detailed schedule and cost for each task. Metrics in the form of a Cost Performance Index (CPI) and a Schedule Performance Index (SPI) are two of the tools that were 7 American Institute of Aeronautics and Astronautics

120 WBS/Product Team Level Level I Level II Airframe Structures Air Vehicle Level III Propulsion Secondary Power Level IV System Test and Evaluation Hydraulic Weapon System Avionics Flight Control System Engineering/ Project Management Technology Fuel System Wing Forward Fuselage Horizontal Tail Vertical Tail Level V Inner Wing Outer Wing LE Devices Level VI Product Teams Align With WBS Integrated Logistics Support Armament/ Weapon Delivery GP cvs Figure 11. Work Breakdown Structure as Implemented on the F/A-18E/F used to ensure that the E/F Program remained on schedule and within budget. These two indices provide the following information. The CPI is a measure of the work accomplished versus what it cost to accomplish it. This is an indication of the cost efficiency with which work has been accomplished. The SPI is a measure of the work accomplished versus what was scheduled to be accomplished. This is a measure of the schedule efficiency with which the work has been accomplished. These indices, along, with others were applied to the tasks defined through the WBS. Results were reported to the program managers so that they always knew where they stood relative to cost and schedule. It should be noted that the E/F program has basically remained on cost and on schedule since contract award in Design Requirements - While the F/A-18C/D has performed well and demonstrated that the concept of a multi-mission aircraft is valid, usage also showed several areas where the aircraft could be improved. During the advanced design process, a number of requirements were investigated using standard trade studies and a final set of requirements was formulated and an enlarged aircraft that met these requirements was defined. These requirements were formulated relative to the C/D aircraft. In addition to the requirements defined below, if a requirement were not specifically identified, it was implicitly assumed that the E/F would be as good as or better than the C/D aircraft. These requirements covered five areas where increased capability was desired. These were: 1) Increased Bring Back - The maximum weight of ordnance and fuel with which the aircraft can land on the carrier has been increased from 5,500 lb to 9,000 lb. 2) Increased Payload - The aircraft store stations have been increased from 9 to 11 and can be used for either air-to-air or air-to-ground weapons. 3) Increased Range - The maximum range of the aircraft has been extended up to 40 percent depending on the mission. 4) Increased Survivability - The ability to avoid damage from hostile forces was improved by up to 8 times depending on the threat. 5) Growth - Space for new hardware as well as electrical power and cooling capability have been increased by up to 65 percent. These requirements were quantified and in effect became constraints that the design had to satisfy. In addition to the requirements described above a set of Technical Performance Measurements (TPMs) were defined which were allocated as appropriate to the IPD teams and were tracked for the aircraft. These TPMs were: weight empty, reliability, maintainability, survivability, signature, average unit airframe cost, growth in terms of internal volume, electrical power, and cooling, and built-in test which was tracked as false alarm rate and fault detection and fault isolation. In addition each team had requirements for cost, schedule, and risk. Each of the TPMs was tracked in terms of its current value relative to a design-to value and a specification value. Figure 12 shows this tracking process as a function of time for empty weight. The chart shows that as of May 98 the actual weight was 666 lbs. above the design-to weight. However, this weight was over 384 lbs. below the spec value. Thus, while weight was not being minimized as an objective function, its value was being closely tracked to ensure that its upper limit was not exceeded. In addition the weight was being kept below the spec value in anticipation that changes might be required as a result of EMD testing. Similar tracking was carried out for all of the TPMs. If the strict definition of MDO is used, MDO was not used to design the F/A-18E/F. However a multidiscipline process that produced a design that satisfies all of the constraints was used. As an example, the technology disciplines of aerodynamics, flight control flying qualities, structural loads and dynamics, and materials and structural development were linked 8 American Institute of Aeronautics and Astronautics

121 Pounds (1,000) Good T&E Allowance EMD Margin Design-To...29,514 lb Out of Tolerance Current Status...30,180 lb Variance lb Current Status Basis Design-To...0% Estimated... 2% Calculated... 23% Actual... 75% Total % 29.0 JA S ON D J FMA MJ J A S ON D J FMA MJ J A S ON D J F MA Figure 12. F/A-18E/F Empty Weight GP cvs through a common database and analysis tools as shown in Figure 13. Each of these disciplines is driven by a specific set of requirements and each is responsible for a given set of products that taken together define the airplane. For example, the structural loads and dynamics group is responsible for design loads, the dynamic environment, and aeroelastic stability. In order to accomplish this each discipline must communicate with the other disciplines. One tool used to accomplish this was the use of a common database. Taken as a whole the interactions among these disciplines produce a balanced set of requirements. Requirements Teams Aerodynamics Aero Database Mission Performance Carrier Suit Perform Weapon Separation Requirements AIR Flight Control Flying Qualities Control Laws Structural Loads and Dynamics Loads Database Common Database and Analysis Tools Flying Qual Criteria Control Laws FCC Hardware/ Software AIR Design Loads Dynamic Environment Aeroelastic Stability Requirements Interactions Produce Balanced Requirements AIR Materials and Structural Development Materials Database Design Allowables Composite Allowables PPV/Full Scale Test Requirements GP cvs Figure 13. Airframe Technology Key Products and Requirements The interactions among the disciplines can be viewed from the standpoint of common tools as well as common data. An example of this is shown in Figure 14. In this case a tool referred to as MODSDF which is a six degree-of-freedom simulation code is being used to determine critical design loads. For this tool to work, input is required from several sources. These inputs can be in the form of criteria, such as Mil Specs or data such as mass properties. One of the ingredients is past experience. Detailed Spec Mil Specs Loads WT Tests Criteria MODSDF Load GP cvs Load Aero Coeff's Mass Properties Structural Stiffness Control Laws A/C Aero Propulsion FEMS Aero WT Tests Design Team Input Interface Subroutines Wing, Pylon, etc Critical Load/Structure Criteria Requirements Past Experience Figure 14. Flight Technology Requirements Development An example of how this process can be used to improve the design is shown in Figure 15. In this case the trailing edge flap was used as a maneuver load alleviation device and its effectiveness was determined using the MODSDF code. As the aircraft pulls load factor the trailing edge flap is scheduled down by the flight control system as a function of load factor. The result is a modification of the lift distribution with less lift on the outer panel of the wing and more on the inner panel. This reduces wing bending moment, which results in a reduction in wing weight. This process is an example of a multidisciplinary approach to design that produces a better aircraft than would be possible if each discipline simply worked alone. One final point about the design process needs to be made and that is the importance of the aerodynamic database. Figure 14 shows that two of the drivers for the MODSDF code are the aerodynamic wind tunnel tests and the loads wind tunnel tests. The generation of this data is one of the key ingredients in the design process. During the period from the start of EMD in 1992 to first flight in 1996, approximately 18,000 hours of wind tunnel occupancy time was accumulated with more than half of this being used by aerodynamics. In addition to the MODSDF simulation tool, pilot in the loop simulation is also extremely important and over 9 American Institute of Aeronautics and Astronautics

122 Figure 15. Load Alleviation of Wing-Fold and Wing-Root 1000 hours of pilot in the loop simulation were accumulated by first flight. Both of these simulation tools require a detailed aerodynamic database. Results The F/A-18E/F has completed the majority (90%) of its flight test program and the results to date have been outstanding. The program is on schedule, on cost, and the aircraft is below the specification weight. The aircraft has met all of its requirements and will provide the Navy with an aircraft that will meet its needs well into the 21st century. While these results validate the design process that was used for the F/A-18E/F aircraft, it is always possible to improve. What follows is a discussion of a series of questions from the session organizers concerning what is needed in the MDO process. This discussion is based on the experience from F/A-18E/F program and other experience of the authors. Barriers, Obstacles, etc. - The major obstacle to MDO is the inability to analytically determine the design variables and their sensitivities. Meaningful design does not occur until the wind tunnel data base has been determined. While Computational Fluid Dynamics (CFD) may ultimately replace the wind tunnel, until this happens the aerodynamic model cannot be coupled with the other disciplines. Organizational barriers can exist. However, the F/A-18E/F program showed that the transition to an IPD organization is possible. Surely, the transition to an MDO based organization is possible once the benefits are demonstrated. Design Problem and Design Goal - The goal is to design an aircraft that satisfies the requirements. An MDO code should aid in making the design feasible as rapidly as possible. Once a feasible design has been found, the next most important thing is to determine the robustness of the design. State of Software Integration Tools - Tools such as database management, simulation, distributed computing, etc. have all contributed to the integration of the design process. The F/A-18E/F uses a common database for aerodynamics, control dynamics, loads, and structures. MDO Simulation for non-linear Loads - The significant challenge here is the generation of the nonlinear aerodynamic database. Once this data base is generated, the simulation and the control law design can proceed. Once these elements are in place, loads calculations can proceed. Barriers to the Use of Disciplinary Analysis in MDO - While several issues were identified, fidelity of the models is the most significant. It makes no sense to optimize a design based on low fidelity data. Loosely Coupled versus Tightly Coupled Approach - There is no inherent reason why a tightly coupled approach could not be used. However, it is difficult to see how a tightly coupled approach could contain all of the constraints that are present in the loosely coupled one that makes use of all current detailed design tools. A tightly coupled code run by an expert could serve as a check on the more detailed loosely coupled approach. However, this could also create conflict if the two methods don t agree. Use of Sensitivity Derivatives - The use of sensitivity derivatives will become wide spread only after the design community becomes familiar with them. At present the concept of dollars-per-pound is well under stood by all designers but it is not clear that all sensitivity derivatives in general are in this category. On the other hand, a trade study where two variables are compared directly can usually be understood by anyone. Automatic Differentiation - The trend in industry is toward off-the-shelf software when possible. Extending this to automatic differentiation might imply that the software vendors should assume the lead here. Single Most Important Obstacle to MDO - The aerodynamic model matures first and the other models depend on this one. An accurate aerodynamic model is 10 American Institute of Aeronautics and Astronautics

123 based on wind tunnel data that may not produce the sensitivity derivatives needed for MDO. Use of MDO Based on Decomposition - Since MDO tools as such did not play a major role in the F/A-18E/F design, there is no reason to single out any particular method. However, before any method will be used in a production aircraft design environment, it will have to prove itself. Top MD Development - Rapid CFD for air loads. Summary/Conclusions The design process for a modern high performance aircraft is a complex process that involves the integration of analyses, tests, databases, and finally the people who make the process happen. For the F/A- 18E/F aircraft these ingredients have come together to produce a superior product. While the process did not make use of mathematical optimization in a formal sense, the final product does indeed satisfy all of the design requirements that would be represented in the form of constraints in the MDO process. In fact, since the F/A-18E/F is a multi-role aircraft, the formulation of a single objective function would be difficult if not impossible. The following observations can be made: 1. Formal MDO was not used as part of the F/A-18E/F design process. 2. For a multi-mission aircraft, the formulation of an objective function is difficult if not impossible to define. 3. The aircraft is designed by its requirements. This is another way of saying that the aircraft is designed to meet a set of constraints. 4. The design process involves more than a coupling of mathematical tools. The people who operate these tools are an essential ingredient. 5. The IPD design process contributed to the success of the F/A-18E/F program. 6. The design process is serial in that an aerodynamic database is required to design the flight control system. Both the aerodynamic database and the flight control system are required to define loads. Loads are required to define structure. Flex-to-rigid ratios are defined after the structure is sized. These ratios are used to correct the aerodynamic database. And the whole process is iterated. All of this can be done once the moldline of the aircraft is defined. 7. The aerodynamic database is the key. This database is very non-linear. For the F/A-18E/F, the aerodynamic database was established by wind tunnel testing. In the future CFD may have the capability to generate this database. 8. For a multi-mission aircraft, MDO tools that rapidly generate a feasible design, one that satisfies the requirements, would be valuable. Once the design is feasible, these tools should allow for rapid what if studies. The manufacturer and his customer should make the ultimate decision for what is best to meet the requirements. References 1. Current State of the Art on Multidisciplinary Design Optimization, An AIAA White Paper, Approved by the AIAA Technical Activities Committee, September Sobieszczanski-Sobieski, J. And Haftka, R. T., Multidisciplinary Aerospace Design Optimization: Survey of Recent Developments, AIAA Paper No , January Venkayya, V. B., Introduction: Historical Perspective and Future Directions, published in Structural Optimization: Status and Promise, edited by Manohar P. Kamat, Progress In Astronautics and Aeronautics, published by the AIAA, Yurkovich, R. N., MDO from the Perspective of a Fighter Aircraft Manufacturer, published in Multidisciplinary Aircraft Design, Proceedings of Industry-University Workshop, Virginia Polytechnic Institute and State University, compiled by R. T. Haftka, et. al., pp , May Anon. Hornet for 2000 Final Report, The McDonnell Douglas Corporation MDC Report B0833, 29 February American Institute of Aeronautics and Astronautics

124 AIAA A Summary of Industry MDO Applications and Needs by Joseph P. Giesing The Boeing Company Jean-Francois M. Barthelemy NASA Langley Research Center 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization Sept. 2-4, 1998 St. Louis MO. 1

125 A Summary of Industry MDO Applications and Needs OUTLINE Introduction 10 Invited Papers Synopsis Process Development of MDO Categories (Taxonomy) -Process of Extracting Salient Points from Invited Papers Discussion of Categories - Challenges and Issues - Needs ( in Industry) Conclusions - Satisfying MDO Development Needs - Concluding Remarks 2

126 A Summary of Industry MDO Applications and Needs INTRODUCTION Last AIAA MDO Technical Committee White Paper Technology Push, Providing Benefits of MDO Current White Paper Meant to be a Technology Pull from Industry - Industry Needs in the Area of MDO - Provide MDO Developers Help in Planning and Direction White Paper Process - 10 Invited Papers From Industry - Plus a Summary Paper - Summary Paper to be Reviewed by MDO TC and Invited Authors - 10 Papers Plus Summary Will be Put on MDO TC Web Site 3

127 A Summary of Industry MDO Applications and Needs SYNOPSIS OF 10 INVITED PAPERS Summary Paper Presents Short Synopsis of Each Invited Paper - Basic Design Problem Summarized - Several Highlights of the Main Points f-22 High Fidelity F/A-18 E/F CFD, FEM F-16 Agile Falcon Intermediate Fidelity Fidelity Level Space Lrg A/C Telescope Rotocraft GM Auto GE Engine Frontier Increasing Difficulty BWB Conceptual Design Level of MDO Trade Studies Limited Optimization/Iteration 4 Full MDO

128 High Fidelity CFD, FEM f-2 Intermediate Fidelity Conceptual Design f-22 High Fidelity CFD, FEM F-16 Agile Falcon F/A-18 E/F Space Lrg A/C Telescope Rotocraft GE Engine Intermediate Fidelity Fidelity Level GM Auto Increasing Difficulty Frontier BWB Conceptual Design Trade Studies Level of MDO Limited Optimization/Iteration Full MDO

129 A Summary of Industry MDO Applications and Needs DEVELOPMENT OF CATEGORIES Questions Asked by an Industrial Designer 1) What are my design objectives and critical constraints 2) What are my disciplinary analysis capabilities/limitations/automation level 3) How do I get critical high fidelity elements into my design in an efficient manner? 4) What design process steps are needed to meet my design objective most efficiently and to know that I have reached my objectives and satisfied my constraints? 5) What MDO or design formulation do I need or what formulations are available to me? 6) What kind of approximation analyses are required? 7) How do I overcome Optimization problems (scaling, smoothness, robustness, effic.)? 8) How do I feed data among disciplinary analyses and the MDO process? 9) How do I overcome computing and data handling issues 10) What is the easiest way to visualize my design space? 11) How robust is my design and how do I check it? 12) Are there commercial systems that can effectively help me? 13) How do I make it all happen at my plant? 5

130 A Summary of Industry MDO Applications and Needs FINAL CATEGORIES (MDO TAXONOMY) MDO Elements Design Formulations &Solutions Design Problem Objectives Design Problem Decomposition,Organization Optimization Procedures and Issues Information Management & Processing MDO Framework and Architecture Data Bases and Data Flow & Standards Computing Requirements Design Space Visualization Analysis Capabilities & Approximations Breadth vs.. Depth Requirements Effective Incl. of High Fidelity Analyses/Test Approximation & Correction Processes Parametric Geometric Modeling Analysis and Sensitivity Capability Management & Cultural Implementation Organizational Structure MDO Operation in IPD Teams Acceptance, Validation,Cost &, Benefits Training 6

131 A Summary of Industry MDO Applications and Needs PROCESS OF EXTRACTING SALIENT POINTS FROM INVITED PAPERS AND PLACING THEM INTO THE MDO ELEMENT CATEGORIES Invited Papers Design Formulations (1) Design Prob. Obj. (2) Decomp., Organiz. (3) Opt. Proc. & Issues One Liner Salient Points One Liner Salient Points One Liner Salient Points Analysis & Approx. (4) Breadth/Depth. (5) Approximations. (6) High Fidelity (7) Parametric Models (8) Analysis/Sensit. One Liner Salient Points One Liner Salient Points Information Mngt. (9) MDO Frameworks (10) Data Bases Stds. (11) Computing Req. (12) Des. Spc. Visual.. Management & Culture (13) Organization (14) IPD Teams & MDO (15) Acceptance & Benefits (16) Training. One Liner Salient Points MDO ELEMENTS (TAXONOMY) 7

132 A Summary of Industry MDO Applications and Needs DISCUSSION OF CATEGORIES (1) Design Problem Statement Distribution of Design Problems for 10 Papers Space F-16 Telescope Agile Falcon f-22 Lrg A/C BWB F/A-18 E/F GE Engine GM Auto Rotocraft Frontier Feasible Improved Optimal Pareto Industry Design Objective Priority Order - Feasible and Viable Design - Robust Design - Improved Design - Optimal Design 8

133 A Summary of Industry MDO Applications and Needs Challenges and Issues Needs (1) Design Problem Statement Each Design Problem Unique Design Problem May Not be Known A-Priori Flexible Framework - Reconfigurable to Multiple User Needs Continued Development of Objective Functions for Industrial Applications 9

134 A Summary of Industry MDO Applications and Needs SIMPLIFIED COST RELATED OBJECTIVE FUNCTION FOR MDO Comparison of Three Objective Functions; Area DOC, MTOGW, Weight DOC DOC/DOCo (or F/Fo) Area DOC MTOGW Wt. DOC 0 Const OEW Fuel Weight Payload Weight Wetted Area Engine Size A B C D E F DOC/DOCo =A +B OEWA/OEWAo + C FWT/FWTo + D PLWT/PLWTo+ E Swt/Swto +F T/To 10

135 A Summary of Industry MDO Applications and Needs (2) Design Problem Decomposition and Organization Challenges and Issues Sophisticated Decomposition Processes (e.g.. CO, CSSO ) - Not Fully Mature - Not Fully Understood by Industry High Fidelity Analysis Processes Difficult or Impossible to Include in MDO Needs - Non Automated & Very Long Computing Time Loosely Coupled Systems - Include Legacy Codes - Global-Local (Multi-Level) Decomposition - Easy to Understand Processes Decomposition Processes that Converge to High Fidelity Results Without High Fidelity Analyses being Called Directly by Optimizer - Update Processes - Approximation Processes - Other Decomposition Processes Tailored & Adapted to Needs and Deficiencies of Analysis Processes 11

136 A Summary of Industry MDO Applications and Needs (2) Design Problem Decomposition and Organization Notional Update Process High Fidelity Analysis Update Approximation Surface or Intermed. Level Analysis Update #1 Update #2 OBJECTIVE FUNCTION F Update #3 Trust Region ITERATION 12

137 A Summary of Industry MDO Applications and Needs Challenges and Issues (3) Optimization Procedures and Issues Lack of Experience in Optimization in Industry Optimization Robustness - Smoothness Requirements - Scaling, Convergence Issues Efficiency Continuous, Discrete & Hybrid Optimization Local Minima Needs Self-Smoothing or Noise Insensitive Opt. Processes Self-Scaling Opt. Processes Robust Processes for Finding Global Minimum Rapid/Efficient Optimization Processes 13

138 A Summary of Industry MDO Applications and Needs Challenges and Issues (4) Breadth and Depth Requirements Identify and Include All Critical Constraints to Avoid Academic Design Identify and Include All Critical Physical Mechanisms to take Advantage of Available Design Opportunities Fidelity Requirements for Each Discipline not Known/Quantified Needs Process for IPD Team to Identify All Critical Aspects of Design as it Progresses Process for Identifying the Fidelity Requirements of Various Disciplines - Possible Use of MDO Process Itself (Sensitivities) to Est. Req. Process for Identifying Critical Physical Mechanisms 14

139 A Summary of Industry MDO Applications and Needs Effect of Objectives and Constraints on Optimal Design A Minimum induced drag at fixed weight. B Minimum total drag at fixed weight. C Minimum total drag at fixed weight with low speed lift constraints. D Minimum total drag, fixed weight, low speed lift constraints, and fuel inertia relief. E Minimum total drag, fixed weight, low speed lift constraints, fuel inertia relief, and static aeroelasticity. 15

140 A Summary of Industry MDO Applications and Needs (5) Effective Inclusion of High Fidelity Analyses/Test Challenges and Issues High Fidelity Process Deficient in - Automation ( Many Manual Steps) - Robustness (Model has to be Iterated and Re-worked) - Efficiency ( Requires Many Hours on the Computer) Needs Advances in Disciplinary State-of-Art - Robustness - Efficiency Advances in Disciplinary Automation and Parametric Modeling Advances in Decomposition or Approximations to Make Up for Deficiencies in High Fidelity Analyses 16

141 A Summary of Industry MDO Applications and Needs TLNS3D N-S, C = , α = 10.0 Ltot Woodward Linear, C = , α = 11.5 Ltot TLNS3D N-S, C = , α = 4.5 Ltot Woodward Linear, C = , α = 4.7 Ltot Nonlinear (Reduced Bending Moment) Nonlinear (Increased Bending Moment) C L * c/c Linear C L * c/c Linear Semispan Fraction Semispan Fraction 17

142 A Summary of Industry MDO Applications and Needs (6) Approximation and Correction Processes Challenges and Issues Generating Data for Response Surfaces (Curse of Dimensionality) Isolating Physical Mechanisms Intermediate Level Analyses Not Simulating All Critical Physical Mechanisms Needs Response Surface and Other Generic Approximation Software Addition of Missing Critical Mechanisms in Intermediate Level Analyses Advanced Correction Procedures for Intermediate Level Analyses - Separate Correction of Each Physical Mechanism - Using Intermediate Analyses as Interpolation/Extrapolation Process Reduced Order Approximations for Use in Optimization - Parameter Identification 18

143 A Summary of Industry MDO Applications and Needs (6) Approximation and Correction Processes High Fidelity Analysis or Sub-Optimiz Generic Approximations -Response Surf. -Neural Nets -Taylor Series Optimizer High Fidelity Analysis or Sub-Optimiz Correction Process Intermediate Fidelity Analysis - Phy. Mech. A - Phy. Mech. B - Phy. Mech. C Optimizer High Fidelity Analysis or Sub-Optimiz Reduced Order Representations Rational Function Approx. A=Σ a i /(S + b i ) Optimizer 19

144 A Summary of Industry MDO Applications and Needs (6) Approximation and Correction Processes Correction Process Subsonic, High α Case (M=0.5, AOA=15 o ) Sectional Lift Distribution Aerodynamic Span Loading on Deformed HSCT Configuration at 15 Degrees Angle of Attack Correction Procedure Linear Direct CFD Solution Span Station (Inches) 20

145 A Summary of Industry MDO Applications and Needs Challenges and Issues (7) Parametric Geometric Modeling Large Common Models Expensive Existing CAD Software Not Robust Enough for Topology Optimization Morphing (Rubberizing) Does Not Always Produce Adequate Layout Needs Automatic Modeling Tool Kit (e.g.. CFD Meshes, Finite Element Models) Parametric Layout Techniques for Changing Topology Grid-Mesh Mapping (e.g.. aerodynamic forces on structural nodes and surface deflection of FEM on CFD mesh) Software for Robust Processes (Commercial or Otherwise) 21

146 A Summary of Industry MDO Applications and Needs (7) Parametric Geometric Modeling Parametric Model with Topological Changes Can Not be Rubberized c1 c1 c2 c2 c3 c3 22

147 A Summary of Industry MDO Applications and Needs Challenges and Issues Needs (8) Analysis and Sensitivity Capability Lack of Automation of High Fidelity Codes and Sub-Optimization Processes Lack of Cost Models for Use in MDO Checking of Analysis Model and Data At Each Step Large Computer Run Times for High Fidelity Codes Robust Automated Disciplinary Analyses Modules (Preferably Commercial) - CFD, FEM, Nonlinear Loads, Aeroservoelastic - Global/Local Structural Sizing - Efficient Aerodynamic Optimization - Other Interactive Analysis Data Monitoring and Checking Tools Simplified and Detailed Manufacturing and Maintenance Cost and Constraint Models 23

148 A Summary of Industry MDO Applications and Needs (9) MDO Frameworks and Architecture Challenges and Issues Commercial OTS MDO Frameworks are Not Yet Industrial Strength - Problem and Model Size Limited - Distributed Computing Not Robust Needs Commercial MDO Framework that is: - Mature, Robust, Efficient, and Industrial Strength - Flexible and User Friendly - Able to Include Legacy Codes 24

149 A Summary of Industry MDO Applications and Needs (10) Data Bases, Data Flow and Standards Challenges and Issues Needs No Universal Standard for Data Hugh Amounts of Data are Used in Industrial Design Multiple Platforms and Locations Need to Interact with Design Data Standardized, Industrial Strength Data Base - Handle Large Amounts of Data (terabites) - Multisite and Heterogeneous Accessible ( Internet?) - Efficient and User Friendly 25

150 A Summary of Industry MDO Applications and Needs Challenges and Issues Needs (11) Computing Requirements High Fidelity Analyses Require Massive Computing Power - CFD Single Analysis 10 hrs on C-90 Type Super Computer - CFD Design (20 design variables) 300 hrs C-90 - Solution 200 (structural sizing optimization) 50 hours for 9 Iterations on a High End Work Station - F-22 Used 10 Terabites of Storage for Structural Design Improved Networking Systems for Work Stations and Other Computers New Methods that Work Efficiently on Massively Parallized Computers (e.g. CFD, Structural Sizing Optimization) Generic Algorithms Designed Especially for Massively Parallized Computers (e.g. Matrix Manipulation, Eiganvalue Analysis) 26

151 A Summary of Industry MDO Applications and Needs Challenges and Issues (12) Design Space Visualization Can Not Physically Visualize More than 3-Dimensions Designers May Be More Interested in Seeing the Design Space Than Finding the Optimum Design Point - e.g. How Flat is Design Space? IPD Team Needs to Understand the Design Space to Make Design Decisions Needs Creative Design Space Depiction Techniques Needed - Visualize Multi-Dimensional Design Space Directly - Generate a New Breed of Data that Will Impart the Needed Design Space Information Without Direct Multi-Dimensional Representations *Reduced Dimensions (Modal or Related Approach) 27

152 A Summary of Industry MDO Applications and Needs Challenges and Issues (13) Organizational Structure Who is In Charge of MDO? Currently Advanced Design Group Responsible for Own Technology - Small Interaction with Discipline Groups Each Discipline Responsible for Methods and Data Integrity/Quality - How Do These Groups Interact with MDO? - How Do Disciplines Buy In to the MDO Process & Results? MDO Solutions Tend to Compromise Performance of Each Discipline for the Benefit of the Whole System Needs Industry Needs an MDO Team - One Part of Team Provides Coordination (Advanced Design?) - Each Discipline Maintains Technical Autonomy - Each Discipline Is Part of and Buy s In to the Process - Each Discipline Maintains Responsibility for Integrity and Quality of Data and Technology - All Disciplines and MDO Coordination Agree on Interfaces 28

153 A Summary of Industry MDO Applications and Needs (14) MDO Operation in IPD Teams Challenges and Issues Not All Design Issues are Incorporated into MDO IPD Team Unfamiliar with MDO Tool and How to Interact with It Defining MDO Problem is Evolutionary as Design Progresses Needs Understanding the MDO Process and Accepting It As a Tool Experience and Training of IPD Teams - Interaction and Direction of MDO Process - Setting and Changing Constraints and Groundrules for MDO Process - Interpreting Results 29

154 A Summary of Industry MDO Applications and Needs (14) MDO Operation in IPD Teams IPD Direction initial design CASES mission analysis CWEP validate weights, advanced design WingMOD preliminary loads, sizing weights, compressibility drag, max lift data reasonable design? yes WingMOD no check design, modify analyses or constraints recalibrate buffet constraint CASES prospective design, cruise spanload acceptable aerodynamics? yes FLO22, CFL3D IPD Team validate Members performance - Structures Finite Element - Aerodynamics detailed sizing and loads - Manufacturing - Stability and Control 30 no Final Design 3 months

155 A Summary of Industry MDO Applications and Needs (15) Acceptance, Cost and Benefits and (16)Training Challenges and Issues Lack of Understanding of MDO and Its Place in Industry Environment Lack of Training and Education in MDO Techniques Cost of Developing a New MDO System Lack of Documented Practical Benefits Fear of Loosing Tried and True Processes Needs Series of Full Industrial Validation Test Cases - Benefit Over Current Practices - Industrial Strength Validation Cases, Preferably on Actual Vehicle MDO Process Plan and Cost 31

156 A Summary of Industry MDO Applications and Needs SATISFYING MDO DEVELOPMENT NEEDS Technology Development Community Industry Government Labs. University Commercial Software Technical Challenges and Needs Technology Development & Verification Technology Transfer & Applications Technology Commercialization University Gov. Labs Com. Soft. Industry TEAM Industrial Strength MDO Financial Leveraging Financial Resources Commer. Software Invest. University Government Contracts & R&T Base Industry IR&D 32

157 A Summary of Industry MDO Applications and Needs CONCLUSIONS Broad Cross-Section of MDO Applications and Experience in Industry Represented Wide Range of Design Objectives Encountered Modified Taxonomy of MDO Elements Suggested Practical MDO Challenges and Issues Delineated Industry MDO Development Needs Presented Teaming of University, Government Labs, Commercial Software Developers, and Industry Suggested - Produce Industrial Strength MDO Processes for the Future 33

158 A SUMMARY OF INDUSTRY MDO APPLICATIONS AND NEEDS Joseph P. Giesing, The Boeing Company, Long Beach, CA 1 Jean-François M. Barthelemy, NASA/Langley Research Center, VA 2 Abstract The AIAA MDO Technical Committee has sponsored a series of 10 invited papers dealing with industry (and related) design processes, experiences, and needs. This paper presents a summary of these papers with emphasis on the needs of industry in the area of MDO. Together the 10 invited papers and this summary paper comprise an AIAA MDO Technical Committee White Paper on this subject. This summary paper contains; 1) a short synopsis of each paper and the industrial design it describes, 2) a sorting of all of the salient points of each of the papers into MDO categories plus a discussion of each category, and 3), a summary of industrial needs distilled from the papers. It is hoped that this summary paper will provide a technology pull to the MDO technology development community by presenting the industrial viewpoint on design and by reflecting industrial MDO priorities and needs. 1. Introduction Upon the establishment of the Multidisciplinary Design Optimization Technical Committee (MDO/TC), a White Paper was prepared to assess the State of the Art in the MDO technical area 1. Jointly written by founding members of the TC, the paper provided a brief history of aerospace design and made the case for integrating all the disciplines in the design process. The White Paper then reviewed recent developments, addressing in turn the human interface aspects of design, its computational aspects and its optimization aspects. The discussion continued with an approach to transitioning the design environment to Concurrent Engineering and a discussion of how MDO can support that transition. The White Paper finally concluded by stating that MDO provides a human-centered environment 1) for the design of complex systems, where conflicting technical and economic requirements must be rationally balanced, 2) that compresses the design cycle by enabling a concurrent engineering process where all the disciplines are considered early in the design process, while there remains much design freedom and key trades can be effected for an overall system optimum, 3) that is adaptive as various analysis/simulation capabilities can be inserted as the design progresses and the team of designers tailor their tool to the need of the moment, and 4) that contains a number of generic tools that permit the integration, of the various analysis capabilities, together with their sensitivity analyses and that supports a number of decision-making problem formulations. Since the publication of the first White Paper, much work has been devoted to MDO as attested in the proceedings of the successive AIAA MA&O Symposia, for example. A number of detailed surveys have been written (see Sobieski and Haftka 2, for example), updating the research community to the latest developments in MDO in general, and in some subareas of MDO as well. The MDO/TC is taking the occasion of the current (7th) MA&O symposium to add to the constant dialogue between MDO users and MDO researchers. It invited designers from various organizations to contribute a technical paper describing a recent design exercise in which they have been involved and to take that opportunity to offer some insight into their application of formal MDO methodology to their problem. In particular, the users were asked to address whether they had used MDO, whether it helped or did not help, and what developments they needed to improve their process. This paper is a draft synopsis of the lessons gleaned from the various contributions. The paper will be reviewed and edited by the MDO/TC and it will be posted on the Web, together with the individual contributions, at the same site as the 1991 White Paper. 1 Boeing Technical Fellow, Associate Fellow, AIAA 2 Manager, Aircraft Morphing, Airframe System Program Office, Senior Member, AIAA. Copyright 1998 by the American Institute of Aeronautics and Astronautics, Inc. No copyright is asserted in the United States under Title 17, U.S. Code. The U.S. Government has a royalty-free license to exercise all rights under the copyright claimed herein for Government purposes. All other rights are reserved by the copyright owner. 1

159 It is hoped that this paper will provide some insight into what are the MDO developments most critical to MDO users (industry, or others). Because this paper is directly based on the inputs of only ten different design exercises, it cannot be presented as a consensus opinion on what MDO should be for the engineering design process however it is felt that a very good representation and cross-section of industrial applications, challenges and needs are given and that the conclusions of the data contained here will be helpful to the MDO technology development community for prioritizing future MDO development. For the purpose of this paper, we use the following definition for MDO: A methodology for the design of complex engineering systems and subsystems that coherently exploits the synergism of mutually interacting phenomena. One can argue that ever since systems have been designed, multiple conflicting requirements have had to be taken into account and therefore multidisciplinary process have always been used. This point is not debated here, however the key word in the definition is methodology. MDO provides a collection of tools and methods that permit the trade-off between different disciplines involved in the design process. MDO is not design but enables it. Ideally the MDO-based environment of the future will be centered on the IPD design team. To facilitate its use the MDO process will be interactive and will permit the design team to formulate its design problem in real time as the design issues become clear. Specifically, the MDO process should be flexible enough so that the problem formulation, applied constraints, and the level of simulation can all be specified by the design team. To facilitate technical communication, the design team may wish to create and update a single parametric model of the system being designed and reshaped it (automatically) in the course of the design. It could be used to automatically generate consistent computational models for simultaneous use in various disciplines. An environment that offers visibility to the process, permitting the team to monitor progress or track changes in the problems dependent or independent variables will be beneficial. All along, the process control would remain squarely in the hands of the design team. The environment could be distributed to reflect the nature of today s design projects. Specifically design exercises can be distributed over many different groups, many sites, often even in different countries. In addition to providing a challenge to the management of the process, its distribution also may provide additional resources as it could open up a network of computing nodes that could be harnessed to carry out the process. The ideal environment would automatically route the computational process to the most suitable/available resources. Since very large amounts of data will be generated, they could be stored in a distributed fashion as well for convenience and efficiency, but the environment would make the data readily available to all design team members in a transparent fashion. The paper is written from the perspective of the user of MDO, and begins with a brief summary of the papers contributed to the sessions by the designer teams. Then, the challenges and issues addressed by the different papers are identified and categorized, forming a taxonomy of MDO, as perceived by the designers. The paper concludes with an assessment of industry needs and some recommendations for MDO development. Note that Sobieski made an earlier attempt at developing a taxonomy for MDO 3 ; his efforts could be seen as a Technology Push approach at defining the needs from MDO, being developed from an distinguished experience in government research. The new taxonomy offered in this paper is coming largely from the other Application Pull perspective. It is expected that the combination of both perspectives will prove thought provoking and helpful to the planning and development of MDO technology. 2. MDO Applications, A Synopsis A short synopsis of each paper is presented in this section. The basic design problem encountered in each paper is summarized along with highlights of a few of the main points made. Figure 2-1 gives a general overview of where each paper lies with reference to fidelity level and MDO level. MDO level is loosely defined as follows. Trade studies indicate that point designs were generated and graded relative to each other without formal optimization. Limited Optimizations/Iterations indicates a disciplinary sub-optimization or one with limited disciplinary interaction. Full MDO indicates vehicle level optimization with most critical disciplines involved. 2

160 f-22 High Fidelity F/A-18 E/F CFD, FEM F-16 Agile Falcon Intermediate Fidelity Fidelity Level Space Lrg A/C Telescope Rotocraft GM Auto GE Engine Frontier Increasing Difficulty BWB Conceptual Design Level of MDO Trade Studies Limited Optimization/Iteration Full MDO Figure 2-1: Distribution of Design Process Fidelity and Level of MDO The Challenge and Promise of Blended Wing Body Optimization Wakayama and Kroo 4 describe the application of the WingMOD MDO process to the minimization of the BWB Take-Off-Gross-Weight. The process is fully multidisciplinary and includes design variables for planform shape/size, mission, aerodynamic, structural sizing/topology, fuel/payload, and trim schedule (134 in all). WingMOD uses a close-coupled approach using intermediate fidelity disciplinary analyses for high aspect ratio wing aircraft. An optimization framework (Genie) makes calls to all of the analysis routines, using finite differences to compute sensitivities. The aerodynamic analyses include the vortex lattice method and quasi twodimensional compressibility corrections. The structural sizing and constraints are based on aeroelastic loads and deflection analysis, simplified buckling, and stress analysis of simple beams. The weight is based on the structural analysis corrected by some statistical data. A wide breadth of practical constraints are considered (705 in all) along with 20 design flight conditions that cover most of the critical design considerations. One of the main points of the paper is that all critical constraints and disciplines (breadth) must be included to produce a realistic/practical configuration and that all critical physical mechanisms should be included, to some level of fidelity (depth), to reach the highest potential benefit of integrated design. The main need of the process is inclusion of CFD (mainly for propulsion/airframe integration) into the process without rendering it intractable. Indeed, this close-coupled system makes many (thousands) of calls to the analysis routines. Issues in Industrial Multidisciplinary Optimization Bennett et al 5 describes the application of the GM IVDA (Integrated Vehicle Design Analysis) system to the maximization of automobile fuel efficiency. The system is composed of both commercial (ODYSSEY, NASTRAN, LPM, DYNA3D, CAL3D, ADAMS, ) and GM codes (aerodynamics, solar load, fuel economy, and others). The user can configure the process within IVDA to produce an optimization sequence which was done for several examples in an ad hoc manner. The examples described included one global design variable (vehicle length), and suboptimizations are performed in the local disciplines (structural member cross-section design). The local designs and analyses feed a results database which is then fit with approximations. For instance the aerodynamic drag data was a neural net fit to test data. The optimizer then uses these approximations to re-design the vehicle. The authors make the point that, in an industrial design environment, the design process does not necessarily fit a particular MD algorithm, rather, the implementation needs to be reconfigurable, on the fly. This introduces the idea of a toolbox of MD tools and off-the-shelf specialized tools that can be interfaced automatically, with the provision that... a menu of appropriate actions should be generated to guide the user through the process. 3

161 Boeing Rotorcraft Experience with Rotor Design and Optimization Tarzanin and Young 6 describe an exercise of optimization to reduce helicopter blade hub dynamic forces. The objective function is a weighted sum of hub forces and moments. The optimization process is tightly coupled and uses an analysis simulation system maintained by several disciplines. Two levels of fidelity are available in this simulation; an approximate analysis level that requires 1 minute per function call, and a high fidelity level that requires 30 minutes per call. The authors make the point that the complexity of the detailed analysis led them to fully integrate their high fidelity codes, thereby obviating the need for any decomposition method. Optimization can proceed by interfacing a single optimizer with the integrated high-fidelity analysis. Practical verification of the benefits of this MDO approach was obtained with wind tunnel tests. The design space encountered in this class of problems is characterized by many local minima and the paper describes several techniques for arriving at the global optimum and overcoming non convergence. Some of these techniques involve probing unexplored portions of the design space by: 1) employing multiple starting points, 2) initially employing loose constraints and gradually tightening them down to the required value, 3) allowing the constants in the objective function to take large excursions and then adjust back to the proper value, 4) updating aeroelastic loads at various times during the optimization. The F-22 Structural/Aeroelastic Design Process with MDO Elements Radovcich and Layton 7 describe a process for the detailed structural design of the F-22 aircraft after the configuration has been fixed. The focus of the effort is the minimization of weight while satisfying all of the detailed stress safety margins, flutter margins, and fatigue life requirements. This involves modifying active controls to alleviate loads and includes filtering control laws to eliminate unfavorable interactions resulting in flutter. Design considerations include, detailed part geometry, materials, external loads, elastic-to-rigid ratios, stiffness, mass, and flight control laws. A single high-fidelity air vehicle FEM is a key requirement for the success of this effort. This FEM is used for stress, loads, flutter, allowables, internal loads, and checking of aeroservoelastic affects. This FEM is the main feature in a tri-company coordination effort, and it payed for itself many times over in providing a straightforward process and in facilitating communication. The only restriction on the FEM is that it not overload the Convex 10 terabyte storage capacity. The design process consists of cycling all of the necessary analyses and design steps. Some of the disciplines are iterated several times within the global cycle. In addition, because of 4 differences in discipline cycle time, several disciplines are at different stages, being 1, 2 or even 3 cycles behind the current global cycle. In the time allotted, four global cycles are carried out, however, the inconsistencies between the discipline stages do not seem to affect convergence greatly. The Role of MDO within Aerospace Design and Progress Towards an MDO Capability Through European Collaboration Bartholomew 8 presents three European MDO projects; 1) the GARTEUR regional transport aircraft structural optimization, 2) the EU IMT project where the A3XX transport aircraft direct operating cost (approximation) is minimized and, 3) the ESPRIT Frontier project where a Pareto front is identified for a multiple objective problem, and where trade-offs between the different objectives are identified. In addition to the examples, a discussion of MDO in general and Europe in particular is presented. The MDO process of choice is loosely coupled, and multilevel. At the lower level, it uses a detailed design process normally used by engineers. An integrated software system is needed that has a flexible user interface, provides for checking all along the way, and uses standardized product data formats (STEP). MDO Technology Needs in Aeroelastic Structural Design Hoenlinger et al 9 present explicit answers to the questions posed by the organizers of this session. The highlights of their paper are two tables, and accompanying discussions, that provide a wealth of information on past experience with structural sizing/optimization and expert opinions on what is needed in MDO. The industrial applications range in time from 1985 to the present and cover the ACA, X-31, Ranger 2000, Stealth Demonstrator, and the MDO Aircraft (A3XX). The history of the development of the LAGRANGE aeroelastic structural optimization software is sketched, ending with the decision not to extend this system to the controls discipline as it is thought that a more general architecture is warranted and that it is better to include LAGRANGE itself in a more general architecture (e.g., isight). The existence and application of a rapid parametric FEM model generator for high aspect ratio wings is also discussed. Like several other contributors, the authors points at the fact that there are serious organizational aspects in introducing MDO in an industrial environment. (..no coordinating position for MDO is present in typical industrial hierarchies. ) A Collaborative Optimization Environment for Turbine Engine Development Rohl et al 10 describe the development of an MDO process for the design a jet engine rotor disc; they show that a significant part of the challenge to performing MDO is to

162 be able to do MDA (Multidisciplinary Design Analysis). The first order of business is feasibility (fatigue life and distortion tolerance). The second consideration is minimum weight, both for the finished part and for the billet (cost). The components of the process are: mechanical design, thermal cycling/loads, forging optimization, heat treatment optimization, machining simulation and life prediction. The mechanical design to meet the mission requires material properties, residual stress, and life prediction which are not known ahead of time and are determined in the forging, heat treatment, and machining simulations and suboptimizations, and the life prediction analysis. Forging is a minimum billet weight optimization (using DEFORM) with constraints on the forging requirements. Heat treatment has conflicting objectives for its suboptimization; i.e. maximum material properties, with minimum residual stresses and requires very high fidelity meshes. The authors point to the fact that the complex analysis capability resulting from the integration of the individual simulations required is not as smooth as desired, and that large step size finite differences are required to obtain robust derivatives. The MDO process was initially implemented in isight and both the CSSO and CO decompositions, were tried. These proved impractical due to the nature of the problem and the requirement for high fidelity. A modified sequential process is suggested but this work is still in progress. Currently most of the emphasis is on the disciplinary tools and automation of these high-fidelity simulations. Specifically, two tool kits, the Product Modeling Kit (PMTK), and the Discrete Analysis Modeling Kit (DMTK) are being developed under DARPA contract. Multidiscipline Design as Applied to Space Lillie et al 11 describes a systems engineering process for the feasible and affordable design of the NGST (Next Generation Space Telescope). The final product is a baseline design and the associated technology development necessary to implement the design. Five IPD Teams are used to design the telescope; 1) Optical Telescope Assembly (telescope structure), 2) Science Module (instruments), 3) Spacecraft Systems (power, propulsion, vibration and thermal control), 4) Operations Systems (ground systems, data handling, operations), and 5) Systems Engineering (Integration of systems and requirements). Requirements related to targets, observations, aperture, quality, imaging spectral bands, stare time, agility, pointing stability, imaging field of view, coverage, field of regard, lifetime, and cost make this a very challenging design for feasibility. The process is one of multidisciplinary integration. An example is the requirement for minimum contamination of the telescope optics from the propulsion system. The design is presented as a series of mostly discrete decisions, few of the variables used are continuous. 5 Usually a short list of available options exists for each choice. The importance of each of the requirements is classified as; 1) required, or 2) highly desired, or 3) desired, and 4) goal. The design decision is made based on the ability of the option to meet the requirement, the importance of the requirement, and the performance impact of the choice. Currently this TRW team is assembling a full structural, thermal, optical multidisciplinary simulation (not reported in the paper). Their objective is to optimize the design using the simulation. The issues with the simulation involve interfacing various systems together, converting and transmitting data among the three disciplines and developing a common model. Multidisciplinary Design Practices from the F-16 Agile Falcon Love 12 describes the process for determining the best design for a more agile F-16 aircraft at reasonable incremental cost. Best is not formally defined but involves ranking of discrete designs on the basis of maneuverability, controllability, weight, and producibility. The design is carried out in two steps, and the wing planform shape is selected in the first step, its twist and camber distributions in the second. A baseline was available for the new agile design and variations are developed about this baseline. Specifically, wing span, sweep, and area variations are analyzed and tested using 6 discrete design points. No one configuration provided superior performance. A new baseline was derived from the aerodynamic, weight, and system interface studies performed using a qualitative process. Further design refinements/studies are performed about the new baseline which consider variations in basic camber and twist distributions of the wing to enhance agility. Aeroelastic tailoring is used to optimize the new baseline, as well as a wash-in and a wash-out wings (i.e., wings that twist up or down, with increased aerodynamic loads). A ranking table that considered maneuverability, controllability, weight, and producibility was used to select the best of the three cases. The author makes the point that... the approach to achieve integration would probably be the same today (1998) as in The differences in the overall process would be in the tool selection... and the amount of data generated. A Description of the F/A-18 E/F Design and Design Process Young et al 13 describe the re-design process of the F-18 to meet multiple missions not originally intended for the original aircraft. Some of the increased requirements involved: carrier suitability (landing weight), strike mission (payload), fighter mission (range), increased survivability, maneuverability, growth potential, and others. The objective is to reach a feasible design at acceptable cost and a Stop-Light (red, yellow, green)

163 process was used to grade each requirement. Seven discrete configurations are analyzed and graded by an IPD Team. Only two configurations had no red stop signs. Of these two, one had slightly better grading and lower cost than the other and this one is selected. Some of the design changes include: a 25% wing area increase, a snag in the leading edge, an enlarged leading edge extension (LEX), a thickness-to-chord ratio increase, enlarged inlets, and an added third weapons carrying station. The authors put a lot of emphasis on the building of an aerodynamic database made of a combination of CFD results and wind tunnel data which will prove critical to good aeroelastic optimization. This paper also describes the IPD Team function and process, the Cost/Schedule Control System (C/SCS) accounting system, a Technical Performance Measurements (TPM) tracking system, and finally a section answering questions on, barriers to MDO and future needs. 3. Industrial Challenges and Issues Selection of Categories Many of the issues, needs, conclusions and salient points gleaned from the 10 papers are summarized, categorized and discussed here. The categories used here were inspired by a classification of MDO Conceptual Elements (MDO Taxonomy) given by Sobieski 3 but modified to reflect industrial needs, prospectives, and priorities. One such modification is the addition of a general classification dealing with Management and Cultural Implementation issues in the industrial environment. The industrial influence on Sobieski s Taxonomy was derived, in part, by a series of hypothetical questions (Figure 3-1) that an industrial designer might ask before designing an MDO system to solve his particular problem. These questions range from What is my design objective? to How do I make it happen at my plant? Questions Asked by an Industrial Designer 1) What are my design objectives and critical constraints 2) What are my disciplinary analysis capabilities/limitations/automation level 3) How do I get critical high fidelity elements into my design in an efficient manner? 4) What design process steps are needed to meet my design objective most efficiently and to know that I have reached my objectives and satisfied my constraints? 5) What MDO or design formulation do I need or what formulations are available to me? 6) What kind of approximation analyses are required? 7) How do I overcome Optimization problems (scaling, smoothness, robustness, effic.)? 8) How do I feed data among disciplinary analyses and the MDO process? 9) How do I overcome computing and data handling issues 10) What is the easiest way to visualize my design space? 11) How robust is my design and how do I check it? 12) Are there commercial systems that can effectively help me? 13) How do I make it all happen at my plant? Figure 3-1: Concerns of an Industrial Designer Prior to Setting Up an MDO Process The final categories or MDO elements selected for this paper are shown in Figure 3-2. There are four general categories which include design formulation issues (prompted by questions 1, 4, 5, and 7 in Figure 3-1), analysis capabilities (related to questions 2, 3, 6, and 11), information management (see questions 8, 9, 10, and 12) and management and culture constraints (question 13). Each general category contains several sub-categories of its own. 6

164 MDO Elements Design Formulations &Solutions Design Problem Objectives Design Problem Decomposition,Organization Optimization Procedures and Issues Information Management & Processing MDO Framework and Architecture Data Bases and Data Flow & Standards Computing Requirements Design Space Visualization Analysis Capabilities & Approximations Breadth vs.. Depth Requirements Effective Incl. of High Fidelity Analyses/Test Approximation & Correction Processes Parametric Geometric Modeling Analysis and Sensitivity Capability Management & Cultural Implementation Organizational Structure MDO Operation in IPD Teams Acceptance, Validation,Cost &, Benefits Training Figure 3-2: MDO Elements Grouped by Categories (MDO Taxonomy) Each of the salient points from the 10 papers have been summarized into short one-line sentences. An initial is placed at the end of each of these sentences to identify the author from which they came. These points (one-liners) were sorted and placed in the categories given in Figure 3-2. The results of this sorting is given in Appendix I. A legend at the beginning of the Appendix gives the key relating the initials to the paper authors. Discussion of Categories A general discussion of the challenges and issues associated with each of the categories (shown in Figure 3-2) is presented here. The basis of these discussions are the sorted one-line salient points presented in Appendix I. The content of the discussion is mostly taken mostly from the pertinent items listed in each category, however additional interpretations, generalizations and the experience of the current author are also sometimes included. Design Problem Objectives The range of industrial design objectives sampled in the 10 papers is illustrated in Figure 3-3. The scale is an imaginary continuum of problem statements that ranges from making a design satisfy all requirements (i.e., feasible), to finding the optimum design for several objective functions. Intermediate possibilities are improving a feasible design and finding a single-objective optimum. Most of the papers included in this series are lumped in the Feasible and Optimal categories. However, even though many of the design problems are cast as optimization problems it is probably true that the real goal of the effort is an improved design. For example, in the helicopter rotor design problem discussed by Tarzanin et al 6, the optimized design was tested to see if it presented an improvement over earlier designs, not to see if the improvement matched the predicted optimum. Young, Anderson, and Yurkovitch 13 show that another implicit goal of the effort is probably design robustness since point designs can be sensitive to unknown problem parameters and are not always of practical value. Bartholomew 8 discusses a paretooptimization approach; a parameterized series of optimizations carried out to effect trade-offs between different conflicting objectives. The authors describe a situation where, generally, the problem statement is not known a priori. Rather, it is defined in an interactive fashion in the course of the design exercise. As an initial statement is adopted, a particular design emerges that may be lacking in one way or another. At that point, the problem statement is modified to address the shortcomings of the initial design. This process is continued, until a satisfactory design is obtained. 7

165 Space F-16 Telescope Agile Falcon f-22 Lrg A/C BWB F/A-18 E/F GE Engine GM Auto Rotocraft Frontier Feasible Improved Optimal Pareto Figure 3-3: Range of Design Objectives Design Problem Decomposition and Organization The consensus appears to be that loosely coupled systems that can work with legacy analysis codes hold the most potential for future advances (see, for example Bennett et al 5, Bartholomew 8, Hoenlinger et al 9 ). Such a system also affords flexibility and can be reconfigured as the problem formulation evolves, as indicated in the previous section. This implies a need for an off- the-shelf modular software framework that facilitates the integration of the different analysis codes. In some instances, multilevel processes are used, rather than all-at-once systems for several applications since it seems inefficient to bring every disciplinary design variable and constraint up to the global level. This is commonly the case in structural optimization with detailed structural element models, where both local and global constraints are employed and where local variables are optimized. (See Bennett et al 5, Rohl et al 10 for examples). One of the advantages of decomposed procedures is that they can be used for multi site operations (Hoenlinger et al 9 ). Wakayama and Kroo 4 and Tarzanin et al 6 pointed out, however, that currently some of the more successful approaches use close-coupled, all-at-once procedures, however, their success depends, in part, on the fact that automated, fast-running analysis codes (intermediate fidelity level) are used. As indicated by Rohl et al 10, and also Hoenlinger et al 9, industry seems to feel that the more sophisticated MDO decomposition processes (e.g., CO, CSSO) are not yet fully proven or sufficiently matured. Rohl et al 10 indicate that, in some cases these approaches are not even suited for some of the applications to which they were applied. In other cases, as indicated by Bennett et al 5, it may be that the more complicated approaches are not easy to understand or follow and thus simpler processes are selected. Additionally, it seems obvious from the various 8 inputs that decomposition process flexibility is an absolute requirement and that the optimization process must be reconfigurable and tailorable to the specific problem encountered and to possible variations that might emerge in the problem formulation. Optimization Procedures and Issues The contributed papers state few requirements on the component optimization capabilities, although Bartholomew 8 points to the lack of robustness of off-theshelf optimization software. In general, industry practitioners need more experience in the art and science of applying optimization algorithms and interpreting their results. The typical engineering optimization problem is non-linear and non-convex, therefore, a great amount of experience is needed to reliably operate the optimization algorithms. Help in coping with lack of smoothness or scaling requirements, in overcoming slow convergence and local minima problems could significantly reduce the turnaround of typical optimization exercises. Wakayama and Kroo 4 point at the need for more robust and efficient industrial-strength, commercial-grade software to solve large scale problems. Hybrid schemes that can handle discrete and continuous design variables can prove also be very helpful in an industrial environment according to Bartholomew 8. Also, Rohl et al 10 point out that interdigitation, a procedure by which a combination of different algorithms is used to get to the global optimum of the problem. Tarzanin et al 6 encountered local minima and suggested various process to avoid them including a hybrid evolutionary process with NPSOL. Breadth and Depth Requirements As detailed by Wakayama and Kroo 4, industrial design processes must possess sufficient breadth. Specifically all of the critical constraints must be considered, otherwise the design will not be practical or feasible. This implies, among other things, that multiple flight conditions must be

166 verified, whether for demonstrating performance, flying qualities or for verifying stress/stability constraints. It has also been pointed out that all of the critical physical mechanisms should be included, to take advantage of all the available design opportunities. Some authors contend that the highest fidelity models are needed throughout the optimization process, others indicate that various level of accuracy are adequate. The MDO process itself can be used to help determine the fidelity levels required by performing accuracy sensitivity studies on the various critical physical mechanisms in the various disciplines. Effective Inclusion of High Fidelity Analyses/Test Bartholomew 8 has a defined set of analysis fidelity levels as follows: - Level 1: empirical equations, - Level 2: intermediate level models (e.g., beam theory, panel aero, etc.) - Level 3: state-of-the-art, high fidelity models(e.g., CFD, FEA) and has observed that industry MDO is moving toward Level 3 since disciplinary experts usually insist on using the latest, best, and highest fidelity information. If they cannot then they do not feel comfortable with the results. (They may even be uncomfortable with the best analyses /tests results since they are never fully assured that the real world is being faithfully simulated.) Therefore, effective inclusion of high fidelity data into the design optimization process is necessary, especially for designs at the preliminary and detailed design levels. This may be the most formidable challenge facing industry MDO users and methods developers. Such high fidelity processes are usually neither automated nor robust and many times require hours (even days) of computer time. Allowing an optimizer the opportunity to call such routines as often as it needs to, even if these routines were fully automated, is impractical, so various approximation methods need to be incorporated (Wakayama and Kroo 4, and Tarzanin et. al. 6 ). Approximation and Correction Processes One class of approximations methods include generic local approximations like Taylor series or variations as well as generic global approximations like response surfaces and neural nets, etc. These provide smooth, simple, explicit analytical expressions that can be generated automatically and that can be called by the optimizer as many times as needed without undue computational burden. Alternately, these approximations can be created concurrently off-line by disciplinary experts who can be responsible for their validity. The challenge in producing these approximations is the tradeoff between the amount of data needed to create them, and the control of their accuracy in the design variable space. For approximations in this class, the number of design variables that are strongly coupled still remains small, otherwise, the curse of dimensionality sets in and the approximations become unduly expensive. Also, it is critical to augment them locally to increase their fidelity in certain critical design regions. Another approximation class uses Level 1 or 2 fidelity disciplinary codes that have been corrected using high fidelity codes, or experimental results (see, for example Chang et al, 14, Baker et al 15, 16 ). In essence, the lower fidelity codes can be used as a smart interpolator/extrapolator. The challenge, as underlined by Wakayama and Kroo 4, is to make sure that all of the critical physical mechanisms are represented to some degree/level so that the high fidelity code information can be effectively utilized. A third class of approximations that can be considered for use in MDO are Reduced Order methods 17. These processes extract the essence of the high fidelity numerical results and expresses them in a relative simple analytic form. Parametric Geometric Modeling Bennett et al 5 and Honlinger et al 9, Radovcich and Layton 7 highlight the need for a shareable common vehicle description to facilitate communication among disciplines and among various companies and sites. Radovcich and Layton 7 report that a single high-fidelity model was used for most of the detail structural sizing and design of the F22 and that this model paid for itself many times over in communication and facilitated analysis and design iteration. They also pointed out that sometimes small changes in structural FEM grids can cause significant changes in internal loads and design, thus it is important to have a high-fidelity model. Automation is one of the essential requirements for MDO and many authors make the point that parametric and feature-based models facilitate automatic model changes (See, for example Hoenlinger et al 9, Wakayama and Kroo 4, Love 12 ). Morphing (rubberizing) is one approach at parameterization, but it does not always produce a manufacturable, or even reasonable structural layout. Hoenlinger et al 9 indicates, that, in such cases more sophisticated processes are called for which may require fitting continuous processes to discrete layouts. The resulting unified and parameterized geometry descriptions must be compatible with existing CAD software, however, as indicated by Rohl et al 10 additional development work is required since the parametric features of CAD available now are not robust enough for topology optimization. The work on the Technical Data 9

167 Modeller and Browser (TDMB) reported by Bartholomew 8 appears to be a response to this need. Analysis and Sensitivity Capability Several examples of this were encountered in the contributed papers where middle-level fidelity analysis codes are directly interfaced with the optimizers. (See for example Wakayama and Kroo 4 ). This was only possible because of the relatively low computational cost of the individual simulations. Some papers made use of off-the-shelf single-discipline high-fidelity optimization codes that were either automated (see Tarzanin et al 6 ) or partially automated (Hoelinger et al 9, Bartholomew 8 ). In each instance, the detailed analysis is interfaced with the optimizer through approximations of different kinds. Several systems such as STARS, LAGRANGE, NASTRAN Sol. 200, and others are available to automate and facilitate structural sizing but much additional work is yet to be done to fully integrate local panel design (as-built weight, composite manufacturability, cost, and mass balancing). Automated, robust, and efficient CFD analysis, optimization design is also needed but is still in the future. Industry prefers, in general, to utilize off-the-shelf (OTS) detailed analysis capability when ever possible. Rohl et al 10 give a good example of such an application to the design of jet engines which is based on UG, PRO-E, I- DEAS, PATRAN, ANSYS, ABAQUS, NASTRAN, and DEFORM. It must be emphasized that the drive towards inclusion of all the disciplines relevant to a complete design problem statement still requires major developments in different disciplines. While these developments are mostly outside of the field of MDO itself they deserve reference here. Satisfactory structural optimization requires detailed aerodynamic loads. A large number of critical flight conditions occur in the transonic regime or at high-angle of attack. While this information is now derived from wind tunnel experiments, significant reduction in design cycle can be achieved by deriving it computationally. Young et al 13 detailed the need for a comprehensive aerodynamic database, and, together with Hoenlinger et al 9 highlight the need for a methodology for nonlinear aerodynamic loads calculation and identification of critical load cases. The next step in disciplinary integration for MDO is to bring controls into a full aeroservoelastic formulation of the design problem. Methods are required that enable deriving controls metric and constraints early in the design process, at a time when very little is known of the aircraft configuration (see, for example Hoenlinger et al 9, Radovcich and Layton 7, Love 12 ). 10 Finally, central to a successful application of MDO are detailed first-principle-based cost models that include development, manufacturing, acquisition, operations and disposal. (See Love 12, for example.) Other Analysis capability needed are: - nonlinear aerodynamic loads (Hoenlinger et al 9 ) - wing load alleviation and aeroservoelastic integ. into str. sizing opt. (Ref. 7, 12 ). - intermed. level fidelity codes (which incl. critical physical mechanisms) (Ref. 4 ) - robust reduced order processes MDO Frameworks & Architecture Commercial off-the-shelf (OTS) software for MDO frameworks are desired by industry and some are available (isight, SYSOPT, others) (Rohl et al 10, Honlinger et al 9 ). Some have been tried but the degree of success is uncertain. In addition commercial distributed computing does not seem to be robust (Bartholomew 8 ). Industry wants demonstrated, validated MDO software (Honlinger et al 9 ) that is easy to use. Databases, Data Flow & Standards Industry considers database capability to be very important (Young et al 13 ). It is a repository for current (and past) design data (and the ground rules for generating them) and as such should facilitate communication and reduce cycle time for interdisciplinary data exchange (Bennett et al 5 ). Such a database must be industrial strength (able to handle huge amounts of data rapidly and should be able to sustain multi site, heterogeneous operation and be user friendly (Radovcich and Layton 7 ). A standard set of formats and ground rules for the data (STEP = Standard for The Exchange of Product data) (Bartholomew 8 ) will also greatly increase the speed of communication, reduce errors and greatly reduce cycle time. European experience includes projects supported by a Software Infrastructure Group and development (Task 8) of database and related tools as follows; - software version management - data definition - database technology - process definition - process execution on distributed networks - data visualization Computing Requirements In the case of the F-22 the size of the structural FEM and resulting database was determined by the computer memory (10 terabites) (Radovcich and Layton 7 ) required to house the database. CFD analysis and design also poses challenges to computing power. For instance it takes on the order of 10 hours for analysis and about hours per design variable for aerodynamic design using the C-90 supercomputer. Thus, if 20 d.v. are used for a design problem then the design would take approximately

168 300 computer hours. NASTRAN Solution 200 can easily run several days on a high end work station. Distributed computing is probably a necessity for the future to garner enough computing power to perform some of the required analysis functions and to drive multi site operations. Design Space Visualization Configuration designers can sometimes be more interested in the design space than the optimum design point. How flat or narrow is the design space near the optimum? How much is lost if an adjacent point is chosen because the optimum point is undesirable? Is the design space precipitous and overly sensitive to errors/noise in the disciplinary modules? How did the optimizer reach the optimum design point? The end result is that it is important to the designer to have user friendly processes for displaying the design space and interpreting the results of the optimization (Tarzanin and Young 6, Honlinger et al 9 ). Organizational Structure Industry is organized along disciplinary lines where each technology group is responsible for maintaining technical excellence, and ensuring that the data generated in that discipline is correct. It is absolutely necessary that this disciplinary control be maintained in any MDO process that is developed. One of these disciplines or technologies is contained in the Advanced/Conceptual Design group. This group is responsible for configuration design and global integration methods and applications. Usually, very approximate analysis methods are used there and so high-fidelity coordination with the various disciplines is minimal. However, for future MDO design such is not the case. If the Advanced/Conceptual Design group is to assume responsibility for MDO at the global level then it will have to change tactics somewhat and provide an integrating function (instead of providing their own simple disciplinary analyses) while allowing the various disciplines to maintain control of the local level design/sub-optimization and data recovery (such as internal FEM loads). In the papers sampled it is the perception that currently no one is in charge of MDO and that an improved company organization would benefit the use of MDO (Honlinger et al 9 ). Ensuring buy-in of the disciplinary experts to the MDO system may be difficult however (Bennett et al 5 ). MDO Operation within IPD Teams The IPD Team is an essential element in industrial design (References 4, 11, 10, 13 ). When MDO is used in the design the IPD team is not replaced but interacts with the process to learn about the design, assess the ground rules, add/replace constraints, furnish guidance in areas not modeled and generally keep the optimization on track (Wakayama and Kroo 4 ). An example of this was the composite wing design of Reference 19. MDO is a tool of 11 the IPD Team which is used to assist in selecting and implementing the final design. Acceptance, Validation, Cost, & Benefits A lack of understanding of MDO and what it means organizationally is an obstacle to industrial acceptance both by managers and by disciplinary experts (H). Also, Industry can have difficulty in determining both the benefits and development/deployment costs of MDO (Honlinger et al 9 ). How does a manager assess if there is a net benefit for developing and using an MDO process? Lack of validated results and quantified benefits in the practical industrial environment (not just mathematical process validation) is a big obstacle to its acceptance (References 4, 9 ). Specifically, the cost/benefit over conventional design processes is needed. An example of a test that proved that there were benefits of an optimized design is given by (Tarzanin and Young 6 ), however, a comparison of the predicted versus actual benefits was not given. Training Only recently have universities offered MDO oriented training and so, for the most part, only those in industry that are newly trained are intimately familiar with the formalisms associated with optimization. The rest of the engineering force are, to one degree or other, are having difficulty (Bennett et al 5 ). This lack of familiarity is an obstacle to the use of MDO in industry. 4. Development Needs for Future Industry MDO MDO Needs by Category MDO development needs in industry, as inferred/interpreted from the 10 papers and the experience of the current authors, are presented here. For consistency these needs are categorized in the same fashion as the salient points of Section 3, i.e., the categories shown in the MDO Taxonomy given in Figure 3-2 are used. Design Problem Objectives (Needs) Each industrial problem is different and so the biggest need is to have MDO frameworks that are flexible enough to accept whatever objective function is needed. As far as objective function formulation is concerned, research has been, and is being done to provide ways to formulate multiple, difficult or nebulous objective functions. Pareto Front techniques help define the biggest bang-for-buck so that, for instance, the DoD can decide on how much performance it can afford. Also, advances in simplified cost related objective functions have been made (Giesing and Wakayama et al 18, Bartholomew 8 ) and this type of work should continue. Design Problem Decomposition and Organization (Needs)

169 Most high fidelity process (e.g., CFD, FEM) are currently not automated, robust, nor fast enough to be directly called by an optimizer. Thus, a very big challenge is to somehow end up with a design that reflects this high fidelity but does not call it directly by the optimizer. Approximation approaches to this problem are mentioned in that particular category (discussed below). However, in this section the question is; are there decomposition approaches that could accomplish this task? For instance, can approaches be developed that converge to a high fidelity result that only require periodic high fidelity updates to the design process? Currently, analysis methods accommodate and are tailored/adapted to the needs of the optimizer (smoothness automation, etc.), however, this needs to be reversed. Development work on decomposition processes that accommodate and are tailored to the needs/deficiencies of the analysis methods (noise, lack of automation, very large computing time, etc.) are needed since analysis methods are the critical limiting factors in industrial MDO processes. Optimization Procedure and Issue (Needs) Improvements in optimization techniques are continuously being made and this must continue since industrial strength, robust, and efficient modules are needed. Industrial strength implies that large problems can be handled (thousands of design variables and constraints). Robust techniques are needed that converge under a wide variety of conditions. Efficient modules are needed to keep the computing time to a reasonable level. User friendly optimization techniques that are insensitive to noise or are self smoothing and that provide their own scaling (self scaling) are also needed. Finally robust processes and procedures for escaping local minima and finding the global optimum are needed. Breadth and Depth Requirement (Needs) All critical physical mechanisms and critical constraints must be accounted for in an accurate manner for realistic design. Breadth indicates the number of disciplines involved (mechanisms and constraints) and depth the accuracy/fidelity. Identification of all critical constraints requires experience in the design of the particular vehicle or artifact involved. Identification of the critical mechanisms is more subtle and difficult and requires understanding of the underlying physics of the various disciplines. Experience with high fidelity codes (e.g., CFD) does not necessarily mean that the various mechanisms are understood. Techniques that use the MDO process itself to determine which are the critical constraints and mechanisms would be very helpful. Effective Inclusion of High Fidelity Ana./Test (Needs) Two approaches for including high fidelity analyses in MDO have already been discussed, (using a decomposition approach and by using an approximation and correction approach). This section discusses what should be done to the high fidelity methods themselves for 12 direct use in MDO. Currently, many high fidelity processes (such as Navier Stokes, FEM global-local structural sizing) can not be used directly in MDO because they are not automated, robust, nor fast enough to be included. This presents formidable challenges in most disciplinary areas and advancements of the state-of-the-art are required. As each high fidelity technology area matures it becomes more robust and efficient and more subject to automation. Even after maturity however, computing requirements will still be a problem for high fidelity methods. Approximations and Corrections (Needs) This may be the single most important need for industrial MDO. As mentioned above many analysis codes (high fidelity or otherwise) can not be put directly into the MDO process and thus approximations and corrections must be used. Response surfaces, neural networks, Taylor series and Taguchi techniques are in current use but robust, efficient, and user-friendly software packages are needed. Procedures that use high fidelity analysis or test data to correct lower fidelity methods are also currently under development but improved techniques are needed in all disciplines. Simple mathematical (non physical) techniques of fudging low fidelity analysis methods need to be upgraded to those that isolate and correct each separate physical mechanism separately. Wakayama s (Reference 4 ) use of calibrated simple 3-D source flow terms to simulate transonic 3-D effects is an example. Baker et al 15,16 have also develoed advanced correction procedures for steady and unsteady aerodynamics and loads. An even more sophisticated approximation procedure is produced using reduced order or parameter identification methods and models (Ref. Baker 17 ). Simple examples are state space representations of dynamic aeroelastic models and associated rational function approximations for the unsteady aerodynamics. Other more sophisticated procedures require development, refinement, and extension. Finally, intermediate level fidelity methods can, themselves, be considered an approximation method whose approximating equations are based on physical mechanisms. If all of the critical physical mechanisms are present and a process, including high fidelity adjustments/corrections to each one, are in place then the intermediate fidelity level methods might be thought of as a physics-based interpolation/extrapolation medium for high fidelity codes. This is highly desirable since physics and not mathematics forms the basis of the approximation equations and not just mathematical fitting functions. Figure 4-1 presents examples of the approximation and correction procedures outlined here. Parametric Geometric Modeling (Needs) MDO processes require parametric models and automated modeling techniques. Tool kits such as the one being generated under DARPA sponsorship (PMTK) (Reference 10 ) will be helpful. Parametric models need to

170 High Fidelity Analysis or Sub-Optimiz Generic Approximations -Responce Surf. -Neural Nets -Taylor Series Optimizer High Fidelity Analysis or Sub-Optimiz Correction Process Intermediate Fidelilty Analysis - Phy. Mech. A - Phy. Mech. B - Phy. Mech. C Optimizer High Fidelity Analysis or Sub-Optimiz Reduced Order Representations Example A B {X}= [ ]{x} C D Optimizer Figure: 4-1 Three Approximation and/or Correction Processes maintain accuracy and realism as design variables are changed. Thus, for instance, morphing techniques may not be adequate for structural layouts since best industrial practices usually require changing the topology as design variables are changed. Also, straight structural members that become curved during morphing will probably not be acceptable. Robust, automated, and accurate nonparametric models are also required in industry as are interdisciplinary grid/mesh mapping techniques. Well proven software modules for these are needed. Analysis and Sensitivity Capability (Needs) Automation is one of the biggest needs with respect to disciplinary analysis methods. An automated analysis will allow the possibility of direct integration into an MDO process and will facilitate the generation and updating of approximations (response surfaces, etc.). Another challenge is the quantification of manufacturing and maintenance cost and constraint requirements into usable models. Cost is usually based on weight even though part count and complexity are much more important for cost than weight. The development and quantification of such models is a definite need in industry. Robust, efficient nonlinear loads analysis methods are also needed as well as well developed aeroservoelastic techniques. A current industry trend is to use well proven, over the counter (OTC) analysis modules and thus development of these is needed in all disciplines. Sensitivity analysis methods did not seem to be high on the list of required technologies, however, such methods are desirable to increase efficiency both for direct inclusion into optimization process or indirectly through the generation of response surfaces and other approximations. Robust CFD (Navier- Stokes) codes both rigid and aeroelastic are needed. Also, an efficient robust global-local structural sizing process is needed that accounts for all of the major structural effects; stress, buckling, aeroelastic loads, local panel design, durability and damage tolerance, flutter, and reversal. MDO Frameworks and Architecture (Needs) A mature, efficient, flexible, robust, industrial strength commercial MDO framework is desired by industry. Preferably, a loosely coupled reconfigurable system that can use legacy and other commercial software is best. The architecture should be flexible enough to accept a wide variety of MDO problems. Databases, Data Flow & Standards (Needs) Data standards for format, access, and monitoring are needed to facilitate analysis module integration and data transfer. An industrial strength, efficient, and easy to use commercial database system for multi-site, multi-platform operation is also needed. Possibly an Internet based system could be the system of the future if and when it is able to handle large engineering data sets in an efficient manner. Computing Requirement (Needs) Current CFD and FEM sizing (e.g., NASTRAN Solution 200) require hours and even days of computer time on high end work stations. This is a formidable barrier to their use in optimization processes. Improving computing power with the use of massively parallelized machines will improve this situation especially if analysis codes can be re-programmed to take advantage of them. Specifically, new subroutines and algorithms (e.g. matrix operations, eiganvalue analysis etc.) designed to take advantage of multiple processors are needed. In this case a straightforward process of re-programming existing analysis codes would be desirable. In this regard the HPCCP (High Performance Computing and Communication Program is dedicated to demonstrating 13

171 teraflops computing since it is assumed that this is the wave of the future. If clusters of work stations are used instead then efficient and robust distributed computing controller systems are needed. If the controller can span multiple sites then this will potentially open up a large resource for computing. This system, however, must be very versatile since work stations are usually available only on an intermittent basis and scheduling and coordinating would be a very challenging task. Design Space Visualization (Needs) Commercial MDO frameworks must provide easy to use optimization and design space visualization/interpreting since designers are sometimes more interested in the space around an optimum than the optimum itself. The largest challenge in this regard are techniques for visualizing a multidimensional design space. Since it is impossible to visualize anything beyond three-dimensions creative ways of interpreting or depicting the design space need to be invented. These depictions could require a lot more computing operations than the optimization process itself. Organizational Structure (Needs) Industry itself needs to adjust their organizations to facilitate MDO. Disciplinary groups would still develop and maintain technical excellence and be responsible for the accuracy and integrity of design data in an autonomous fashion. The responsibility for interfacing and coordinating all of the disciplines into an MDO process will have to be assigned to an MDO group. All of the disciplines will work together with the MDO Group as a team to decide on the interface processes. It makes sense that the MDO Group also is responsible for global configuration optimization and this job is currently being done by the Advanced Design Group. Does it then make sense to broaden the role of the Advanced Design Group to assume the responsibility of the MDO function? MDO Operation in IPD Teams (Needs) Industry itself needs to address this issue since IPD Teams are now a permanent part of the industrial landscape and are an ideal place to direct the MDO efforts. The MDO Group (or Advanced Design Group) may conduct the configuration optimum operations and perform trade studies that may not fit the optimization process, however, the IPD Team will direct this effort at a higher level. The IPD Team must get used to using MDO as a tool that they can direct. Design philosophy, ground rules for design, critical constraint selection and definition, restraints on the design, trade studies, etc. will all be directed by the disciplinary, tooling, manufacturing, maintenance, and cost experts that comprise the ITD Team. Acceptance, Validation, Cost & Benefits (Needs) The major need in this category is to produce a series of full industrial validation cases. These validations must be practical industrial strength cases and preferably done on actual vehicles. A firm validation based on test is preferred where the additional benefits of MDO, over and above current design practices, are quantified and compared to the additional effort/cost of MDO. Training (Needs) Industry is not used to the formalisms and use of optimization and MDO and thus training materials and courses that are meaningful to industry are needed. Also, new university graduates that are already properly trained are also needed. Satisfying MDO Development Needs The needs outlined in this section impact every sector of the MDO technology development community including universities, government labs, commercial software companies, and industry itself. Universities and government labs can help advance the state-of-the-art for disciplinary and MDO technology. Industry, can efficiently transfer this technology into practical use in industrial design. Commercial software companies can provide off-the-shelf industrial strength capability to setup and execute major multi-site design problems. The resources required for this development are very large and will have to come from multiple sources with maximum leveraging. A team approach is needed that coordinates plans and resources to ensure long range success. Figure 4-1 presents an illustration of this cooperative thrust. 14

172 Technology Development Community Industry Government Labs. University Commercial Software Technical Challenges and Needs Technology Development & Verification Technology Transfer & Applications Financial Leveraging Technology Commercialization University Gov. Labs Com. Soft. Industry TEAM Industrial Strength MDO Financial Resources Commer. Software Invest. University Government Contracts & R&T Base Industry IR&D Figure 4-2: Teaming of MDO and Disciplinary Technology Development Community 5. Conclusions A series of 10 invited design papers has been reviewed with the purpose of providing the MDO technology development community with a distilled view of industry applications, challenges, and needs. A wide variety of industries (airframe, automobile, rotorcraft, jet engine, space), and design problems (feasible design, trade studies, structural sizing, sub-optimization, dynamic response minimization, and full configuration MDO) were contained in the papers reviewed. The process of summarizing the papers and presenting the final results was as follows. First, a brief synopsis of each paper was presented to give an overview of the applications reviewed. Second, the challenges and salient points from each paper were delineated into one-line sentences which were then sorted into logical categories for various elements of MDO (Appendix I). These logical categories were based on an extension/revision of an existing taxonomy (classification of MDO elements) by Sobieski 3. Thirs, a general summary of each category was then written which was based on the salient points contained in that category. Finally, a summary of the MDO development needs for industry was given after distilling them from all of the categorized data. Even though the sample of papers was limited it is felt that a very good representation and cross-section of industrial applications, challenges and needs has been given and that the conclusions of the data contained here will be helpful to the MDO technology development community for prioritizing future MDO development. The technology development needs are wide ranging and will require the cooperative involvement of universities, government labs., 15 industry, and commercial software developers to answer these needs. 1 American Institure for Aeronautics and Astronautics Inc. (AIAA), Current State-of-the-Art in Multidisciplinary Design Optimization, prepared by the MDO Technical Committee, Jan 1991, AIAA, Reston, VA. (see also: sponsored/aiaa_paper.html) 2 Sobieszczanski-Sobieski, J. Haftka, R.T., Multidisciplinary Aerospace Design Optimization, Survey of Recent Developments, Structural Optimization, Vol. 14, No. 1, Aug Sobieszczanski-Sobieski, J. Multidisciplinary Design Optimization: An Emerging New Engineering Discipline, in Advances in Structural Mechanics, J. Herkovitch, Ed. Kluwer Academic Publishers, Doordrecht, pp , Wakayama, S., and Kroo, I, The Challenge and Promise of Blended-Wing-Body Optimization, AIAA Paper , presented at the 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, MO, Sep Bennett, J., Fenyes, P., Haering, W., and Neal, M., Issues in Industrial Multidisciplinary Optimization, AIAA Paper , presented at the 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, MO, Sep Tarzanin, F., and Young, D.K., Boeing Rotorcraft Experience with Rotor Design and Optimization, AIAA

173 Paper , presented at the 7th AIAA/ USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, MO, Sep Radovcich, N., and Layton, D., The F-22 Structural Aeroelastic Design Process with MDO Examples, AIAA Paper , presented at the 7th AIAA/ USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, MO, Sep Bartholomew, P. The Role of MDO within Aerospace Design and Progress Towards an MDO Capability Through European Collaboration, AIAA Paper , presented at the 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, MO, Sep Hoenlinger, H., Krammer, J., and Stettner, M., MDO Technology Needs in Aeroservoelastic Structural Design, AIAA Paper , presented at the 7th AIAA/ USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, MO, Sep Rohl, P., He, B., and Finnigan, P., A Collaborative Optimization Environment for Turbine Engine Development, AIAA Paper , presented at the 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, MO, Sep Lillie, C., Wehner, M., and Fitzgerald, T, R., Multidiscipline Design as applied to Space, AIAA Paper , presented at the 7th AIAA/USAF/ NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, MO, Sep Love, M. H., Multidisciplinary Design Practices from the F-16 Agile Falcon, AIAA Paper , presented at the 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, MO, Sep Young, J.A., Anderson, R.D., and Yurkovitch, R.N., A Description of the F/A-18E/F Design and Design Process, AIAA Paper , presented at the 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, MO, Sep Chang, K.J., Haftka, R.T., Giles, G.L., and Kao, P.J., Sensitivity-based scaling for approximating structural response, Vol. 30, pp , Baker, M. L., Yuan, K., Goggin, P. J., Calculation of Corrections to Linear Aerodynamic Methods for Static and Dynamic Analysis and Design, AIAA Paper , presented at the 39th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Long Beach, CA, April Baker, M. L., CFD Based Corrections for Linear Aerodynamic Methods, presented at the 85th Meeting of the AGARD Structures and Materials Panel, Aalborg, Denmark, Oct and contained in AGARD Report 822, entitled, Numerical Unsteady Aerodynamic and Aeroelastic Simulation, March 1998, pg Baker, M. L., Mingori, D. L., Goggin, P. J., Approximate Subspace Iteration for Constructing Internally Balanced Reduced Order Models of Unsteady Aerodynamic Systems, AIAA Paper , presented at the 37th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Salt Lake City UT, April 15-17, Giesing, J. P., Wakayama, S., A Simple Cost Related Objective Function for MDO of Transport Aircraft, AIAA Paper , presented at the 35th Aerospace Sciences Meeting & Exhibit, Jan. 1997, Reno, NV. 19 Wakayama, S., Page, M., Liebeck, R. H., Multidisciplinary Optimization on an Advanced Composite Wing, AIAA Paper CP, presented at the 6th AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Bellevue, WA., Sept. 4-6, 1996 Appendix I: Salient Points from the 11 Papers Sorted by Catagories Legend Y=Young, Anderson, & Yurkovich W=Wakayama & Kroo L=Love H=Honlinger, Krammer, & Stettner R=Rhol, Beichang, & Finnigan B=Bennett, Fenyes, Haering, & Neal Bw=Bartholomew Rl=Radovcich/Layton T=Tarzanin & Young Lwf=Lillie/Wehner/Fitzgerald Design Formulations & Solutions Design Objectives - Minimize TOGW. W - Large aeroelastic structural sizing/optimization of aircraft. H - MDO math. formulation and definition of Best is a problem. W Y L - Accuracy of Obj. Funct. may be off by 100%. Y - Objective function hard to formulate. Y L - Most important is satisfying constraints. Y Lwf - Second most important is Robustness. Y - Better design, Nearest local opt. mostly continuous design variables. H - Feasible, better design, mostly continuous, large no. of d.v. and constr. and multiple obj. H - Reduced cycle time, discover critical aspects early, model manufacturing; continuous process definition from definition to product. H - Reduced weight, maintain performance, detailed design. Rl 16

174 - DOC (Direct Operating Cost) heuristically approximated with very simple linear combination of weight and drags at various flight conditions. Bw - Frontier Project uses Pareto Front techniques to identify biggest bang for buck. Bw Design Problem Decomposition and Organization - Definition of MDO excludes flight simulation. Bw - BWB is a highly coupled problem and used an all-atonce MDO formulation i.e., included all d.v. (mission, aero, str., etc) at the global level. W - Industry processes are sequential; MDO requires concurrent processes. H - MDO technology not yet mature enough for industrial use. H - MDO strategies for multisite operation is needed. H - How do you use CO to include high fidelity results. W - Just use trade study and DOE approach. L Y - Just add more analyses to trade study approach (MDO not needed). L Y - Advanced decomposition processes are OK if they prove themselves. Y - Needed when high fidelity involved. W - Interdigitized optimization could prove useful. R - CO and CSSO may not be very practical. R - How do you make CO practical. W - Need a distributed optimization process. R - Going to loosely coupled processes for MDO since source code not available for OTS MDO codes like isight. R - Global/Local process needed; Sub optimization of disciplines used. B - Complex large scale optimizer not needed; used ADS. B - Must go toward loose coupling to make further progress in MDO. B - Suitable MDO method is needed. H - CSSO CO class of decomposition too complex and little understood. H - CSSO CO class of decomposition immature for Industry. H - CSSO CO class of decomposition lacks software. H - Loosely coupled process needed to handle all of the constraints. Y - Tightly coupled needed to be efficient and enable to perform in reasonable time. W - Had to use tightly coupled system to make practical. T - Loosely coupled preferred. H - Tightly coupled needed for special problems. H - Both are needed. H - Design done in cycles requiring sequential steps. Various disciplines lagged several cycles; loads/ flutter; one cycle, fatigue; 2 cycles, elastic-to-rigid effects on maneuver flight simulator; three cycles. Some disciplines performed several cycles for each global cycle. Rl - Sometimes had to get forward looking models to help leap frog the global iteration. Rl - Challenge is to provide tools to integrate disciplines. Bw - Europe moving toward loosely coupled systems. Bw - Conceptual Design is multidisciplinary but low fidelity. Bw - Preliminary Design is fragmented and configuration flexibility lost. Bw - Don t need close coupled black box. Bw - Do need loose coupled modular framework that can use legacy codes. Bw - Multilevel Global-Local Structural optimization employed in GARTEUR. Bw - MDO process needs to be flexible and reconfigurable. Bw - Industrial design process does not necessarily fit a particular MD procedure. Need flexibility and reconfigurability. B Optimization Procedures and Issues - MDO problem Size is an issue. W - Smoothness can be a problem. W R - Local minimums is a challenge. T - Ways to get around local minimums. T 1) New starting point. 2) Broaden move and constraint limits initially. 3) Change wt. factors in Obj. Function. 4) Update fixed parameters periodically. - Increase robustness by incrementally tightening constraints as optim. progresses. - Structural sizing optimization. Rl - Manual optimization facilitated by common high fidelity FEM, rapid turn- around on cycle updates, performing strength/fatigue sizing first then iterating for flutter. Rl - Direct use of optimizer less attractive due to the number of possible function calls to high fidelity analysis routines; possibly use a hybrid scheme. Bw - Design variable linking needed. B - MDO robustness is lacking since different sites end up with different optimums. Bw - Optimize system by running simulation of interdisciplinary process. Lwf Analysis Capabilities & Approximations Breadth vs Depth Requirements - All critical constraints needed otherwise weird results (e.g. pointed wing tips). W - All critical mechanisms needed otherwise may loose a mechanism to optimize. W - Must have high fidelity or results are useless. Y - Inability to analytically (instead of wind tunnel tests) determine design variable sensitivities is a need. Y 17

175 - Need capability for multiple configurations, fuel, stores, actuator failure. H Approximation and Correction Processes - Response Surfaces may be too big and expensive. W - Response Surfaces play a key role. L - Use RS, Neural Nets, Taylor Series. B - Lack of Intermediate Fidelity Codes is a problem. W - Approximation based processes. H - Use Approximation models. B W - Approximation generation software needed. H - Correct intermediate methods using high fidelity data (References 15 and 16) - Used nonlinear wind tunnel test data to correct linear loads (especially with reference to control surfaces). Rl - Use Response Surfaces to reduce cost. B W Effective Inclusion of High Fidelity Analyses/Test Results in Optimization and Design - Close coupled process made high fidelity possible. T - Replacing Wind Tunnel data in design process. Y - Possibly use Response Surfaces. W - Used an automatic FEM generator. H - Rapid CFD for air loads. Y - Need high fidelity propulsion integration for BWB; cannot effectively include it at intermediate fidelity level. W - Fidelity levels categorized; Bw Level 1- empirical modes (e.g. conceptual design) Level 2- intermediate level (e.g. beam str. models, panel aero etc.) Level 3- State-of-art high fidelity (e.g. CFE, FEM) - MDO is moving toward Level 3 fidelity. Bw - Analysis times for high fidelity codes can make MDO problem intractable. R Parametric Modeling - Need parametric geometric mode compatible with current CAD systems. R - Parametric CAD not robust enough for topology optimization. R - Need parametric/associative modeling and speed up analysis. L - Automated robust model generation needed. H W - Lack of layout/material distribution algorithms. H - Discipline models too complex. H - Standard product process models and interfaces catering to it. H - Automation and ease of use and checking is a barrier in disciplinary analysis integration to MDO. H - Single high fidelity FEM used for stress, loads, flutter, allowables, fatigue, aeroelastic effectiveness. Rl - TDMB (Technical Data Modeller and Browser) can develop a fully parameterized aircraft configuration and associated aero, FEM and AE models. Data conforms to STEP standards. Bw - Unified parameterized geometry description. B - Need shareable common vehicle description and approximations, easy ways to interact back and forth with various disciplines. B - Common models for structural, thermal, and optical needed. Lwf Analysis and Sensitivity Capability - Affordability missing in design. L - Move away from weight based cost. L - Manufacturability in design is needed. L - Need missing engine-out constraint for BWB. W - Bring controls into structural design process (early). H L - Need to bring controls further up in the design process. L - Nonlinear loads database is a big barrier. Y - Sensitivities will be used when design community gets use to them. Y - Aero wind tunnel data can not produce sensitivities needed in optimization. Y - Need aeroservoelastic integration. H - Need capability for multiple configurations, fuel, stores, actuator failure. H - Lack of Robustness is a barrier to use of disciplinary analysis in MDO. H - Employed high fidelity fuel tank loads. Rl - Used CFD and test to determine Hammer Shock. Rl - Maneuver load active controls used to reduce weight. Rl - STARS code used for structural optimization. B - LAGRANGE code used for structural optimization. H - Need nonlinear aero but is complex. H - Need standardized tool interfaces and disciplinary analysis tools which are developed with interdisciplinary interfacing in mind. H - Moving to OTS codes for analysis and MDO (UG, PRO-E, I-DEAS, PATRAN, ANSYS, ABAQUS, NASTRAN, DEFORM etc.) R - Applicability to MDO is a barrier to use of disciplinary analysis in MDO. H - Working on a full structural, thermal, optical simulation process. Lwf - Large internal load changes due to FEM grid changes/refinements. Rl - Important margin of safety changes due to small internal load or FEM changes. Rl - Composite tailoring impractical due to costs associated with testing/databases. Rl Information Management, Data Flow & Processing MDO Frameworks & Architecture - Use the isight generic MDO system. R 18

176 - Developed GM system tailored to car design. B - Industry wants to use off the shelf tools AD included. Y - Use generic Genie system and GUI but not commercially available system. W - Stopped developing LAGRANGE because it might be better to go to a general architecture. H - Need a flexible user configurable MDO architecture. Current commercial optimization codes over sensitive to details, do not always converge to optimum, and are not very flexible. Bw - Commercial distributed computing not robust. Bw - GSE software is lacking. H - Software integration tools needed for design process organization. H - Demonstrated Validated MDO software is needed. H - Interfacing various systems together and keeping versions of software working is a concern. Lwf Databases, Data Flow & Standards - Common databases, database management all help. Y - Tool interfaced do not match. H - Tool interfaces is a barrier. H - Data standards are needed. H - Database updating of data and the ground rules that generated them. B - ORACLE database used. Rl - Terabyte data handling needed. Rl - Recent projects supported by Software Infrastructure Group. Bw - Need common standards for data definition and intercommunication vehicle (STEP=standard for the exchange of product data). Bw - Multi-site MDO and data capability needed. Bw - European MDO Process (Task 8) have provided the following tools; software version management, data definition, database technology, process definition, process execution on distributed networks, data visualization and optimization. Bw - Common database used for F/A-18 E/F. Y - Database as support for Response Surfaces. T - Interdisciplinary data conversion and transmission is a problem. Lwf Computing Requirements - F-22 needed a widely distributed, very heterogeneous computing system. Rl - Very large memory 10 Terabytes needed for F-22. Rl - The amount of data stored for the F-22 was so large that the process had constraints on the amount of information manipulated. Plies were optimized later in the process because of that. Rl - Distributed computing used for F/A -18 E/F. Y - Computing infrastructure and available deployed hardware not kept up to demands of MDO. R Design Space Visualization - Need graphic visualization. H - Need process for extracting characteristic features of a family of designs. H - Interpreting results is an obstacle to optimization. H - User friendly monitoring tools would be beneficial. H - Need design space display. T Management & Cultural Implementation Organizational Structure - No coordinating person for MDO in industry. H - MDO should be someone s job in industrial organization. B - Conflicting requirements impedes MDO implementation - Conceptual Design. Dept. says that MDO code does not include all the needed disciplines- Analysis Dept. says that your models are too simple. B - Industry sometimes lacks math skills and has difficulty with MDO formalisms. B - Improved company organization would benefit use of MDO. H - Loss of control by disciplinary experts is an issue. H - Coordinated Tri-company team by instituting detailed ground rules, guidelines, and policies. Rl - Cross functional, partners, different locations. Rl - Coordinating and scheduling of multisite MDO important. Bw MDO Operation within IPD Teams - Integration of IPT and MDO needed. W - IPT Needed to keep opt. on track. W - IPT (key organizational element) Needed to help decide on opt. config. Y - Common High fidelity FEM model used to facilitate communication and reduce cycle time and errors. Rl - Non optimal design of long lead time items (actuators). Rl - Budget profiles did not always match process flow requirements. Rl - Variations in results due to ground-rules which may not be known ahead of time. Bw - IPD team direction and learning is needed to help direct MDO and its ground rules. Bw Acceptance, Validation, Cost & Benefits - Validation is a MDO Cultural Acceptance Problem. W - MDO produces benefits over conventional design in performance, weight and in providing baselines for further analysis. W - Lack of acceptance of MDO by management and disciplinary experts. H - Lack of validated MDO results is an obstacle to use of optimization. H 19

177 - Quantification of MDO benefit versus MDO development cost is missing. H - Imbalance of fidelity is an obstacle to acceptance of discipline trading via MDO. W - Large common FEM (and associated computing bill) paid for itself many times over in reduced cycle time, increased communications and reduced errors. Rl - Future European SM to verify MDO and its benefits. Bw - MDO gives clear benefits as shown by tests (however no comparison with expected improvement). T Training - User familiarity and training is an obstacle to using optimization. H - Engineering force having difficulty with optimization formalisms and precisely defining objective function. B - New engineers are more familiar with optimizaiton tools. B 20

178 MDO TC Home Page MULTIDISCIPLINARY DESIGN OPTIMIZATION TECHNICAL COMMITTEE The AIAA Multidisciplinary Design Optimization Technical Committee (MDO TC) works to provide an AIAA forum for those active in development, application, and teaching of a formal design methodology based on the integration of disciplinary analyses and sensitivity analyses, optimization, and artificial intelligence, applicable at all stages of the multidisciplinary design of aerospace systems. News and Announcements In May 2003 the AIAA MDO TC web site moved from its current location to a server at AIAA headquarters. Once the move occurs, the old MDO TC web site will remain available, but it will not be updated with new information. I'll send out to the TC members once the new site is up and running. Comments on the new web site are welcome. -Tony Giunta, webmaster, aagiunt@sandia.gov Click here for a link to the NEW MDO TC web site. Click here for a link to the old MDO TC web site. Last Updated: 29 May 2003 Anthony A. Giunta, aagiunt@sandia.gov 12:28:43 PM

179 MDO TC Home Page MULTIDISCIPLINARY DESIGN OPTIMIZATION TECHNICAL COMMITTEE The AIAA Multidisciplinary Design Optimization Technical Committee (MDO TC) works to provide an AIAA forum for those active in development, application, and teaching of a formal design methodology based on the integration of disciplinary analyses and sensitivity analyses, optimization, and artificial intelligence, applicable at all stages of the multidisciplinary design of aerospace systems. News and Announcements In May 2003 the AIAA MDO TC web site moveed from this site to its current location on a server at AIAA headquarters. The infomation on this web site is no longer updated. -Tony Giunta, webmaster, aagiunt@sandia.gov Click here for a link to the new MDO TC web site. Communications White Paper on Industrial Experience with MDO. TC lists and browsable web archives: Two electronic mailing lists are available for internal TC announcements. Contact Tony Giunta if you need the addresses for these lists. (They are not listed here to reduce spam .) TC meeting minutes TC subcommittee reports TC newsletters Download TC files Sponsored Activities (1 of 2)12/29/ :28:44 PM

180 MDO TC Home Page (need to update) Conferences supported by the MDO TC Short courses supported by the MDO TC White papers and publications prepared by the MDO TC Frequently Asked Questions What is MDO? What functions are performed by the AIAA MDO TC? How do I join the AIAA MDO TC? Operations Information MDO TC Operations Manual TC operations slides in: HTML format. Portable Document Format (PDF file, Adobe Acrobat required). Downloadable postscript. Last Updated: 17 October 2002 Anthony A. Giunta, aagiunt@sandia.gov (2 of 2)12/29/ :28:44 PM

181 MDO Electronic Mailing Lists MDO Electronic Mailing Lists The MDO Electronic Mailing Lists are serviced by Majordomo and the browsable archives are managed by LWGate. The following FAQ and help information provide additional details on Majordomo, although this background is not required to be able to use the MDO mailing lists. mdotc_public: The mdotc_public majordomo list sends electronic mail to all current AIAA MDO TC members. It is a public list in that all traffic on the list is archived here on the TC Web site (accessible to anyone on the Web, not just members of the TC). Therefore, TC members should use the mdotc_public list for matters concerning all TC members which are appropriate for posting on the Web. The purpose of the Web archives is to provide a convenient reference and central database of TC information and announcements. To send a public message to the TC, TC members should use the address mdotc_public@endo.sandia.gov. Postings to the list are restricted to members of the TC. With assistance from the MDO TC chairman's database, the Internet subcommittee chairman keeps the addresses current. No action is required from the TC membership. Archives from the mdotc_public list: mdotc_public 2006 sorted by: [ date ] [ subject ] [ author ] mdotc_public 2005 sorted by: [ date ] [ subject ] [ author ] mdotc_public 2004 sorted by: [ date ] [ subject ] [ author ] mdotc_public 2003 sorted by: [ date ] [ subject ] [ author ] mdotc_public 2002 sorted by: [ date ] [ subject ] [ author ] mdotc_public 2001 sorted by: [ date ] [ subject ] [ author ] mdotc_public 2000 sorted by: [ date ] [ subject ] [ author ] mdotc_public 1999 sorted by: [ date ] [ subject ] [ author ] mdotc_public 1998 sorted by: [ date ] [ subject ] [ author ] mdotc_private: (1 of 2)12/29/ :28:45 PM

182 MDO Electronic Mailing Lists Like the mdotc_public list, the mdotc_private list will send electronic mail to all AIAA MDO TC members. However, it is a private list in that its traffic is not posted on the Web for all to see. Therefore, TC members should use the mdotc_private list for matters concerning all TC members for which posting on the Web is inappropriate. To send a private message to the TC, TC members should use the address mdotc_private@endo.sandia.gov. Postings to this list are restricted to members of the TC. [ NO ARCHIVES ] Back to MDO TC Home Page Last Updated: 12 September 2002 aagiunt@sandia.gov (2 of 2)12/29/ :28:45 PM

183 If you're familiar with mail servers, an advanced user's summary of Majordomo's commands appears at the end of this message. Majordomo is an automated system which allows users to subscribe and unsubscribe to mailing lists, and to retrieve files from list archives. You can interact with the Majordomo software by sending it commands in the body of mail messages addressed to Please do not put your commands on the subject line; Majordomo does not process commands in the subject line. You may put multiple Majordomo commands in the same mail message. Put each command on a line by itself. If you use a "signature block" at the end of your mail, Majordomo may mistakenly believe each line of your message is a command; you will then receive spurious error messages. To keep this from happening, either put a line starting with a hyphen ("-") before your signature, or put a line with just the word end on it in the same place. This will stop the Majordomo software from processing your signature as bad commands. Here are some of the things you can do using Majordomo: I. FINDING OUT WHICH LISTS ARE ON THIS SYSTEM To get a list of publicly-available mailing lists on this system, put the following line in the body of your mail message to Majordomo@endo.sandia.gov: lists Each line will contain the name of a mailing list and a brief description of the list. To get more information about a particular list, use the "info" command, supplying the name of the list. For example, if the name of the list about which you wish information is "demo-list", you would put the line (1 of 6)12/29/ :28:46 PM

184 info demo-list in the body of the mail message. II. SUBSCRIBING TO A LIST Once you've determined that you wish to subscribe to one or more lists on this system, you can send commands to Majordomo to have it add you to the list, so you can begin receiving mailings. To receive list mail at the address from which you're sending your mail, simply say "subscribe" followed by the list's name: subscribe demo-list If for some reason you wish to have the mailings go to a different address (a friend's address, a specific other system on which you have an account, or an address which is more correct than the one that automatically appears in the "From:" header on the mail you send), you would add that address to the command. For instance, if you're sending a request from your work account, but wish to receive "demo-list" mail at your personal account (for which we will use "jqpublic@my-isp.com" as an example), you'd put the line subscribe demo-list jqpublic@my-isp.com in the mail message body. Based on configuration decisions made by the list owners, you may be added to the mailing list automatically. You may also receive notification that an authorization key is required for subscription. Another message will be sent to the address to be subscribed (which may or may not be the same as yours) containing the key, and directing the user to send a command found in that message back to Majordomo@endo.sandia.gov. (This can be a bit of extra hassle, but it helps keep you from being swamped in extra by someone who forged requests from your address.) You may also get a message that your subscription is being forwarded to the list owner for approval; some lists have waiting lists, or policies about who may subscribe. If your request is forwarded for approval, the list owner should contact you soon after your request. Upon subscribing, you should receive an introductory message, containing list policies and features. Save this message for future reference; it (2 of 6)12/29/ :28:46 PM

185 will also contain exact directions for unsubscribing. If you lose the intro mail and would like another copy of the policies, send this message to intro demo-list (substituting, of course, the real name of your list for "demo-list"). III. UNSUBSCRIBING FROM MAILING LISTS Your original intro message contains the exact command which should be used to remove your address from the list. However, in most cases, you may simply send the command "unsubscribe" followed by the list name: unsubscribe demo-list (This command may fail if your provider has changed the way your address is shown in your mail.) To remove an address other than the one from which you're sending the request, give that address in the command: unsubscribe demo-list In either of these cases, you can tell to remove the address in question from all lists on this server by using "*" in place of the list name: unsubscribe * unsubscribe * jqpublic@my-isp.com IV. FINDING THE LISTS TO WHICH AN ADDRESS IS SUBSCRIBED To find the lists to which your address is subscribed, send this command in the body of a mail message to Majordomo@endo.sandia.gov: which You can look for other addresses, or parts of an address, by specifying the text for which Majordomo should search. For instance, to find which users at my-isp.com are subscribed to which lists, you might send the command (3 of 6)12/29/ :28:46 PM

186 which my-isp.com Note that many list owners completely or fully disable the "which" command, considering it a privacy violation. V. FINDING OUT WHO'S SUBSCRIBED TO A LIST To get a list of the addresses on a particular list, you may use the "who" command, followed by the name of the list: who demo-list Note that many list owners allow only a list's subscribers to use the "who" command, or disable it completely, believing it to be a privacy violation. VI. RETRIEVING FILES FROM A LIST'S ARCHIVES Many list owners keep archives of files associated with a list. These may include: - back issues of the list - help files, user profiles, and other documents associated with the list - daily, monthly, or yearly archives for the list To find out if a list has any files associated with it, use the "index" command: index demo-list If you see files in which you're interested, you may retrieve them by using the "get" command and specifying the list name and archive filename. For instance, to retrieve the files called "profile.form" (presumably a form to fill out with your profile) and "demo-list.9611" (presumably the messages posted to the list in November 1996), you would put the lines get demo-list profile.form get demo-list demo-list.9611 in your mail to Majordomo@endo.sandia.gov. VII. GETTING MORE HELP To contact a human site manager, send mail to Majordomo-Owner@endo.sandia.gov. (4 of 6)12/29/ :28:46 PM

187 To contact the owner of a specific list, send mail to that list's approval address, which is formed by adding "-approval" to the user-name portion of the list's address. For instance, to contact the list owner for demo-list@endo.sandia.gov, you would send mail to demo-list-approval@endo.sandia.gov. To get another copy of this help message, send mail to Majordomo@endo.sandia.gov with a line saying help in the message body. VIII. COMMAND SUMMARY FOR ADVANCED USERS In the description below items contained in []'s are optional. When providing the item, do not include the []'s around it. Items in angle brackets, such as <address>, are meta-symbols that should be replaced by appropriate text without the angle brackets. It understands the following commands: subscribe <list> [<address>] Subscribe yourself (or <address> if specified) to the named <list>. unsubscribe <list> [<address>] Unsubscribe yourself (or <address> if specified) from the named <list>. "unsubscribe *" will remove you (or <address>) from all lists. This _may not_ work if you have subscribed using multiple addresses. get <list> <filename> Get a file related to <list>. index <list> Return an index of files you can "get" for <list>. which [<address>] Find out which lists you (or <address> if specified) are on. who <list> Find out who is on the named <list>. (5 of 6)12/29/ :28:46 PM

188 info <list> Retrieve the general introductory information for the named <list>. intro <list> Retrieve the introductory message sent to new users. Non-subscribers may not be able to retrieve this. lists Show the lists served by this Majordomo server. help Retrieve this message. end Stop processing commands (useful if your mailer adds a signature). Commands should be sent in the body of an message to "Majordomo@endo.sandia.gov". Multiple commands can be processed provided each occurs on a separate line. Commands in the "Subject:" line are NOT processed. If you have any questions or problems, please contact "Majordomo-Owner@endo.sandia.gov". (6 of 6)12/29/ :28:46 PM

189 MDO TC Meeting Minutes MDO TC Meeting Minutes September 2002 TC Meeting Minutes (Atlanta) April 2002 TC Meeting Minutes (Denver) January 2002 TC Meeting Minutes (Reno) April 2001 TC Meeting Minutes (Seattle) January 2001 TC Meeting Minutes (Reno) September 2000 TC Meeting Minutes (Long Beach) April 2000 TC Meeting Minutes (Atlanta) January 2000 TC Meeting Minutes (Reno) October 1999 TC Meeting Minutes (Internet meeting) April 1999 TC Meeting Minutes (St. Louis) January 1999 TC Meeting Minutes (Reno) September 1998 TC Meeting Minutes (St. Louis) April 1998 TC Meeting Minutes (Long Beach) January 1998 TC Meeting Minutes (Reno) October 1997 TC Meeting Minutes (St. Louis) April 1997 TC Meeting Minutes (Kissimmee) January 1997 TC Meeting Minutes (Reno) September 1996 TC Meeting Minutes (Bellevue) (1 of 2)12/29/ :28:54 PM

190 MDO TC Meeting Minutes April 1996 TC Meeting Minutes (Salt Lake City) January 1996 TC Meeting Minutes (Reno) September 1995 TC Meeting Minutes (Los Angeles) Back to MDO TC Home Page Last Updated: 26 June 2002 Tony Giunta, (2 of 2)12/29/ :28:54 PM

191 mdotc_apr02 MINUTES OF THE MDO TC MEETING April 22, 2002 Denver,CO PRELIMINARIES Achille Messac called the meeting to order at 6:30 PM. Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Balabanov, Basu, Canfield, Gurdal, Kodiyalam, Smith, Striz, de Weck,Willcox,Zang,Schweiger, Giunta,Tappeta. Other guests were Mattson, Mullur, Ismail-yahaya, Fadel, Engelsen,Wang, Malare, Chris Horton (AIAA), Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., names, addresss, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through Achille Messac in order to maintain a consistent and up to date database. Changes will be passed on to Anthony Giunta for inclusion on the web site. Reno MDO-TC (January 14, 02) MEETING MINUTES REVIEWED AND APPROVED MA &O 2002 Balabanov discussed the progress on organizing this conference, which will be held at Grand Hyatt Atlanta from 4-6 Sept The number of abstracts submitted for the conference was 285 and out of these 270 papers were accepted. The acceptance percentage was 94%. Participants upon registration will get a Book of Abstracts to plan their 3 days effectively. The General co-chairs for this conference are Farrokh Mistree and Dan Schrage from GT. The technical co-chairs for this conference are Dan DeLaurentis from GT School of AE and Pradeep Raj from Lockheed Martin Aeronautics Company. The theme of the conference will be System Affordability. SDM 2002 meeting at Denver. Kodiyalam represented MDO TC at this conference. Gurdal represented MDO TC at the SDM long range planning committee. Zafar mentioned that this committee is proposing new guidelines for chairing future conferences and it may not be possible for MDO TC representative to chair the SDM conference according to new rules. There was a discussion amongst the TC members about the small size of the (1 of 3)12/29/ :28:55 PM

192 mdotc_apr02 rooms provided for the MAO sessions. Even though the room was supposed to accommodate 50 persons there were only 30 chairs and for some presentations there was no standing room. SDM meeting at Norfolk, April Srinivas and Khot will represent the MDO TC at this Conference. Awards Committee (Canfield) Bob Canfield discussed the activities of this subcommittee regarding membership upgrades, best paper award, MDO TC award etc. Top 12 papers were selected for the best paper award and this number will be reduced to three papers during the next step in the selection process. Application Subcommittee (Purcell) Guruswamy was not present but Frode Engelsen mentioned that the committee is still working on collecting and condensing inputs from MAO community. The target is to write a white paper based on the information collected. Education Subcommittee(Kemper) Kemper was not present but Doug Smith summarized the activities of the subcommittee. The committee is planning to have MAO paper competition during 2004 MAO conference. Their future plan includes marketing an AIAA endorsed home study course on MDO. Publication Subcommittee (Striz) Striz discussed future plans on setting up a web site for benchmark problems and definitions. Presentation by Dr. Schweiger Schweiger made presentation on the Active Aeroelastic Aircraft Structures research work being conducted at EADS Deutschland. Plaque for Messac Balabanov presented a plaque to Achille Messac on behalf of AIAA for his excellent work as the chairman of the MDO TC. (2 of 3)12/29/ :28:55 PM

193 mdotc_apr02 White Paper Issues. Achille Messac discussed the future plans for the white paper and then divided the members into four groups for brainstorming exercise. At the end representative form each group presented their ideas. Achille Messac requested each team representative to him summary of team s ideas. MEETING SCHEDULE NEXT MEETING: 4-6 September 2002 at Atlanta, Georgia The meeting was adjourned at 10:30 PM. Respectfully submitted on 6/21/2002 Narendra Khot AFRL/VASD 2210 Eighth Street Wright -Patterson AFB, OH, Tel: (937) Fax: (937) Narendra Khot@va.wpafb.af.mil (3 of 3)12/29/ :28:55 PM

194 MDO TC Meeting Minutes (11 January 2000) PRELIMINARIES MINUTES OF THE MDO TC MEETING January 14, 2002 Reno, NV Chairman Achille Messac called the meeting to order at 7:00 PM. Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Messac, Anderson, Balabanov, Batill, Bounajem, Canfield, DeLaurentis, Grossman, Guruswamy, Khot, Kramer, Purcell, Striz, Giunta. Other guests were Raj (Lockheed), and members of AIAA staff and members of the AIAA Technical Activities Committee. Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through Achille Messac in order to maintain a consistent and up to date database. Changes will be passed on to Anthony Giunta for inclusion on the web site. AIAA Activity Steve Schultz from AIAA staff discussed the new Strategic Plan. He mentioned that the MDO TC would be moved from its current organizational home (Aircraft Technology Integration & Operation ) to a new home (Engineering & Technology and Management). His presentation gave an impression that this decision taken by the members of the board of directors of the AIAA Technical Activities Committee, without consultation with MDO TC, was final. However, Robert Winn, Vice President-Elect, Technical Activities who came afterwards mentioned that this decision is not final and he will communicate to the board of directors the opinion of the MDO TC. It was then agreed that the AIAA staff will send the pertinent information to MDO TC Chair, who will pursue the matter further, taking into consideration the opinion of the members of the MDO TC committee. As of the writing of this report, Achille Messac has led a successful discussion with the whole TC and with AIAA, and the matter has been resolved to the satisfaction of all parties. Seattle MDO-TC (Aprill 17, 01) MEETING MINUTES REVIEWED AND APPROVED (1 of 4)12/29/ :28:56 PM

195 MDO TC Meeting Minutes (11 January 2000) MA &O 2002 STATUS REPORT The two technical co-chairs, Dan DeLaurentis from GT School of AE and Pradeep Raj, discussed the progress on organizing this conference. Abstract submission deadline has been extended to 11 Feb Super chairs and Special session organizers are in place. The conference will be held at Grand Hyatt Atlanta on 4-6 Sept SDM meeting at Denver, April 2001 Srinivas Kodiyalam represented the MDO TC at this Conference. He was unable to attend MDO TC meeting at Reno. Awards Committee (Canfield) Bob Canfield discussed requirements for membership upgrades to Senior Member, Associate Fellow and Fellow. Bernie Grossman and Frank Eastep (previous member of TC) were elected Fellows. Evin Cramer and Ram Krishnamachari were elected Associate Fellows. Best paper nominations have been received and the selection committee is in the process of picking up the best paper for award during MA & O 2002 conference. The nominees for MDO award are due soon. Education Subcommittee (Anderson) Kurt Anderson presented his thoughts on MAO graduate and undergraduate paper competitions and marketing of AIAA endorsed home study course on MDO. Survey Guru Guruswamy has sent out a questioner to assess the state of the art on the use of high fidelity methods in multidisciplinary optimization. He discussed his related activities. Publication Subcommittee (Stritz) Stritz discussed future plans on publication of a color brochure explaining MDO to industry. He (2 of 4)12/29/ :28:56 PM

196 MDO TC Meeting Minutes (11 January 2000) also mentioned that he would like to collect segments of the Aerospace America Highlight articles of the last few years into a comprehensive MDO development story and put it on the MDO web page. MDO TC Chair Chairman Achille Messac was reelected unanimously by the TC for another term. Due to his upcoming responsibilities as the General Chair of the Multidisciplinary Analysis and Optimization Symposium in 2004, he will step down as TC Chair in one year. This will allow him to devote his full TC attention to the success of the conference. It was also proposed that the TC should consider changing the term of the TC Chair to three years for the next chair. This matter will be addressed further. MEETING SCHEDULE NEXT MEETING: Monday April at Denver CO, 6:30PM-10:00 PM. The meeting was adjourned at 10:30 PM. Respectfully submitted on 3/6/2002 Narendra Khot AFRL/VASD 2210 Eighth Street Wright -Patterson AFB,OH, Tel: (937) Fax: (937) Narendra Khot@va.wpafb.af.mil Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: March 22, (3 of 4)12/29/ :28:56 PM

197 MDO TC Meeting Minutes (11 January 2000) Michael Eldred, (4 of 4)12/29/ :28:56 PM

198 Michael S. Eldred - Sandia National Laboratories Michael S. Eldred Telephone: Voice: (505) Fax: (505) Address: Sandia National Laboratories P. O. Box 5800 MailStop: 1318 Org: Albuquerque, NM Location: Bldg: CSRI Room: mseldre@sandia.gov (Personal) dakota-developers (DAKOTA project) Experience Mike received his B.S. in Aerospace Engineering from Virginia Tech in 1989, his M.S.E. and Ph.D. in Aerospace Engineering from the University of Michigan in 1990 and 1993, and is currently a Principal Member of the Technical Staff in the Optimization and Uncertainty Estimation Department within the Computation, Computers, Information, and Mathematics Center at Sandia National Laboratories. Research Mike is currently the project leader for the DAKOTA effort. Mike's research interests include surrogate-based optimization, uncertainty quantification, optimization under uncertainty, parallel processing, and object-oriented software development. A number of his publications are available on the DAKOTA web site. Professional Activities Mike is an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and a member of the Society for Industrial and Applied Mathematics (SIAM), the International Society for Structural and Multidisciplinary Optimization (ISSMO) and the United States Association for Computational Mechanics (USACM). Mike served as a member of the AIAA Multidisciplinary Design Optimization Technical Committee from , and currently serves on the editorial board for Structure and Infrastructure Engineering: Maintenance, Management, Life-Cycle Design and Performance and as a member of the AIAA Nondeterministic Approaches Working Group. (1 of 2)12/29/ :28:58 PM

199 Michael S. Eldred - Sandia National Laboratories Quarterly Reports (Restricted Access) Sandia Corporation Site Contact Site Map Privacy and Security (2 of 2)12/29/ :28:58 PM

200 Large-scale Engineering Opt and UQ The DAKOTA Project: Large-scale Engineering Optimization and Uncertainty Analysis DAKOTA Version 4.0 Released May 12, 2006 DAKOTA software Download DAKOTA Applications Publications Research Contacts DAKOTA in the News 2006 Risk-Informed Design Flyer April 2002 Press Release November 2001 Lab News article Supercomputing 2000 flyer Overview Computational methods developed in structural mechanics, heat transfer, fluid mechanics, shock physics, and many other fields of engineering can be an enormous aid to understanding the complex physical systems they simulate. Often, it is desired to use these simulations as virtual prototypes to obtain an acceptable or optimized design for a particular system. This effort seeks to enhance the utility of these computational methods by enabling their use as design tools, so that simulations may be used not just for single-point predictions, but also for automated determination of system performance improvements throughout the product life cycle. This allows analysts to address the fundamental engineering questions of foremost importance to our programs, such as "what is the best design?", "how safe is it?", and "how much confidence do I have in my answer?". System performance objectives can be formulated to minimize weight, cost, or defects; to limit a critical temperature, stress, or vibration response; or to maximize performance, reliability, throughput, reconfigurability, agility, or design robustness. A systematic, rapid method of determining these optimal solutions will lead to better designs and improved system performance and will reduce dependence on prototypes and testing, which will shorten the design cycle and reduce development costs. Toward these ends, a general purpose software toolkit is under continuing development for the integration of commercial and in-house simulation capabilities with broad (1 of 4)12/29/ :29:00 PM

201 Large-scale Engineering Opt and UQ classes of systems analysis tools. Written in C++, the DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit is intended as a flexible, extensible interface between simulation codes and iterative systems analysis methods. In addition to optimization methods, DAKOTA implements uncertainty quantification with sampling, reliability, and stochastic finite element methods, parameter estimation with nonlinear least squares methods, and sensitivity/variance analysis with design of experiments and parameter study capabilities. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment as well as a platform for rapid prototyping of advanced methodologies which focus on increasing robustness and efficiency for computationally complex engineering problems. Several of these research programs are discussed below. Large-scale Applications Multilevel Parallel Optimization with Salinas CVD Reactor Design with MPSalsa Publications A list of recent and upcoming publications is available. Many can be downloaded in PDF or postscript form. Research Directions Research programs have focused on several areas: Parallel processing. Selected publications include: "Multilevel Parallel Optimization Using Massively Parallel Structural Dynamics". (2 of 4)12/29/ :29:00 PM

202 Large-scale Engineering Opt and UQ "Multilevel Parallelism for Optimization on MP Computers: Theory and Experiment". Surrogate-based optimization. SBO with data fits. SBO with multifidelity models. SBO with reduced-order modeling (ROM). Uncertainty quantification. Selected publications include: "Investigation of Reliability Method Formulations in DAKOTA/UQ". "A Toolkit For Uncertainty Quantification In Large Computational Engineering Models". Optimization under uncertainty. Surrogate-based. Reliability-based. Contacts DAKOTA Software Contact: dakota-developers. Technical Contact: Michael S. Eldred, Principal Member of Technical Staff. Business Contact: Scott A. Mitchell, Manager of Optimization and Uncertainty Estimation Department. Location Sandia National Laboratories P. O. Box 5800, Mail Stop 0370 Albuquerque, NM Back to top of page Questions and Comments Acknowledgment and Disclaimer Last Updated: August 4, 2004 dakota-developers (3 of 4)12/29/ :29:00 PM

203 Large-scale Engineering Opt and UQ (4 of 4)12/29/ :29:00 PM

204 Recent and Upcoming Publications Recent and Upcoming Publications Journal Papers Optimization Home Journal Papers Conference Papers Conference Abstracts SAND Reports Giunta, A.A., McFarland, J. M., Swiler, L.P., and Eldred, M.S., "The promise and peril of uncertainty quantification using response surface approximations," Structure & Infrastructure Engineering: Maintenance, Management, Life-Cycle Design & Performance, special issue on Uncertainty Quantification and Design under Uncertainty of Aerospace Systems, Vol. 2, Nos. 3-4, Sept.-Dec. 2006, pp Eldred, M.S., Agarwal, H., Perez, V.M., Wojtkiewicz, S.F., Jr., and Renaud, J.E., "Investigation of Reliability Method Formulations in DAKOTA/UQ," Structure & Infrastructure Engineering: Maintenance, Management, Life-Cycle Design & Performance (to appear), Taylor & Francis Group. Also appears in Proceedings of the 9th ASCE Joint Specialty Conference on Probabilistic Mechanics and Structural Reliability, Albuquerque, NM, July 26-28, Lemke, R.W., Knudson, M.D., Bliss, D.E., Cochrane, K., Davis, J.- P., Giunta, A.A., Harjes, H.C., and Slutz, S.A., "Magnetically accelerated, ultrahigh velocity flyer plates for shock wave experiments," J. Applied Physics, Vol. 98, Salinger, A.G., Pawlowski, R.P., Shadid, J.N., and van Bloemen Waanders, B., "Computational Analysis and Optimization of a Chemical Vapor Deposition Reactor with Large-Scale Computing," Industrial and Engineering Chemistry Research, in press, Simpson, T. W., Booker, A. J., Ghosh, D., Giunta, A. A., Koch, P. N. and Yang, R.-J., "Approximation Methods in Multidisciplinary Analysis and Optimization: A Panel Discussion," Structural and Multidisciplinary Optimization, Vol. 27, No. 5, 2004, pp Eldred, M.S., Giunta, A.A., and van Bloemen Waanders, B.G., "Multilevel Parallel Optimization Using Massively Parallel (1 of 15)12/29/ :29:02 PM

205 Recent and Upcoming Publications Structural Dynamics," Structural and Multidisciplinary Optimization, Springer-Verlag, Vol. 27, Nos. 1-2, May 2004, pp Also appears as paper AIAA in Proceedings of the 42nd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Seattle, WA, April 16-19, Romero, V. J., Swiler L. P., and Giunta, A. A., "Construction of Response Surfaces Based on Progressive-Lattice-Sampling Experimental Designs," Structural Safety, Vol. 26, No. 2, pp , Biegler, L.T., Ghattas, O., Heinkenschloss, M., and van Bloemen Waanders, B., "Large-scale PDE-constrained Optimization: An Introduction," Large-Scale PDE-Constrained Optimization, Lecture Notes in Computational Science and Engineering, No. 30, Springer- Verlag, 2003, pp Salinger, A.G., Pawlowski, R.P., Shadid, J.N., van Bloemen Waanders, B., Bartlett, R., Itle, G.C., and Biegler, L., "rsqp Optimization of Large Scale Reacting Flow Applications with MPSalsa," Large-Scale PDE-Constrained Optimization, Lecture Notes in Computational Science and Engineering, No. 30, Springer- Verlag, 2003, pp Bartlett, R.A. and Biegler, L.T., "rsqp++: An Object-Oriented Framework for Successive Quadratic Programming," Large-Scale PDE-Constrained Optimization, Lecture Notes in Computational Science and Engineering, No. 30, Springer-Verlag, 2003, pp Greenberg, D.S., Hart, W.E., and Phillips, C.A., "Enabling Department-Scale Supercomputing," Algorithms for Parallel Processing, IMA Volumes in Mathematics and Its Applications, 105: Hart, W.E., "Sequential Stopping Rules for Random Optimization Methods with Applications to Multistart Local Search," SIAM Journal of Optimization, 1999, pp Also appears as Sandia (2 of 15)12/29/ :29:02 PM

206 Recent and Upcoming Publications Technical Report SAND , Nov Dowding, K.J., and Blackwell, B.F., "Joint Experimental/ Computational Techniques to Measure Thermal Properties of Solids," Measurement Science and Technology, Vol. 9, No. 6, June 1998, pp Eldred, M.S., Outka, D.E., Bohnhoff, W.J., Witkowski, W.R., Romero, V.J., Ponslet, E.R., and Chen, K.S., "Optimization of Complex Mechanics Simulations with Object-Oriented Software Design," Computer Modeling and Simulation in Engineering, Vol. 1, No. 3, August 1996, pp Also appears as paper AIAA in Proceedings of the 36th AIAA/ASME/ ASCE/AHE/ASC Structures, Structural Dynamics, and Materials Conference, New Orleans, LA, April 10-13, 1995, pp Conference Papers Bichon, B.J., Eldred, M.S., Swiler, L.P., Mahadevan, S., and McFarland, J.M., "Multimodal Reliability Assessment for Complex Engineering Applications using Sequential Kriging Optimization," abstract submitted for 48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (9th AIAA Non- Deterministic Approaches Conference), Honolulu, HI, April 23-26, Eldred, M.S., Adams, B.M., Copps, K.D., Carnes, B., Notz, P.K., Hopkins, M.M., and Wittwer, J.W., "Solution-Verified Reliability Analysis and Design of Compliant Micro-Electro-Mechanical Systems," abstract submitted for 48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (9th AIAA Non-Deterministic Approaches Conference), Honolulu, HI, April 23-26, Adams, B.M., Eldred, M.S., Wittwer, J., and Massad, J., "Reliability- Based Design Optimization for Shape Design of Compliant Micro- Electro-Mechanical Systems," paper AIAA in the (3 of 15)12/29/ :29:02 PM

207 Recent and Upcoming Publications Proceedings of the 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Portsmouth, VA, Sept. 6-8, Eldred, M.S. and Dunlavy, D.M., "Formulations for Surrogate-Based Optimization with Data Fit, Multifidelity, and Reduced-Order Models," paper AIAA in the Proceedings of the 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Portsmouth, VA, Sept. 6-8, Giunta, A.A., Swiler, L.P., Brown, S.L., Eldred, M.S., Richards, M. D., and Cyr, E.C., "The Surfpack Software Library for Surrogate Modeling of Sparse Irregularly Spaced Multidimensional Data," paper AIAA in the Proceedings of the 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Portsmouth, VA, Sept. 6-8, Robinson, T.D., Willcox, K.E., Eldred, M.S., and Haimes, R., "Multifidelity Optimization for Variable-Complexity Design," paper AIAA in the Proceedings of the 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Portsmouth, VA, Sept. 6-8, Eldred, M.S. and Bichon, B.J., "Second-Order Reliability Formulations in DAKOTA/UQ," paper AIAA in Proceedings of the 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (8th AIAA Non- Deterministic Approaches Conference), Newport, Rhode Island, May 1-4, Robinson, T.D., Eldred, M.S., Willcox, K.E., and Haimes, R., "Strategies for Multifidelity Optimization with Variable Dimensional Hierarchical Models," paper AIAA in Proceedings of the 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (2nd AIAA Multidisciplinary Design Optimization Specialist Conference), Newport, Rhode Island, May 1-4, Weickum, G., Eldred, M.S., and Maute, K., "Multi-point Extended Reduced Order Modeling For Design Optimization and Uncertainty Analysis," paper AIAA in Proceedings of the 47th AIAA/ ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and (4 of 15)12/29/ :29:02 PM

208 Recent and Upcoming Publications Materials Conference (2nd AIAA Multidisciplinary Design Optimization Specialist Conference), Newport, Rhode Island, May 1-4, Eldred, M.S., Bichon, B.J., and Adams, B.M., "Overview of Reliability Analysis and Design Capabilities in DAKOTA," Proceedings of the NSF Workshop on Reliable Engineering Computing (REC 2006), Savannah, GA, February 22-24, Eldred, M.S., Giunta, A.A., and Collis, S.S, "Second-Order Corrections for Surrogate-Based Optimization with Model Hierarchies," paper AIAA in Proceedings of the 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Albany, NY, Aug Sept. 1, Giunta, A.A., Eldred, M.S., Swiler, L.P., Trucano, T.G., and Wojtkiewicz, S.F., Jr., "Perspectives on Optimization Under Uncertainty: Algorithms and Applications" paper AIAA in Proceedings of the 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Albany, NY, Aug Sept. 1, Perez, V.M., Eldred, M.S., and Renaud, J.E., "Solving the Infeasible Trust-region Problem Using Approximations," paper AIAA in Proceedings of the 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Albany, NY, Aug Sept. 1, Giunta, A.A., Eldred, M.S., and Castro, J.P., "Uncertainty Quantification Using Response Surface Approximations," Proceedings of the 9th ASCE Joint Specialty Conference on Probabilistic Mechanics and Structural Reliability, Albuquerque, NM, July 26-28, Perez, V.M., Eldred, M.S., and Renaud, J.E., "An rsqp Approach for a Single-Level Reliability Optimization," Proceedings of the 9th ASCE Joint Specialty Conference on Probabilistic Mechanics and Structural Reliability, Albuquerque, NM, July 26-28, van Bloemen Waanders, B., "Application of Optimization Methods to the Calibration of Water Distribution Systems," Proceedings of the World Water and Environmental Resources Congress (EWRI), (5 of 15)12/29/ :29:03 PM

209 Recent and Upcoming Publications Salt Lake City, UT, June 27 - July 1, Giunta, A.A., Wojtkiewicz, S.F., Jr., and Eldred, M.S., "Overview of Modern Design of Experiments Methods for Computational Simulations," paper AIAA in Proceedings of the 41st AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, Jan. 6-9, Simpson, T.W., Booker, A.J., Ghosh, D., Giunta, A.A., Koch, P.N., and Yang, R.-J., "Approximation Methods in Multidisciplinary Analysis and Optimization: A Panel Discussion," 3rd ISSMO/AIAA Internet Conference on Approximations in Optimization, Oct , Eldred, M.S., Giunta, A.A., Wojtkiewicz, S.F., Jr., and Trucano, T. G., "Formulations for Surrogate-Based Optimization Under Uncertainty," paper AIAA in Proceedings of the 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Atlanta, GA, Sept. 4-6, Giunta, A.A., Eldred, M.S., Trucano, T.G., and Wojtkiewicz, S.F., Jr., "Optimization Under Uncertainty Methods for Computational Shock Physics Applications," paper AIAA in Proceedings of the 43rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (Nondeterministic Approaches Forum), Denver, CO, April 22-25, Giunta, A. A., "Use of Data Sampling, Surrogate Models, and Numerical Optimization in Engineering Design," paper AIAA in Proceedings of the 40th AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, Jan Wojtkiewicz, S.F., Jr., Eldred, M.S., Field, R.V., Jr., Urbina, A., and Red-Horse, J.R., "A Toolkit For Uncertainty Quantification In Large Computational Engineering Models," paper AIAA in Proceedings of the 42nd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Seattle, WA, April 16-19, Eldred, M.S., Hart, W.E., Schimel, B.D., and van Bloemen Waanders, B.G., "Multilevel Parallelism for Optimization on MP (6 of 15)12/29/ :29:03 PM

210 Recent and Upcoming Publications Computers: Theory and Experiment," paper AIAA in Proceedings of the 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Long Beach, CA, September 6-8, Giunta, A.A., and Eldred, M.S., "Implementation of a Trust Region Model Management Strategy in the DAKOTA Optimization Toolkit," paper AIAA in Proceedings of the 8th AIAA/ USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Long Beach, CA, September 6-8, Eldred, M.S., and Schimel, B.D., "Extended Parallelism Models for Optimization on Massively Parallel Computers," paper 16-POM-2 in Proceedings of the 3rd World Congress of Structural and Multidisciplinary Optimization (WCSMO-3), Amherst, NY, May 17-21, Eldred, M.S., and Hart, W.E., "Design and Implementation of Multilevel Parallel Optimization on the Intel TeraFLOPS," paper AIAA in Proceedings of the 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, MO, Sept. 2-4, 1998, pp Blackwell, B.F., and Eldred, M.S., "Application of Reusable Interface Technology for Thermal Parameter Estimation," Proceedings of the 32nd National Heat Transfer Conference, Vol. 2, Eds. Dulikravitch, G.S., and Woodbury, K.E., HTD-Vol. 340, August 1997, pp Chen, K.S., and Witkowski, W.R., "Design Optimization of Liquid- Distribution Chamber-Slot Dies Using the DAKOTA Toolkit," 50th Annual Conference of the Society for Imaging Science and Technology, Cambridge MA, May 18-23, Hobbs, M. L., "A Global HMX Decomposition Model," 1996 JANNAF Propulsion Systems Hazards Subcommittee Meeting, Naval Postgraduate School, Monterey, CA, Nov. 4-8, Eldred, M.S., Hart, W.E., Bohnhoff, W.J., Romero, V.J., Hutchinson, S.A., and Salinger, A.G., "Utilizing Object-Oriented Design to Build Advanced Optimization Strategies with Generic (7 of 15)12/29/ :29:03 PM

211 Recent and Upcoming Publications Implementation," paper AIAA in Proceedings of the 6th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Bellevue, WA, Sept. 4-6, 1996, pp Moen, C.D., Spence, P.A., Meza, J.C., and Plantenga, T.D., "Automatic Differentiation for Gradient-Based Optimization of Radiatively Heated Microelectronics Manufacturing Equipment," paper AIAA in Proceedings of the 6th AIAA/USAF/NASA/ ISSMO Symposium on Multidisciplinary Analysis and Optimization, Bellevue, WA, Sept. 4-6, 1996, pp Ponslet, E.R., and Eldred, M.S., "Discrete Optimization of Isolator Locations for Vibration Isolation Systems: an Analytical and Experimental Investigation," paper AIAA in Proceedings of the 6th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Bellevue, WA, Sept. 4-6, 1996, pp Also appears as Sandia Technical Report SAND , May Hart, W.E., "A Stationary Point Convergence Theory for Evolutionary Algorithms," Proceedings of Foundations of Genetic Algorithms 4, San Diego, CA, August 3-5, 1996, pp Hart, W.E., Baden, S., Belew, R.K., Kohn, S., "Analysis of the Numerical Effects of Parallelism on a Parallel Genetic Algorithm," Proceedings of the 10th International Parallel Processing Symposium(IPPS `96), Honolulu, HI, April 15-19, 1996, pp Hart, W.E., "A Theoretical Comparison of Evolutionary Algorithms and Simulated Annealing," Proceedings of the Fifth Annual Conference on Evolutionary Programming (EP `96), San Diego, CA, February 29 - March 2, 1996, pp Harding, D.C., Eldred, M.S., and Witkowski, W.R., "Integration of Finite Element Analysis and Numerical Optimization Techniques for RAM Transport Package Design," Proceedings of the 11th International Conference on the Packaging and Transportation of Radioactive Materials (PATRAM `95), Las Vegas, NV, Dec. 3-8, Harding, D.C., and Eldred, M.S., "Radioactive Material (8 of 15)12/29/ :29:03 PM

212 Recent and Upcoming Publications Transportation Package Design Using Numerical Optimization Techniques," Proceedings of the 1995 Joint ASME/JSME Pressure Vessels and Piping Conference, Honolulu, Hawaii, July 23-27, 1995, Vol. PVP-307, pp Romero, V.J., Eldred, M.S., Bohnhoff, W.J., and Outka, D.E., "Application of Optimization to the Inverse Problem of Finding the Worst-Case Heating Configuration in a Fire," Proceedings of the 9th International Conference on Numerical Methods in Thermal Problems, Atlanta, GA, July 17-21, 1995, Vol. 9, Part 2, pp Witkowski, W.R., Eldred, M.S., and Harding, D.C., "Integration of Numerical Analysis Tools for Automated Numerical Optimization of a Transportation Package Design," Proceedings of the 5th AIAA/ NASA/USAF/ISSMO Symposium on Multidisciplinary Analysis and Optimization, paper AIAA , Panama City Beach, FL, Sept. 7-9, Conference Abstracts Carnes, B., Copps, K.D., Eldred, M.S., Adams, B.M., Wittwer, J.W., "Coupled a posteriori error estimation and uncertainty quantification for a nonlinear elasticity MEMS problem," abstract for SIAM Conference on Computational Science and Engineering (CSE07), Costa Mesa, CA, February 19-23, Dunlavy, D.M. and Eldred, M.S., "Formulations for Surrogate-Based Optimization Using Data Fit and Multifidelity Models," abstract for SIAM Conference on Computational Science and Engineering (CSE07), Costa Mesa, CA, February 19-23, Robinson, T.D., Willcox, K.E., Eldred, M.S., and Haimes, R., "Multifidelity Optimization for Variable-Complexity Design," abstract submitted for Second International Workshop on Surrogate Modeling and Space Mapping for Engineering Optimization, Lyngby, Denmark, Nov. 9-11, Giunta, A.A., Castro, J.P., Hough, P.D.,Gray, G.A., Eldred, M.S., "Multifidelity Modeling Approaches in Simulation-Based (9 of 15)12/29/ :29:03 PM

213 Recent and Upcoming Publications Optimization," abstract for the SIAM Conference on Optimization, Stockholm, Sweden, May 15-19, Giunta, A.A., Eldred, M.S., Hough, P.D., and Castro, J.P., "Overview of Surrogate-Based Optimization Research and Applications at Sandia National Laboratories," abstract for the Surrogate Optimization Workshop, Houston, TX, May 24-25, Giunta, A.A. and Eldred, M.S., "Robust Design Optimization Using Surrogate Models," abstract for the Robust Optimization-Directed Design (RODD) Conference, Shalimar, FL, April 19-21, Giunta, A.A., Eldred, M.S., Wojtkiewicz, S.F., Jr., Trucano, T.G., and Castro, J.P., "Surrogate-Based Optimization Methods for Engineering Design," abstract in Proceedings of the Fifth Biennial Tri-Laboratory Engineering Conference on Computational Modeling, Santa Fe, NM, October 21-23, Giunta, A. A., and Eldred, M. S., "Surrogate-Based Optimization Under Uncertainty: Formulations and Applications" abstract in the Proceedings of the 18th International Symposium on Mathematical Programming, Copenhagen, Denmark, Aug Eldred, M.S., Giunta, A.A., Wojtkiewicz, S.F., Jr., and Trucano, T. G., "Formulations for Surrogate-Based Optimization Under Uncertainty," abstract in Proceedings of the 7th U.S. National Congress on Computational Mechanics, Albuquerque, NM, July 28-30, Giunta, A.A. and Eldred, M.S., "Engineering Design Optimization Algorithms: Theory and Practice," abstract in Proceedings of the 7th U.S. National Congress on Computational Mechanics, Albuquerque, NM, July 28-30, Eldred, M.S., Giunta, A.A., Wojtkiewicz, S.F., Jr., and Trucano, T. G., "Surrogate-Based Optimization Under Uncertainty: Status and Directions," abstract in SIAM Conference on Computational Science and Engineering. Final Program and Abstracts, San Diego, CA, Feb 10-13, Giunta, A.A. and Eldred, M.S., "Case Studies in Computational Engineering Design Optimization: Challenges and Solutions," (10 of 15)12/29/ :29:03 PM

214 Recent and Upcoming Publications abstract in SIAM Conference on Computational Science and Engineering. Final Program and Abstracts, San Diego, CA, Feb 10-13, Eldred, M.S., "DAKOTA: Virtual Prototyping with Large-Scale Engineering Simulations," abstract in IMA Workshop 4: Optimization in Simulation-Based Models, Minneapolis, MN, January 9-16, Eldred, M.S., "The DAKOTA Optimization Framework: Virtual Prototyping with ASCI-Scale Simulations," abstract in Proceedings of the Fourth Biennial Tri-Laboratory Engineering Conference on Computational Modeling, Albuquerque, NM, Oct , 2001, p. 82. Wojtkiewicz, S.F., Jr., Field, R.V., Jr., Eldred, M.S., Red-Horse, J. R., and Urbina, A., "Uncertainty Quantification in Large Computational Engineering Models," abstract in Proceedings of the Fourth Biennial Tri-Laboratory Engineering Conference on Computational Modeling, Albuquerque, NM, Oct , 2001, p. 11. Hart, W. E., Giunta, A. A., Salinger, A. G., and van Bloemen Waanders, B., "An Overview of the Adaptive Pattern Search Algorithm and its Application to Engineering Optimization Problems," abstract in Proceedings of the McMaster Optimization Conference: Theory and Applications, McMaster University, Hamilton, Ontario, Canada, August 2001, p. 20. Wojtkiewicz, S.F., Jr., Eldred M.S., Field, R.V., Jr., Urbina, A., Red- Horse, J.R., and Giunta, A.A., "DAKOTA/UQ: A Toolkit for Uncertainty Quantification in a Multiphysics, Massively Parallel Computational Environment," presented as (1) poster at ODU-NASA Training Workshop on Nondeterministic Approaches and Their Potential for Future Aerospace Systems, held in Langley, Virginia, May 30-31, 2001, (2) abstract (no proceedings) at USNCCM VI (Sixth United States Congress on Computational Mechanics) held in Dearborn, Michigan, August 1-3, 2001, and (3) abstract (no proceedings) at LLNL Sensitivity Analysis Workshop, August 16-17, van Bloemen Waanders, B., "Simultaneous Analysis and Design Optimization of Massively Parallel Simulation Codes using Object Oriented Framework," abstract for Tenth SIAM Conference on (11 of 15)12/29/ :29:03 PM

215 Recent and Upcoming Publications Parallel Processing for Scientific Computing, March Giunta, A.A., "Coupling High-Performance Computing, Optimization, and Shock Physics Simulations," abstract in session CP04 of the Final Program of the First SIAM Conference on Computational Science and Engineering, Washington, DC, September 21-23, 2000, p. 47. Hart, W.E., Eldred, M.S., and Giunta, A.A., "Solving mixed-integer nonlinear problems with PICO," abstract in proceedings of the 17th International Symposium on Mathematical Programming (ISMP 2000), Atlanta, GA, August 7-11, van Bloemen Waanders, B.G., Eldred, M.S., Hart, W.E., Schimel, B. D., and Giunta, A.A., "A Review of the Dakota Toolkit, Multilevel Parallelism for Complex PDE Simulations on TeraFLOP Computers," abstract presented in the Optimization in Engineering Minisymposium at the SIAM Annual Meeting, Rio Grande, Puerto Rico, July 10-14, Romero, V.J., Painton, L.A., and Eldred, M.S., "Optimization Under Uncertainty: Shifting of Maximum Vulnerability Point Due to Uncertain Failure Thresholds," 1997 INFORMS Spring Meeting, San Diego, CA, May Eldred, M.S., Outka, D.E., and Bohnhoff, W.J., "Optimization of Complex Engineering Simulations with the DAKOTA Toolkit," abstract in Proceedings of the First Biennial Tri-Laboratory Engineering Conference on Computational Modeling, Pleasanton, CA, Oct. 31-Nov. 2, SAND Reports Adams, B.M., Bichon, B.J., Carnes, B., Copps, K.D., Eldred, M.S., Hopkins, M.H., Neckels, D.C., Notz, P.K., Subia, S.R., and Wittwer, J.W., "Solution-Verified Reliability Analysis and Design of Bistable MEMS Using Error Estimation and Adaptivity," Sandia Technical Report SAND , October Eldred, M.S., Brown, S.L., Adams, B.M., Dunlavy, D.M., Gay, D. (12 of 15)12/29/ :29:03 PM

216 Recent and Upcoming Publications M., Swiler, L.P., Giunta, A.A., Hart, W.E., Watson, J.-P., Eddy, J.P., Griffin, J.D., Hough, P.D., Kolda, T.G., Martinez-Canales, M.L. and Williams, P.J., "DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 4.0 Users Manual," Sandia Technical Report SAND , October Eldred, M.S., Brown, S.L., Adams, B.M., Dunlavy, D.M., Gay, D. M., Swiler, L.P., Giunta, A.A., Hart, W.E., Watson, J.-P., Eddy, J.P., Griffin, J.D., Hough, P.D., Kolda, T.G., Martinez-Canales, M.L. and Williams, P.J., "DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 4.0 Reference Manual," Sandia Technical Report SAND , October Eldred, M.S., Brown, S.L., Adams, B.M., Dunlavy, D.M., Gay, D. M., Swiler, L.P., Giunta, A.A., Hart, W.E., Watson, J.-P., Eddy, J.P., Griffin, J.D., Hough, P.D., Kolda, T.G., Martinez-Canales, M.L. and Williams, P.J., "DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 4.0 Developers Manual," Sandia Technical Report SAND , October Swiler, L.P. and Wyss, G.D., "A User's Guide to Sandia's Latin Hypercube Sampling Software: LHS UNIX Library Standalone Version," Sandia Technical Report SAND , July Eldred, M.S., Giunta, A.A., van Bloemen Waanders, B.G., Wojtkiewicz, S.F., Jr., Hart, W.E., and Alleva, M.P., "DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis. Version 3.0 Users Manual." Sandia Technical Report SAND , April Updated April 2003 (Version 3.1). Eldred, M.S., Giunta, A.A., van Bloemen Waanders, B.G., Wojtkiewicz, S.F., Jr., Hart, W.E., and Alleva, M.P., "DAKOTA, A (13 of 15)12/29/ :29:03 PM

217 Recent and Upcoming Publications Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis. Version 3.0 Reference Manual." Sandia Technical Report SAND , April Updated April 2003 (Version 3.1), July 2004 (Version 3.2), and December 2004 (Version 3.3). Eldred, M.S., Giunta, A.A., van Bloemen Waanders, B.G., Wojtkiewicz, S.F., Jr., Hart, W.E., and Alleva, M.P., "DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis. Version 3.0 Developers Manual." Sandia Technical Report SAND , April Updated April 2003 (Version 3.1), July 2004 (Version 3.2), and December 2004 (Version 3.3). van Bloemen Waanders, B., Bartlett, R., Long, K., Boggs, P., and Salinger, A., "Large Scale Non-Linear Programming for PDE Constrained Optimization," Sandia Technical Report SAND , October Gardner, D.R., and Vaughan, C.T., "The Optimization of a Shaped- Charge Design Using Parallel Computers," Sandia Technical Report SAND , November Hobbs, M.L., Erickson, K.L., and Chu, T.Y., "Modeling Decomposition of Unconfined Polyurethane Foam," Sandia Technical Report SAND , November Eisler, G.R., and Veers, P.S., "Parameter Optimization Applied to Use of Adaptive Blades on a Variable Speed Wind Turbine," Sandia Technical Report SAND , December McGee, B.C., Hobbs, M.L., and Baer, M.R., "Exponential 6 Parameterization for the JCZ3-EOS," Sandia Technical Report SAND , July Eldred, M.S., "Optimization Strategies for Complex Engineering Applications," Sandia Technical Report SAND , February (14 of 15)12/29/ :29:03 PM

218 Recent and Upcoming Publications Zimmerman, D.C., "Genetic Algorithms for Navigating Expensive and Complex Design Spaces," Final Report for Sandia National Laboratories contract AO-7736 CA 02 (year 2), Sept Hart, W.E., "Evolutionary Pattern Search Algorithms," Sandia Technical Report SAND , October Zimmerman, D.C., "Genetic Algorithms for Navigating Expensive and Complex Design Spaces," Final Report for Sandia National Laboratories contract AO-7736 (year 1), Sept Meza, J.C., and Plantenga, T.D., "Optimal Control of a CVD Reactor for Prescribed Temperature Behavior," Sandia Technical Report SAND , April Moen, C.D., Spence, P.A., and Meza, J.C., "Optimal Heat Transfer Design of Chemical Vapor Deposition Reactors," Sandia Technical Report SAND , April Meza, J.C., "OPT++: An Object-Oriented Class Library for Nonlinear Optimization," Sandia Technical Report SAND , March Back to top of page Questions and Comments Acknowledgment and Disclaimer Last Updated: February 3, 2004 dakota-evelopers@sandia.gov (15 of 15)12/29/ :29:03 PM

219 MDO TC Meeting Minutes (11 January 2000) PRELIMINARIES MINUTES OF THE MDO TC MEETING April 17, 2001 Seattle, WA Achille Messac called the meeting to order at 7:30 PM. Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Renaud represented Batill, Blair, Bounajem, Canfield, Chen, Cramer, DeLaurentis, Finckenor, Gurdal, Guruswamy, Khot, Long, Purcell, Smith, Stephens, Striz, Zang, Schweiger, Suleman, Toropov, Krishnamachari, Wujek. Other guests were Eldred (Sandia), Thomas (Altair), Batayneh (RPI), Ismail-Yahara (RPI), Chris Horton (AIAA). Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., names, addresss, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through the Chair in order to maintain a consistent and up to date database. Changes will be passed on to Anthony Giunta for inclusion on the web site. PRESENTATION BY Dr. Zang Dr. Zang discussed the possibility of application of knowledge management to MDO. Reno MDO-TC (January 9, 01) MEETING MINUTES REVIEWED AND APPROVED MA &O 2002 Dan DeLaurentis discussed the progress on organizing this conference, which will be held at Grand Hyatt Atlanta from 4-6 Sept The deadline for the abstracts is 11 January The General cochairs for this conference are Farrokh Mistree and Dan Schrage from GT. The Technical co-chairs for this conference are Dan DeLaurentis from GT School of AE and Pradeep Raj from Lockheed Martin Aeronautics Company. The theme of the conference will be System Affordability. SDM 2001 meeting at Seattle. Fred Stritz represented MDO TC at this conference. He discussed the number of sessions organized and (1 of 3)12/29/ :29:03 PM

220 MDO TC Meeting Minutes (11 January 2000) the number of papers presented at each session on different topics. Zafer Gurdal will represent MDO TC at the SDM long range planning committee. He mentioned that there was discussion about MDO TC representative chairing the SDM conference sometimes in the near future. SDM meeting at Denver, April Srinivas will represent the MDO TC at this Conference. Awards Committee (Canfield) Bob Canfield discussed the activities of this subcommittee regarding membership upgrades, best paper award, MDO TC award etc. Application Subcommittee (Purcel) The new subcommittee chair will be Tim Purcell. He outlined the future planned activities of the committee Publication Subcommittee (Striz) Stritz proposed a possible subcommittee effort to make the management aware of the benefits of MDO in different companies. Tony Giunta will take over the job of maintenance of MDO TC web page from Mike Eldred. MEETING SCHEDULE NEXT MEETING: Monday, January 14, 2002 at Reno, NV, 7:00-11:00 PM. The meeting was adjourned at 10:30 PM. Respectfully submitted on 12/12/2001 Narendra Khot AFRL/VASD 2210 Eighth Street Wright -Patterson AFB,OH, Tel: (937) Fax: (937) Narendra Khot@va.wpafb.af.mil (2 of 3)12/29/ :29:03 PM

221 MDO TC Meeting Minutes (11 January 2000) Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: 13 December 2001 Tony Giunta, (3 of 3)12/29/ :29:03 PM

222 MDO TC Meeting Minutes (11 January 2000) PRELIMINARIES MINUTES OF THE MDO TC MEETING January 9, 2001 Reno, NV Chairman Achille Messac called the meeting to order at 7:00 PM. Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Messac, Batill, Baysal, Cramer, Eldred, Finckenor, Gage, Grossman, Guruswamy, Khot, Striz, Stephens, Balabanov, DeLaurentis was represented by Schrage, Krishnamachari, Kodiyalam. Other guests were Zang (NASA), Reuther (NASA), Ali de-jongh (AIAA staff), Emily Springer (AIAA staff), Pete Wells (Boeing). Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through Achille in order to maintain a consistent and up to date database. Changes will be passed on to Mike Eldred for inclusion on the web site. AIAA Activity Ali de-jongh from AIAA staff talked about the congressional visit in March 2001 by the members of the TC. Achille will attend this event. Emily Springer from AIAA distributed T-shirts to the members who did not get them during the last meeting. She talked about the newly designed AIAA web page. She also mentioned that AIAA has started a three year program on selecting historical sights. Last year five sights were selected. If any one wants a particular sight to be considered for this selection, a special form has to be filled in and submitted to AIAA. Long Beach MDO-TC (September 7, 00) MEETING MINUTES REVIEWED AND APPROVED MA &O 2002 STATUS REPORT Dan Schrage discussed in detail the current status of the Georgia Tech Planning Team's effort in organizing this conference. The conference will be held at Grand Hyatt Atlanta located at Buckhead, Atlanta's most prestigious and fashionable area. The theme of the conference will be MA&O for Systems Affordability. The general co-chairs for this conference will be Farrokh Mistree and Dan Schrage. The technical programs co-chair will be Dan DeLaurentis from GT School of AE. The (1 of 3)12/29/ :29:04 PM

223 MDO TC Meeting Minutes (11 January 2000) industrial co-technical chair will be announced soon. AIAA will send out announcement for the papers in July PRESENTATION BY KRISHNAMACHARI Dr Krishnamachari from Boeing Corporation made a short presentation on the Multidisciplinary Optimization problems in Air Traffic Management. He will be presenting a paper on this topic during SDM 2001 conference at Seattle. CPSRS (Collection of Preferred Space Related Standards) Pete Wells made a short presentation on the development of CPSRS. The present SPACE standards are too many and outdated. He was seeking volunteers to participate in this endeavor. If any one of the members are interested he should visit for more information. The budget for this effort is of the order of $1 million. At present 295 reviewers, 15 countries, 155 organizations and 20 universities are going to participate in this effort. Presentation by Daniel Schrage Prof. Schrage gave an overview of the Center for Aerospace Systems Analysis (CASA) at Georgia Institute of Technology. This center combines research and education of School of Aerospace Sciences. The full time faculty is 32 with 250 graduate students and 250 undergraduate students. The function and the details about this center can be found at their web page SDM meeting at Seattle, April 2001 Fred Stritz represented the TC at this Conference. He mentioned that there will be 7 sessions on MDO at this meeting. Out of 43 abstracts submitted, 42 were accepted.the total number of sessions would be 7. There will be 2 panel discussions: 1)Use of Optimization Tools in Practical Design chaired by Dr. Balabanov, and 2) Multidisciplinary Systems Optimization Using Simulation Models chaired by Dr. Krishnamachari. MDO TC at 2002 SDM will be represented by Srinivas Kodiyalam. Future Committee Activity Four Subcommittees: Applications, Awards, Education and Publications will be headed by Tim Purcell, Bob Canfield, Kemper Lewis and Alfred Striz respectively. MEETING SCHEDULE NEXT MEETING: Tuesday April at Seattle WA, 7:00 PM-10:00 PM. (2 of 3)12/29/ :29:04 PM

224 MDO TC Meeting Minutes (11 January 2000) The meeting was adjourned at 10:30 PM. Respectfully submitted on 2/20/2001 Narendra Khot AFRL/VASD 2210 Eighth Street Wright -Patterson AFB,OH, Tel: (937) Fax: (937) Narendra Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: May 16, 2001 Michael Eldred, (3 of 3)12/29/ :29:04 PM

225 MDO TC Meeting Minutes (4 April 2000) PRELIMINARIES MINUTES OF THE MDO TC MEETING September 7, 2000 Long Beach, CA Achille Messac called the meeting to order at 7:30 PM. Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Messac, Anderson, Batill, Baysal, Chen, Eldred, Finckenor, Giesing, Grossman, Gurdal, Guruswamy, Khot, Lewis, Purcell, Stephens, Striz, Rodriguez, Suleman, Balabanov, DeLaurentis, Tappeta, Wujek, Ex-officio chairs Barthelemy and Perez represented Renaud. Other guests were Morelle, Blair, Mistree, Grandhi, Giunta, Simpson, Toropov, Schulbach (NASA), Chris Horton (AIAA). Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through Achille in order to maintain a consistent and up to date database. Changes will be passed on to Mike Eldred for inclusion on the web site. PRESENTATION BY DR. CATHY SCHULBACH Dr.Schulbach who is the project manager at Ames Research Center, made a presentation on the High Performance Computing and Communications Program started by NASA advancing the frontiers of science and technology on earth and in space.nasa's HPCC Program is a critical element of the Federal Information Technology Research and Development effort. The five project areas included in this program are Computational Aerospace Sciences (CAS), Earth and Space Sciences (ESS), Remote Exploration and Experimentation (REE), Learning Technologies (LT) and NASA Research and Education Network (NREN). The detailed information on this NASA's HPCC effort may be found on the following web pages: gov and AIAA Activity Chris Horton from AIAA announced that the MAO 2002 conference will be held at Hyatt located at Buckhed, about 40 miles from Atlanta. Mistree who is the technical chair of the conference described in detail the amenities available at this hotel and the city. (1 of 3)12/29/ :29:05 PM

226 MDO TC Meeting Minutes (4 April 2000) Atlanta MDO-TC (April 4, 00) MEETING MINUTES REVIEWED AND APPROVED MA &O 2000 General Chairman and Technical Chairman for this conference are Jean-Francois Barthelemy and Kumar Bhatia respectively. Barthelemy made a detailed presentation on organizing the conference and compared various aspects with the previous MA & O conferences.the theme of the conference was Multidisciplinary Design--Adding Value. The total number of papers submitted were 264, and 249 papers were accepted for presentation with the acceptance ratio of 94%. The number of work in progress papers were 22. Most of the papers were accepted based on the single review. Second review was initiated only for papers on the bubble. This was the first AIAA conference where AIAA Conference Management System was used to receive the abstracts and review them.barthelemy mentioned that the foreign participation in MA &O conferences has been steadily increasing while there has been steady decline of USA participants. SDM 2001 meeting at Seattle, WA. April 2001 Fred Stritz will represent MDO TC at SDM He attended SDM 2001 organization committee meeting and mentioned that there will be eight sessions available for MDO related papers including a panel session. 25 abstracts have been received until now. Gurdal who represented MDO TC at the long term planning committee of SDM, mentioned that there was discussion about MDO TC representative chairing the SDM conference sometimes in near future. Stritz proposed to have MA &O conference as add-on specialty conference similar to Dynamic specialty conference. Barthelemy proposed that we should be fully participant and not add-on to the SDM conference. These proposals were put to vote. Majority voted for fully participation in the conference. In order to pursue this matter further, ad-hoc committee was formed with Gurdal, Grossman, Grandhi, Striz and Messac as the members. Awards Committee (Kolonay) The MDO Technical Award at the MA &O 2000 conference was awarded to Dr V. B. Venkayya who is the founding member of this committee. AIAA Design Competition (Anderson) Anderson mentioned that AIAA has invited MDO to propose student competition in MDO and made a presentation on his tentative proposal. The abstract on the proposal was required to be submitted to AIAA by 10th Oct Grossman mentioned that there are already number of undergraduate student (2 of 3)12/29/ :29:05 PM

227 MDO TC Meeting Minutes (4 April 2000) competitions and graduate students do not have enough time to participate in these competitions. Committee decided not to respond to this proposal. Instead it was proposed that TC could hold best paper competition for the undergraduate student participants. The committee was formed with Anderson, Grossman, Kemper, Long and Guruswamy as the members to study the proposal. Messac discussed the results of his survey. MEETING SCHEDULE NEXT MEETING: Reno, Nevada ( date will be announced ) The meeting was adjourned at 10:30 PM. Respectfully submitted on 11/18/2000 Narendra Khot AFRL/VASD 2210 Eighth Street Wright -Patterson AFB,OH, Tel: (937) Fax: (937) Narendra Khot@va.wpafb.af.mil Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: December 21, 2000 Michael Eldred, mseldre@sandia.gov (3 of 3)12/29/ :29:05 PM

228 MDO TC Meeting Minutes (4 April 2000) PRELIMINARIES MINUTES OF THE MDO TC MEETING April 4, 2000 Atlanta, GA Achille Messac called the meeting to order at 7:30 PM. Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Renaud, Giesing, Striz, Khot, Balabanov, Baysal, Bhatia, Chen, Finckenor, Gage, Gilje, Grossman, Gurdal, Guruswamy, Kolonay, Lewis, Nagendra, Padula, Stephens, Schrage was represented by DeLaurentis. Other guests were Martinez, Tappeta (GE), Walsh (NASA), Housner (NASA), O'Leary (AIAA), Chris Horton (AIAA), Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through Achille in order to maintain a consistent and up to date database. Changes will be passed on to Mike Eldred for inclusion on the web site. PRESENTATION BY DR. JERRY HOUSNER Dr.Housner made a presentation on the Intelligent Synthesis Environment (ISE) Initiative started by NASA aimed at making substantial progress toward fulfilling the NASA Administrator's vision for revolutionizing next generation science and engineering capabilities. This initiative will achieve this vision by developing revolutionary ISE related technologies,engineering practices and coordinating related on -going NASA activities, industry activities, other government agency initiatives and university research. The set of view graphs used by Jerry may be found at the web AIAA Activity Steve O'Leary from AIAA staff discussed the plan for electronic submission of abstract, reviewing process for the future AIAA meetings. 42nd AIAA/ASME SDM conference will be the first major AIAA conference where electronic submission will be strongly encouraged. Authors having trouble submitting abstracts electronically may the abstracts. Chris Horton from AIAA discussed the possible locations for holding MAO 2002 conference. He suggested that a city like Buckhed closer to Atlanta would be more suitable than Atlanta because of the size of the hotel and the available room (1 of 3)12/29/ :29:06 PM

229 MDO TC Meeting Minutes (4 April 2000) rates. The MDO TC and MAO Organizing committee members will have to decide on the location soon. Reno MDO-TC (January 11, 00) MEETING MINUTES REVIEWED AND APPROVED MA &O 2000 Sharon Padula discussed the progress of this conference which will be held at Long Beach, Westin Hotel from 6-8 Sept Sept. 4 is the Labor Day. General Chairman and Technical Chairman for this conference are Jean-Francois Barthelemy and Kumar Bhatia respectively. The theme of the conference is Multidisciplinary Design--Adding Value. The manuscripts are due by 23rd of June. AIAA's new Conference Management System was used to receive the abstracts, evaluation etc. The total number of papers submitted were 264, and 249 papers were accepted for presentation The number of work in progress papers were 22. Most of the papers were accepted based on the single review. Second review was initiated only for papers on the bubble. The upgrade of the AIAA Conference Management System is in progress and will facilitate future conferences. SDM 2001 meeting at Seattle, WA. April 2001 Fred Stritz will represent MDO TC at SDM He attended SDM 2001 organization committee meeting and mentioned that there will eight sessions available for MDO related papers. Zafer Gurdal will represent MDO TC at the SDM organization committee. He mentioned that there was discussion about MDO TC representative chairing the SDM conference sometimes in near future. SDM meeting at Atlanta, April Khot who represented the TC at this Conference mentioned that there will be 7 sessions on MDO at this meeting. 51 abstracts were received. Out of these 46 papers were included in the seven sessions and 2 papers were rejected. The authors of the 3 papers were suggested to present their results at the postal session. These papers otherwise would have been rejected. Awards Committee (Kolonay) Ray Kolonay mentioned that there were two nominees for MDO Technical Award and he is in the process of selecting the committee. The final decision will be taken after consulting with the full TC. Future guide lines for this award will be formulated by the TC during the next meeting. Application Subcommittee (Gilje) (2 of 3)12/29/ :29:06 PM

230 MDO TC Meeting Minutes (4 April 2000) Gilje informed the TC that this meeting would be his last, and that a replacement for his sub-committee would be needed. Publication Subcommittee (Messac) Messac had written the yearly Aerospace America article for the past four years. Hovever, since he will become Chair of the TC, this effort will need to be led by another member. Messac presented a plaque to John Renaud for his excellent work as the chairman of the MDO TC committee. MEETING SCHEDULE NEXT MEETING: Thursday September 7, 2000 at Long Beach CA, 7:00-10:00 PM. The meeting was adjourned at 10:30 PM. Respectfully submitted on 6/9/2000 Narendra Khot AFRL/VASD 2210 Eighth Street Wright -Patterson AFB,OH, Tel: (937) Fax: (937) Narendra Khot@va.wpafb.af.mil Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: August 15, 2000 Michael Eldred, mseldre@sandia.gov (3 of 3)12/29/ :29:06 PM

231 MDO TC Meeting Minutes (11 January 2000) PRELIMINARIES MINUTES OF THE MDO TC MEETING January 11, 2000 Reno, NV New Chairman-Elect Achille Messac called the meeting to order at 7:00 PM. Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Khot, Balabanov, Baysal, Chen, Cramer, Eldred, Finckenor, Gage, Gilje, Grossman, Gurdal, Guruswamy, Human, Messac, Stephens, Schrage was represented by DeLaurentis, Padula was represented by Walsh. Other guests were Giunta (Sandia), Emily Springer (AIAA), Dave Culpepper (AIAA), Chris Horton (AIAA), Chris Pestak (Analex Corp.), Pete Wells (Boeing), Tom Weeks (J. of Aircraft). Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through Achille/John in order to maintain a consistent and up to date database. Changes will be passed on to Mike Eldred for inclusion on the web site. AIAA Activity Emily Springer from AIAA staff distributed T-shirts to all members who were present. Dave Culpepper, V.P. of TAC, discussed the possibility of TCs getting about $ for the TC projects. Funding will be coming from the voluntary contributions from the AIAA members. At present this project is approved for a period of three years. At the end of three years if the concept is found worthwhile, it will be extended. TAC will then put the required expenditure in their budget. He also mentioned that the TC members will be called upon to help review the papers in the future that will be sent in.pdf format. Chris Horton from AIAA mentioned that there is no possibility of holding MAO 2002 conference in Atlanta because of the restricted number of attendees and the anticipated expenditure (That statement has evolved since then). The MDO TC would probably have to select some other city. In this respect Chris Pestak from Analex, Clevaland made a pitch for holding the MAO2002 at Renaissance Cleveland Hotel, which satisfies most of the MAO conference requirements. The MDO TC and MAO Organizing committee members will have to decide on the location soon. St. Louis MDO-TC (September 12, 99) MEETING MINUTES REVIEWED AND APPROVED (1 of 3)12/29/ :29:08 PM

232 MDO TC Meeting Minutes (11 January 2000) PRESENTATION BY DR. TOM WEEKS, EDITOR OF JOURNAL OF AIRCRAFT Dr. Weeks discussed the scope of the Journal. He wants the TC's help in identifying and motivating reviewers. The TC generated reviewer list would be useful. Also, authors who present papers at the conferences need to be identified and motivated to submit the papers to the journals. He also mentioned that there will be a special issue in year 2003 in celebration of the Wright Brothers first flight a hundred years ago. He is seeking suggestions on history papers, topics and possible authors. MA &O 2000 Joanne Walsh discussed the progress. This conference will be held at Long Beach Westin Hotel from 6-8 Sept Sept 4 is the Labor Day. Session will be finalized by 3rd of March and the manuscripts are due by 23rd of June. Bernie Crossman mentioned about the Meeting held at Air Vehicle Directorate regarding the Energy Methods in Design methodology. Khot will get in contact with Dr. David Moorhouse to check whether he would propose a special session at MA& O conference. CPRS (Collection of Preferred Space Related Standards) Pete Wells made a short presentation on the development of CPRS. The present SPACE standards are too many and outdated. He was seeking volunteers to participate in this endeavor. If any one of the members are interested he should visit for more information. Fall Internet Meeting Mike Eldred briefed on the fall internet meeting. Some members had problems logging into the system or were reluctant to visit the OneList commercial Web site from work computers. Ideas to improve future internet meetings and the MAO2002 contingency plan were discussed. SDM meeting at Atlanta, April Khot who represented the TC at this Conference mentioned that there will be 7 sessions on MDO at this meeting. The total number of papers would be 46. The conference will be for a period of four days with sessions on Thursday afternoon. Design Engineering TC Vladimir Balabanov who is the member of this committee suggested to have joint meeting in order to make this committee aware of the MAO activity. Gurdal and Messac volunteered to attend Design Engineering TC meeting at Atlanta in April 2000 during SDM conference. (2 of 3)12/29/ :29:08 PM

233 MDO TC Meeting Minutes (11 January 2000) Associate Fellows Following members were selected to be Associate Fellows of AIAA: Jean-Francois Barthelemey, Todd Beltracchi, Christina Bloebaum, Robert Canfield, Farrokh Mistree and John Renaud. Congratulations to these present and past members. Future Committee Activity The new chairman of the committee Achille Messac initiated a discussion on the future projects the TC should consider initiating in order to make MDO activity known to the AIAA community. Peter Gage volunteered to write down the points of discussion. He would send the list of items to all the members for their comments. MEETING SCHEDULE NEXT MEETING: Tuesday April at Atlanta Ga., 7:00 PM-10:00 PM. The meeting was adjourned at 10:30 PM. Respectfully submitted on 3/02/2000 Narendra Khot AFRL/VASD 2210 Eighth Street Wright -Patterson AFB,OH, Tel: (937) Fax: (937) Narendra Khot@va.wpafb.af.mil Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: March 22, 2000 Michael Eldred, mseldre@sandia.gov (3 of 3)12/29/ :29:08 PM

234 MDO TC Meeting Minutes (12 January 1998) MINUTES OF THE MDO TC MEETING April 12, 1999 St Louis, MO PRELIMINARIES Chairman John Renaud called the meeting to order at 7:30 PM. Nelson Wolf who represented Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Renaud, Stritz, Bhatia, Eastep, Gilje, Iqbal, Kodiyalam,Kolonay, Lewis, Livne, Long, Messac,Orozco, Padula, Purcell,Balabanov. Other guests were Wolf,Grandhi,Zailar,Mavris,Venkayya,Guruswamy. Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through John in order to maintain a consistent and up to date database. Changes will be passed on to Mike Eldred for inclusion on the website. MA&O CONFERENCE 2000 Jean-Francois Barthelemy discussed the details of this meeting which will be held at Long Beach, CA, Sept 6-8.He mentioned that the increased focus will be on applications, pursue third party vendors, invite state-of the art papers, special presentations etc. He also discussed the paper review process. SDM CONFERENCE 99 Srinivas Kodiyalam who represented MDO TC at this conference, mentioned that he had received a total of 33 abstracts. Each paper was reviewed by 3 reviewers. 32 papers were accepted and were divided into 6 sessions. Narendra Khot will be TC representative at SDM 2000 conference. WAC 99 John mentioned about the call for papers at this conference. AEROSPACE SCIENCES (1 of 4)12/29/ :29:09 PM

235 MDO TC Meeting Minutes (12 January 1998) Achille Messac represented TC at this conference. He has sent requests for the papers and he is looking forward for good papers. ISSMO Kemper Lewis gave the details of the conference which will take place in May The registration fee for this conference will be $ Tennis and golf tournaments are planned after the conference. MA&O Conference John Renaud mentioned that he will send out the call for nominations for chairs on private MDO , to organize this conference. The procedure was voted acceptable by the members. TC OPERATION John Renaud showed TC Operations and TC structure chart. He asked for publication lead to replace Eli Livne. He mentioned that replacements for new officers and co-chairs will be elected by this summer. BREAKOUT SESSION The members were asked to break into small groups to come up with the action items for MDO. Following were the tentative action items suggested by the groups: Educate people about optimization and MDO. Survey AIAA members about MDO use. Educate starting with H. S., Colleges, Work Places, Managers etc. Optimization demos to show its usefulness. How to Educate teachers to teach the subject. MDO articles; how is it helpful. Sponser design contests. MDO committee publish benefits -- How much did it improve product. Put together Web Page on MDO benefits. Action items : Put some abstracts on the Web-- John will check this out. Out reach to other TC's about MDO value John will consider these and suggest a three year plan. He will try to have it ready for the next TC Chairman. (2 of 4)12/29/ :29:09 PM

236 MDO TC Meeting Minutes (12 January 1998) SUBCOMMITTEE REPORTS Awards Subcommittee (Kolonay) Ray Kolonay had proposal for modifications to MDO award selection procedures. Move to accept the proposal for selecting the MDO award was made. This was passed by votes. He wanted suggestions for AIAA Fellow nominations by the MDO committee. Application Subcommittee (Gilje) Ron Gilje would put the report on the Web. Education (Messac) Achille Messac discussed the progress of MDO article in Aerospace America and MDO Course. Benchmarking Subcommittee (Lewis) Kemper Lewis has set up MDO TEST SUITE on the web ( mod.test/index.html). He is planning to add more bench mark problems on the Web. Strategic Committee John Renaud mentioned that he wants someone to represent MDO TC at this committee. MEETING SCHEDULE NEXT MEETING: World Aviation Congress Oct 1999 in San Franscisco. The meeting was adjourned at 10:00 PM. Respectfully submitted on 7/10/99 Narendra Khot AFRL/VASD 2210 Eighth Street Wright -Patterson AFB,OH, Tel: (937) Fax: (937) Narendra Back to Meeting Minutes list Back to MDO TC Home Page (3 of 4)12/29/ :29:09 PM

237 MDO TC Meeting Minutes (12 January 1998) Last Updated: October 13, 1999 Michael Eldred, (4 of 4)12/29/ :29:09 PM

238 MDO TC Meeting Minutes (12 January 1998) PRELIMINARIES MINUTES OF THE MDO TC MEETING January 11, 1999 Reno, NV Chairman John Renaud called the meeting to order at 7:00 PM. Nelson Wolf who represented Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Renaud, Stritz, Balling, Bayard, Baysal, Eldred, Finckenor, Gage, Ghattas, Gilje, Grossman, Gurdal, Human, Kolonay, Livne, Majumdar, Messac, Mosher, Santangelo, Schrage was represented by DeLaurentis, Lewis was represented by Bloebaum (WCSMO3). Other guests were Riddie, LeGresley, Ovens, Townsend, Sobieski, Artcliff, Emily Davies (AIAA), Tom Weeks (J. of Aircraft). Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through John in order to maintain a consistent and up to date database. Changes will be passed on to Mike Eldred for inclusion on the website. PRESENTATION: Optimization Activities at Sandia National Laboratories Mike Eldred made a presentation on the activities of Sandia National Labs in the area of optimization software and on the development of parallel optimization methods for the Accelerated Strategic Computing Initiative (ASCI). He overviewed the capabilities of the DAKOTA software under development at Sandia and highlighted the exploitation of multiple levels of parallelism which results in near-linear scaling on massively parallel computers containing thousands of processors. St. Louis MDO-TC (September 1, 98) MEETING MINUTES REVIEWED AND APPROVED PRESENTATION BY AIAA STAFF Emily Davies updated the TC on AIAA activities. AIAA has now over 30,000 members, 19 lifetime members. This year 30 fellows were selected. PRESENTATION BY DR. TOM WEEKS, EDITOR OF JOURNAL OF AIRCRAFT (1 of 4)12/29/ :29:10 PM

239 MDO TC Meeting Minutes (12 January 1998) Dr. Weeks discussed the scope of the Journal. He wants the TC's help in identifying and motivating reviewers. TC generated reviewer list would be useful. Also, authors who present papers at the conferences need to be identified and motivated to submit the papers to the journals. WHITE PAPER John discussed action on the white paper. White paper would be on the web in March He would like to receive comments. MA &O 2000 John stated 2000 MA & O meeting-site selection still is on going. He suggested a motion that 3 years prior to the future meetings Conference Chairman be selected. Fred Stritz seconded the motion. Motion was passed. WCSM03 Bloebaum discussed the progress of the conference. The details of the conference can be found on the web CANDIDATES FOR AIAA DIRECTOR-AT-LARGE Dr. Richard Antcliff and Mr. Anthony Gross, who are standing for election for the positions of directorat-large, distributed handouts giving the summary of their education and experience. SUBCOMMITTEE REPORTS Awards Subcommittee (Ghattas) Omar discussed the procedure he is following on selection of best paper from MAO98. The award will be presented at MAO2K.He discussed the roll of TC in nomination for AIAA fellow award and wants the members to send names of the potential nominees for AIAA fellow. The voting will take place during the committee meeting at SDM99. Congratulations to Rudi Yurkovich past TC member who was selected fellow this year. Ray Kolonay will be taking over the chairmanship of this committee after SDM 99 conference SDM meeting at St Louis April John mentioned that there will be 6 sessions on MDO at this meeting. Srinivas Kodiyalam was the TC representative at this conference. Narendra Khot will be the TC representative at SDM 2000 conference. Publications Subcommittee (Livne) (2 of 4)12/29/ :29:10 PM

240 MDO TC Meeting Minutes (12 January 1998) Eli Livne discussed the progress on the special issue of Journal of Aircraft on MDO in Aerospace Context. Membership(Balling) He discussed the status of membership. The maximum number of members is limited to 35. Benchmarking Subcommittee (Lewis) Kemper Lewis has taken over as chairman of the subcommittee. The subcommittee report was distributed by Kemper. The details are posted on the MDO TC AIAA web page. The test suite of MDO problems developed at the MDO Branch of NASA Langley Research Center can be accessed on the web under URL ( Kemper mentioned that he has been made aware by other researchers and graduate students that there are errors in some of the problems. Some effort is going into correcting the existing problems. World Aviation Congress 99 John mentioned that he is organizing two sessions on MDA&O and looking to get ten papers.the abstracts for this conference are due by 15 Jan He would like to know if anyone would be interested in presenting a paper. Application Subcommittee(Gilje) Gilje outlined the objectives of the committee and the planned contents of the report. He had some problems hearing from some of the committee members. The committee progress has been posted on the web page. Liaison Subcommittee (Grossman) Grossman will send web site information to Mike Eldred. MEETING SCHEDULE NEXT MEETING: Monday April at St. Louis, Mo, 7:00 PM-11:00 PM. The meeting was adjourned at 11:30 PM. Respectfully submitted on 3/12/99 Narendra Khot AFRL/VASD 2210 Eighth Street Wright -Patterson AFB,OH, (3 of 4)12/29/ :29:10 PM

241 MDO TC Meeting Minutes (12 January 1998) Tel: (937) Fax: (937) Narendra Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: April 8, 1999 Michael Eldred, (4 of 4)12/29/ :29:10 PM

242 MDO TC Meeting Minutes (4 April 1997) PRELIMINARIES MINUTES OF THE MDO TC MEETING SEPTEMBER 1, 1998 St. Louis, MO Chairman John Renaud called the meeting to order at 7:00 PM. Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Renaud, Giesing, Striz, Khot, Eastep, Majumdar, Kolonay, Suleman, Messac, Morris, Padula, Petiau, Grossman, Gage, Orozco, Finckenor, Smith, Gilje, Eldred, Gurdal, Stephens, Nagendra, Kodiyalam, Karpel and Schrage. Other guests were Grandhi (Past Member), Canfield (Past Member), Brewster King (AIAA), Chenevey (AIAA), Cramer (Boeing), Shimko (Universal Analytics), Platnick (Universal Analytics), Yurkovich (Boeing), Stettner (NASA). Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through Renaud, in order to maintain a consistent database. Changes will be passed on to Mike Eldred for inclusion on the website Long Beach MDO-TC (April 98) MEETING MINUTES REVIEWED AND APPROVED PRESENTATION: ASTROS OPTIMIZATION SOFTWARE Joseph Platnick made a presentation on the capabilities of ASTROS (Automated STRuctural Optimization System) program.this is a finite element-based software that has been designed to assist, to the maximum practical extent, in the preliminary design of aerospace structures. ASTROS supports the multidisciplinary nature of design by implementing the disciplines in separate modules and by the use of MAPOL (Matrix Analysis Problem Oriented Language), concerning a high level language, to direct the interaction among the modules. This software ASTROS Version 20.1 at presented is marketed by Universal Analytics, Inc.Torrance, California. PRESENTATION BY AIAA STAFF Brewster King and Cathy Chenevey discussed the possible locations and the problems in selecting the Hotel for MA&O 2000 meeting. (1 of 4)12/29/ :29:11 PM

243 MDO TC Meeting Minutes (4 April 1997) MA&O CONFERENCE Bob Canfield (Technical Chair) discussed his experience in the organization of the MA&O 1998 conference. This was the first AIAA conference where electronic abstracts submission was used. He mentioned that 305 abstracts were received, 279 papers were accepted and 24 papers were withdrawn. There were 50 papers from Europe, 23 work-in -progress. Ramana Grandhi (General Chair)mentioned that MA&O 2000 will be organized by Drs. Jean -Francois Barthelemy and Kumar Bhatia, since they received maximum votes from the committee members. This proposal was put to motion and committee approved it. Grandhi recommended that M&O 2002 be organized by Profs. F. Mistree and D. Schrage which was the second team who had shown interest in organizing MA&O However,the committee recommended that this should be finalized by the future TC and not the present one. MDO WHITE PAPER PROPOSAL FOR 1998 Joe Giesing discussed the papers to be presented in the two special sessions on Industry MDO Applications and Needs. There would be 11 papers and one summary paper which was authored by Giesing and Barthelemy. All the papers presented in the two sessions will constitute AIAA MDO TC white paper. The summary paper will be put on the web. Renaud suggested that TC members should submit their comments on all the papers to Giesing so that he can get them finalized. Renaud will get in touch with Livne to check whether the summary paper can be published in the Journal of Aircraft in his special issue. SUBCOMMITTEE REPORTS Awards Subcommittee (Ghattas) Omar Ghattas did not attend the meeting. Renaud had received from Omar discussing the progress of his committee.the TC- supported AIAA Fellow nomination package for Chris Borland. The 1998 MDO Award will be presented to Prof. Raphael Haftka.The 6th MAO Symposium Best Paper Award will be presented to :V. Balabanov, M Kaufma, D Knill, D. Haim, O. Golovidov, a. Giunta, R. Haftka, B.Grossman, W, Mason, and L. Watson, for their paper titled, "Dependence of Optimal Structural Weight on Aerodynamic Shape for a High Speed Civil Transport", AIAA Paper Conference Support Subcommittee (Chair Vacant at Present) Srinivas Kodiyalam, TC representative at 1999 SDM conference mentioned that he had received 33 papers and their will be 6 sessions at the conference on MDO related topics. Narendra Khot has agreed to be the TC representative at 2000 SDM conference. ISSMO (Padula) Padula discussed the progress on organizing this conference, which will be held at Niagara Falls on May 17-21, The abstracts for this conference are due by 30 Oct (2 of 4)12/29/ :29:11 PM

244 MDO TC Meeting Minutes (4 April 1997) Publication Subcommittee (Livne) Livne was not present. Renaud received discussing the progress of his subcommittee. 28 papers for the special issue of J of Aircraft have been reviewed and are sent to publication. The estimated date of publication is Jan/Feb Messac will be writing a MDO review article for the Aerospace America. Education Subcommittee (Renaud) John Renaud put the motion to the floor to approve the new charter which was put on the web. The motion was passed. Internet Subcommittee (Eldred) Mike talked about the updates to the web page. He mentioned that new member roster is on the web. Mike will get in contact with new members to get their Bio data. Liaison Subcommittee (Grossman) Bernie discussed the need for members to represent MDO TC at other TC committees. Application Subcommittee (Gilje) Gilje outlined the progress of the committee. Benchmarking Subcommittee (Striz) Fred Striz discussed the progress of his subcommittee on selecting the benchmark problems. ACTION ITEM:All subcommittee chairs are requested to put their progress reports on the web so that the interested members can get the details.. MEETING SCHEDULE NEXT MEETING: Jan 11, Monday (7:00PM-11:00PM)at Reno, NV. Renaud presented a plaque to Jean-Francois Barthelemy for his excellent work as the chairman of the MDO TC committee. The plaque was received by Padula since Barthelemy was not present Respectfully submitted on 10/13/98, Narendra Khot AFRL/VASD 2130 Eighth Street, Ste 1 Wright-Patterson AFB. OH, Tel: (937) Fax: (937) (3 of 4)12/29/ :29:11 PM

245 MDO TC Meeting Minutes (4 April 1997) Business Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: December 11, 1998 Michael Eldred, (4 of 4)12/29/ :29:11 PM

246 MDO TC Meeting Minutes (20 April 1998) PRELIMINARIES MINUTES OF THE MDO TC MEETING April 20, 1998 Long Beach, CA Chairman Jean-Francois Barthelemy called the meeting to order at 7:00 PM. Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Barthelemy, Giesing, Eldred, Eastep, Briggs, Striz, Messac, Rais-Rohani, Canfield, Grandhi, Iqbal, Renaud, Majumdar, Haftka, Gurdal, Khot, Livne, Bhatia, Karpel, Bolognese, Human, Gilje Mazzaway and Rocha. Other guests were Sharon Padula, Jonathan Bishop, Pramod Rao Bangarpet,Tom Zielen, Mike Long, Resende, Brewster King (AIAA). Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through Renaud, in order to maintain a consistent database. Changes will be passed on to Mike Eldred for inclusion on the website. Reno MDO-TC (Jan 98) MEETING MINUTES REVIEWED AND APPROVED PRESENTATION: OPTIMIZATION AT VMA ENGINEERING Gary Vanderplatts made a presentation concerning the optimization services and software offered by VMA Engineering, Inc. He gave historical background on the developement of GENESIS program, its new analysis and design capabilities. He also mentioned that GENESIS PC version is now available He discussed the capabilities of the general purpose numerical optimization software DOC/DOT. The company has a web site ( PRESENTATION BY AIAA STAFF Brewester King discussed the possible locations and the problems in selecting the Hotel for MA&O 2000 meeting. The final decision will be made after the selection of the Chair for this conference. MA&O CONFERENCE (1 of 3)12/29/ :29:12 PM

247 MDO TC Meeting Minutes (20 April 1998) Bob Canfield (Technical Chair) discussed in detail the progress in the organization of the conference. He mentioned that 257 papers have been accepted for presentation at the conference. The organization plan is on schedule. The detailed program will be published in June 1998 Aerospace America. Ramana Grandhi gave general overall picture of the conference mentioning the names of the keynote speakers and award luncheon speaker. MDO WHITE PAPER PROPOSAL FOR 1998 Joe Giesing discussed the proposed white paper. This paper will emphasize real-world problems, mainly taken from industrial projects. Nine draft papers have been received. The summary paper will be written by Giesing and Barthelemy. The invited papers will be presented in two sessions in St. Louis at the MA&O conference. SUBCOMMITTEE REPORTS Awards Subcommittee (Ghattas) Omar Ghattas did not attend the meeting. The TC nomination for AIAA Fellow was discussed. ACTION ITEM: Omar will send everyone s with information on the nominees, and voting will be done electronically. Conference Support Subcommittee (Chair Vacant at Present) Srinivas Kodiyalam will be TC representative at 1999 SDM conference. Narendra Khot has agreed to be the TC representative at 2000 SDM conference. Publications Subcommittee (Livne) Eli Livne is working with Tom Weeks to put together a Journal of Aircraft issue on MDO. He mentioned that 13 papers have been received in final form and 6 papers are due within a month. It will be about two weeks before the work will be completed. Education Subcommittee (Renaud) MDO TC committee charter has been placed on the web. Sharon Padula will take over the chairmanship of this committee since Renaud will be the new TC Chairman. ACTION ITEM: Each subcommittee chair should review the subcommittee function discussion in the charter and send their suggestions and comments to Renaud. It is suggested that the chairman of the committees should consider holding meetings with their members using phone system to discuss the agenda and the progress. Internet Subcommittee (Eldred) Mike talked about the updates to the web page, MDO related web sites and discussed the MDO Electronic Mailing Lists details as posted on the web. (2 of 3)12/29/ :29:12 PM

248 MDO TC Meeting Minutes (20 April 1998) Membership(Balling) Richard mentioned the names of the new members. He will get in contact with the new members and suggest that they get involved in the subcommittee tasks of their interest. Application Subcommittee (Gilje) Gilje outlined the objectives of the committee. He mentioned that even though he has retired from TRW he would like to continue his work with the committee. Benchmarking Subcommittee (Striz) Fred Striz discussed the progress of his subcommittee on selecting the benchmark problems. MEETING SCHEDULE NEXT MEETING: Sep 1, Tuesday (7:00PM-11:00PM) and Sep 3, Thursday (7:30PM-9:30 PM) at HYATT REGENCY UNION STATION, St. Louis, MO. This was the last day for Jean-Francois as the chairman of the committee. All members present at the conference applauded before the meeting was adjourned at 11:15 hours. Respectfully submitted on 5/13/98, Narendra Khot AFRL/VASD 2130 Eighth Street, Ste 1 Wright-Patterson AFB. OH, Tel: (937) Fax: (937) Business khotns@wl.wpafb.af.mil Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: May 27, 1998 Michael Eldred, mseldre@sandia.gov (3 of 3)12/29/ :29:12 PM

249 MDO TC Meeting Minutes (12 January 1998) PRELIMINARIES MINUTES OF THE MDO TC MEETING January 12, 1998 Reno, NV Chairman Jean-Francois Barthelemy called the meeting to order at 7:00 PM. Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Barthelemy, Giesing, Renaud, Khot, Grandhi, Grossman, Livne, Majumdar, Gilje, Kolonay, Gage, Agrawal was represented by Unger, Balling, Canfield, Eastep, Fadel, Ghattas, Mazzawy, Peraire, Santangelo, Schrage was represented by Olds and Mosher. Other guests were Brewster King (AIAA), Ray Chatman (AIAA), Tom Weeks (J. of Aircraft), C. L. Bloebaum (ISSMO 99). Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through Jean-Francois, in order to maintain a consistent and up to date database. Changes will be passed on to Mike Eldred for inclusion on the website. St. Louis MDO-TC (October 9, 97) MEETING MINUTES REVIEWED AND APPROVED PRESENTATION BY AIAA STAFF Brewster King discussed the opportunities the TC has to organize short courses (2-5 days) or tutorials ( 1 day) and the time table for implementation of these professional development courses. Ray Chatman discussed the scholarship programs developed by AIAA for undergraduate and graduate students. At present 20 undergraduate scholarships ($1000 each) and 5 graduate scholarships ($5000 each) are being awarded by AIAA. The information regarding this program has been sent to the universities. This program will be expanded as new endowments will be coming. PRESENTATION BY DR. TOM WEEKS, EDITOR OF JOURNAL OF AIRCRAFT Dr. Weeks discussed the scope of the Journal and mentioned that he is primarily interested in papers on applied aircraft technology. He wants TC's help in identifying and motivating reviewers. Also, authors who present papers at the conferences need to be identified and motivated to submit the papers to the journals. He also mentioned that the page limit on survey papers has been removed. In addition, he (1 of 4)12/29/ :29:12 PM

250 MDO TC Meeting Minutes (12 January 1998) requested from the TC on how the publication process can be improved. ACTION ITEM: Messac will follow-up on his idea of last year to ping the members for their preference as reviewer and communicate the information to the appropriate Associate Editors. MA&O CONFERENCE Bob Canfield (Technical Chair) discussed the format, the procedure he is going to follow to get the papers reviewed and the time table the super chairs should adhere to, in order to get the summary rating sheets back to him either by mail or internet by 28 Feb He mentioned that the MAO planning is on schedule up until now. ACTION ITEM: Todd Mosher will get in contact with Bob Canfield to discuss the procedure followed by IEEE to receive the abstracts and check the status regarding acceptance of paper. ACTION ITEM: Ghattas will provide Grandhi a point of contact in the Dept of Energy for inviting a speaker on the subject of High Speed Computing. MDO WHITE PAPER PROPOSAL FOR 1998 Joe Giesing discussed the proposed white paper. This paper will emphasize real-world problems, mainly taken from industrial projects. The format has been changed from a single report to a series of invited papers accompanied by a summary paper. The invited papers will be presented in two MA&O sessions. Papers will stress the use of MDO, bring up industrial needs, or point out areas where MDO could have been used to enhance the design process. Eight abstracts have been received, one is eminent and three are in progress. There will be two full sessions covering these invited papers and the summary paper. ACTION ITEM: Joe Giesing and Jean-Francois Barthelemy will write the summary paper for presentation at the conference and subsequent editing by the TC. MA &O Chair/Technical Chair team will send a call for nomination between ASM and SDM to past and current TC members for proposals to organize the conference and select the sight. Between SDM and MDO Chair/Technical Chair will review and prioritize the proposals. The General Chair, Tech Chair and the location will be announced at 1998 MA&O 1998 meeting at St. Louis. ACTION ITEM: Barthelemy will communicate to Grandhi the procedure for selection of the 2000 MA&O team. SUBCOMMITTEE REPORTS (2 of 4)12/29/ :29:12 PM

251 MDO TC Meeting Minutes (12 January 1998) Awards Subcommittee (Ghattas) Omar Ghattas discussed the roll of TC in nomination for AIAA fellows award. He will put on the web the procedure TC plans to follow. Nominations for MDO Award are due by Jan Aerospace Sciences Meeting Jan Three sessions are planned at this meeting related to MDO. Publications Subcommittee (Livne) Eli Livne discussed the progress on the special issue of Journal of Aircraft on MDO in Aerospace Context. There will be about papers. Education Subcommittee (Renaud) Renaud distributed draft copy of the charter for MDO TC operating plan. He will put this on the web. TC members should take a look at the draft and send their comments to Renaud. Membership(Balling) 16 new applicants have been received to become TC members. The recommendations for these applicants are as follows: 9 members, 3 associate members and 4 will be denied memberships at present. Benchmarking Subcommittee (Striz) The subcommittee report was distributed by Renaud. At present the members of this committee are Haftka, Majumdar, Messac, Renaud and Morris. If any one is interested in becoming the member of this subcommittee should get in contact with Striz. The test suite of MDO problems developed at the MDO Branch of NASA Langley Research Center by Sharon Padula and her associates can be accessed on the web under URL ( World Aviation Congress 98 Bill Bickard from Boeing Long Beach was looking for a TC member to organize a session on MDO taking into consideration needs of the practical designers. He needs information regarding the title of the papers etc. by May The information will be put on the web. Dan Schrage will represent MDO TC at the Aircraft Technology Integration and Operation meeting at the WAC. Application Subcommittee(Gilje) Gilje outlined the objectives of the committee, the planned contents of the report and plans for publication of the report. The main objective of this committee is to communicate, educate internally and externally within the general public MDO concepts. (3 of 4)12/29/ :29:12 PM

252 MDO TC Meeting Minutes (12 January 1998) MEETING SCHEDULE NEXT MEETING: Monday April at Long Beach, CA, 7:00 PM-11:00 PM. The meeting was adjourned at 11:30 PM. Respectfully submitted on 2/2/98, Narendra Khot WL/FIBD 2130 Eighth Street, Ste 1 Wright -Patterson AFB,OH, Tel: (937) Fax: (937) khotns@fltvc1.flight.wpafb.af.mil Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: February 17, 1998 Michael Eldred, mseldre@sandia.gov (4 of 4)12/29/ :29:12 PM

253 MDO TC Meeting Minutes (9 October 1997) PRELIMINARIES MINUTES OF THE MDO TC MEETING October 9, 1997 St. Louis, MO Chairman Jean-Francois Barthelemy called the meeting to order at 8:10 AM. Narendra Khot recorded the minutes. There was an introduction of members and guests. Members present were: Barthelemy, Giesing, Yurkovich, Eldred, Briggs, Striz, Messac, Rais-Rohani, Iqbal, Kodiyalam, Renaud, Haftka, Khot, Bhatia, Ghattas, Gilje, Grossman, Schrage, Mazzaway, Human and Bolognese. Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through Jean-Francois, in order to maintain a consistent database. Changes will be passed on to Mike Eldred for inclusion on the website. KISSIMMEE MDO-TC (APRIL 97) MEETING MINUTES REVIEWED AND APPROVED PRESENTATION: isight at ENGINEOUS SOFTWARE Inc. Srinivas Kodiyalam made a presentation concerning the Compuer Aided Optimization (CAO) software which is under developement at Engineous Software Inc.The software would be used for Design Automation, Design Integration and Design Optimization with least effort to switch from one to other commericially or in-house developed software. The program is being marketed and at present is being used by the industry and the govermental agencies. The software uses MDOL language. Members who attended this meeting are requested to send their comments to Jean-Francois Barthelemy. MA&O CONFERENCE Ramana Grandhi (General Chair) and Bob Canfield (Technical Chair) were unable to attend the meeting due to the last minute unforseen difficulties. Rudy Yurkovitch discussed the location of the conference and the support he would be getting from his company regarding permiting interested engineers from the company to attend the conference.he mentioned that about 94 persons attending the conference would be able to visit Boeing to see the PROLOG Room and military aircraft assembly lines. (1 of 4)12/29/ :29:13 PM

254 MDO TC Meeting Minutes (9 October 1997) MDO WHITE PAPER PROPOSAL FOR 1998 Joe Giesing discussed the proposed white paper. This paper will emphasize real-world problems, mainly taken from industrial projects. The format has been changed from a single report to a series of invited papers accompanied by a summary paper. The invited papers will be presented in two MA&O sessions. Papers will stress the use of MDO, bring up industrial needs, or point out areas where MDO could have been used to enhance the design process.five abstracts have been received and three are in progress. There will be two full sessions covering these invited papers ACTION ITEM: Joe Giesing and Jean -Francois Barthelemy will write the two page summary for distribution during the sessions at the MA&O Conference. ACTION ITEM: Joe Geising,Bob Canfield and Ramana Grandhi will get in contact to discuss the session organization,time etc SDM AIAA CONFERENCE Bhatia discussed the session organization of the papers under MDO at this conference. 49 abstracts were received and out of these 38 papers were accepted. Six sessions have been organized. Chair and co-chair persons have been selected.bhatia will get in contact with these persons to confirm their acceptance. SUBCOMMITTEE REPORTS Awards Subcommittee (Ghattas) Omar Ghattas discussed the roll of TC in nomination for AIAA fellows award. He will put on the web the procedure TC plans to follow. This will be voted by the TC during the Reno meeting. Conference Support Subcommittee (Chair Vacant at Present) Bhatia suggested that TC should select representative for 1999 AIAA SDM meeting. Srinivas Kodiyalam has agreed to take this responsibility. MDO TC is not in the current SDM conference chair rotation. It was recommened that TC should send a formal letter to AIAA, stating that the committee is not in favor of becoming the conference chair. ACTION ITEM : Bhatia and Barthelemy will prepare the formal letter to be sent to AIAA regarding TC's unwillingness to become member of SDM conference chair rotations Publications Subcommittee (Livne) Eli Livne could not attend the meeting. However he communicated the message that he is making good progress on putting a special issue of Journal of Aircraft on MDO. (2 of 4)12/29/ :29:13 PM

255 MDO TC Meeting Minutes (9 October 1997) Achille Messac will start and initiate a discussion on what is MDO and which is the proper terminology. He seeks contributions from the members. He plans to organize and condense the response. Education Subcommittee (Renaud) There is no formal charter for MDO TC with AIAA. ACTION ITEM :Barthelemy and Renaud will draft a formal charter for MDO TC for sending to AIAA. The draft will be ready for Reno meeting. Internet Subcommittee (Eldred) Mike talked about updates to the web page.call for papers for MA&O meeting is on the web. MDO and optimization related web sites have been listed on the web. The list contains information from the universities, industry and the goverment agencies. Liaison Subcommittee (Fadel) Clark Briggs mentioned that the Design Engineering TC report has been put on the web. Benchmarking Subcommittee (Striz) Fred Striz reported his progress on selecting the problems for this task. He is of the opinion that these bench mark problems should be put on the web for easy access. He will have more on this to say during the Reno meeting. World Aviation Congress Dan Schrage will represent MDO TC at the Aircraft Technology Integration and Operation meeting at the WAC. Special Thanks to Rudy Yurkovitch for arranging the meeting at the Boeing Company, and providing the bus from the hotel and to the airport.he also gave attending TC members tour of the PROLOG room, a virtual reality dome and the military aircraft final assembly building. MEETING SCHEDULE NEXT MEETING: Monday Jan. 12, 1998 at Reno Hilton in Reno, NE, 7:00 PM-11:00 PM. The meeting was adjourned at 12:00 PM.. Respectfully submitted on 10/22/97, Narendra Khot WL/FIBD 2130 Eighth Street, Ste 1 (3 of 4)12/29/ :29:13 PM

256 MDO TC Meeting Minutes (9 October 1997) Wright -Patterson AFB,OH, Tel: (937) Fax: (937) Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: October 28, 1997 Michael Eldred, (4 of 4)12/29/ :29:13 PM

257 MDO TC Meeting Minutes (4 April 1997) PRELIMINARIES MINUTES OF THE MDO TC MEETING April 4, 1997 Kissimmee, FL Chairman Jean-Francois Barthelemy called the meeting to order at 7:05 PM. Allan Goforth recorded the minutes. There was an introduction of members and guests. Members present were: Barthelemy, Goforth, Giesing, Yurkovich, Eldred, Fadel, Thomas, Eastep, Briggs, Striz, Messac, Rais-Rohani, Kolonay, Martin, Canfield, Grandhi, Iqbal, Renaud, Majumdar, Haftka, Gurdal, Khot, Livne, Bhatia, Karpel, Ghattas, and Rocha. Member Gilje was represented by Dean Waldie (TRW). Other guests were Prabhat Hajela (RPI), Jaroslaw Sobieski (NASA LaRC), Keram Nazari (Altair Computing), Larry Pinson (MRJ Tech. Solutions), Emily Davies (AIAA), Brewster King (AIAA), and Joanna Spar (AIAA). Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. It was noted that corrections should come through Jean-Francois, in order to maintain a consistent database. Changes will be passed on to Mike Eldred for inclusion on the website. RENO MDO-TC (JAN 97) MEETING MINUTES REVIEWED AND APPROVED PRESENTATION: OPTIMIZATION AT ALTAIR COMPUTING Harold Thomas made a presentation concerning the optimization services and software offered by Altair Computing, Inc. Altair does structural optimization work under contract for the Big Three automobile makers using commercial software packages such as Genesis and MSC/NASTRAN. In addition, Altair has it's own software products. These are Hypermesh, a pre/post processor similar to PATRAN, and Optistruct, which does topology optimization. The company has a website ( PRESENTATION: AIAA BUSINESS DEVELOPMENT Emily Davies outlined the restructured (flat) organization of AIAA and the new emphasis on business development. Results from last year's survey of the membership by market analysts were discussed. Response to the calendar survey was excellent. Brewster King talked about business development. He works with the TC's to improve the conferences and define new technical areas that AIAA should get (1 of 5)12/29/ :29:14 PM

258 MDO TC Meeting Minutes (4 April 1997) involved with. He is also interesting in developing new ideas for continuing education courses. PRESENTATION: CONGRESSIONAL VISIT DAY Larry Pinson discussed the AIAA Congressional Visit Day held March 12, The AIAA wanted to make three main points: (1) AIAA represents both business and individuals in an aerospace industry that was responsible for a $24 billion positive balance of trade last year. (2) AIAA is located locally and should be the source of information for the aerospace community. (3) AIAA is very concerned about the well being of research in the United States. The members of congress visited seemed quite receptive to our input. Congressman Dana Rohrbacher asked AIAA to take a position on proposed fast-track patent legislation, which he is afraid may harm small businesses. MA&O CONFERENCE Ramana Grandhi (General Chair) announced that the1998 MA&O Conference will be held Sept. 2-4 (Wed, Thur, Fri before Labor Day), 1998, at the Hyatt Regency in St. Louis. The theme of the conference will be real-world applications of MDO. It was mentioned that the St. Louis area has gambling on riverboats, and that a $1 Metrolink ride to the hotel is available. Bob Canfield (Technical Chair) announced that he is seeking volunteers for Superchairs. These people basically will arrange to have reviewers for the abstracts in their area, distribute abstracts to reviewers, collect them after review, consolidate scores, and pass these on to the organizing committee. A call for papers will be sent to AIAA around 9/1/97. The November Issue of Aerospace America will include the call for papers. Abstracts to Superchairs will be due 1/31/98. Reviews of these abstracts are due 2/21/98. There is a possibility of using electronic submittal for the abstracts - a website may be established for this purpose. MDO WHITE PAPER PROPOSAL FOR 1998 Joe Giesing discussed the proposed white paper. This paper will emphasize real-world problems, mainly taken from industrial projects. The format has been changed from a single report to a series of invited papers accompanied by a summary paper. The invited papers will be presented in two MA&O sessions. Papers will stress the use of MDO, bring up industrial needs, or point out areas where MDO could have been used to enhance the design process. Several suggestions were made concerning subject matter, and a list of possible authors was presented by Joe. The call for papers and guidelines has been drawn up and a tentative schedule established. The papers will be due before the normal deadline for papers, in order for the summary paper to be written. Some prospective authors have been contacted. It was suggested that the list was dominated by aircraft, and additional authors from the space community will be contacted. ACTION ITEM: Fred Striz will contact people at Loral to see if they can participate. ACTION ITEM: Dean Waldie will make contact at TRW regarding their participation. (2 of 5)12/29/ :29:14 PM

259 MDO TC Meeting Minutes (4 April 1997) ELECTIONS Elections will be held electronically on the web before the next TC meeting. This should take place during July/August and be complete by September 1. SUBCOMMITTEE REPORTS Awards Subcommittee (Thomas) Harold Thomas is rolling off the TC, and Omar Ghattas will be replacing him as chair. The process for selecting the best paper award at the MA&O was discussed. At present, the process is to review papers which are chosen from both the highly-rated abstracts and the best-of-session papers, as chosen by the session chairs. A motion was made and seconded to continue this process in the future for best paper. MOTION APPROVED. The question of including MDO papers from other conferences (SDM, ASM, WAC, etc.) as candidates for best paper was brought up. A motion was made to limit the candidate papers to only those from the MA&O Conference. MOTION APPROVED. A discussion of when to present the award ensued. A motion was made to notify the recipient, announce the award in Aerospace America, and to wait for the next MA&O Conference for the award presentation. MOTION APPROVED. A motion was made to recognize the ten finalists by sending a letter from the TC to each one. MOTION APPROVED. The TC nomination for AIAA Fellow was discussed. ACTION ITEM: Harold will send everyone s with information on the nominees, and voting will be done electronically. Conference Support Subcommittee (Chair Vacant at Present) Kumar Bhatia reported on the 97 SDM conference. There were 6 invited one-hour papers, and these were very successful (the rooms were full). About 2/3 of submitted abstracts were accepted. Kumar is also the representative for the 98 SDM conference. He wants to maintain the invited papers, but focus on one or two areas - possibly from industry. He would also like to limit these presentations to 45 minutes, leaving 15 minutes for questions. A suggestion was made that the MA&O replace the Adaptive Structures Conference as a two-day event every other year at the SDM Conference. This proposal was voted on by the TC. MOTION FAILED. Kumar asked for any suggestions concerning the invited papers for MDO at the 1998 SDM Conference (3 of 5)12/29/ :29:14 PM

260 MDO TC Meeting Minutes (4 April 1997) to be ed to him. Publications Subcommittee (Livne) Eli Livne is working with Tom Weeks to put together a Journal of Aircraft issue on MDO. He has about 15 papers which are candidates for inclusion, but is looking for more. He has asked people to come up with MDO papers more general in scope with good bibliographies, instead of using previously published papers. This makes it more difficult, but Eli is now more hopeful of success than a few months ago. Achille Messac has been asked for help in identifying knowledgeable reviewers for several AIAA journals. ACTION ITEM: Achille will send out s asking for information in order to form a database of potential reviewers. Education Subcommittee (Renaud) Because the education panel session at the MDO meeting in Seattle was so successful, this will be done again at the next MA&O Conference. Internet Subcommittee (Eldred) Mike talked about updates to the web page. The membership list has been updated. New additions to the website include number of hits and FAQ. Mike discussed ideas on implementing Sobieski's idea of having an MDO Electronic Forum. The recommended approach is a combination of and Web based formats. Liaison Subcommittee (Thomas) Georges Fadel will be replacing Harold as subcommittee chair. Shreekant Agrawal will replace Rudy Yurkovich as the liaison for the Applied Aero TC. Clark Briggs reported that the Design Engineering TC had two sessions on knowledge-based design at the WAC which were very good. They are putting out the third edition of their design handbook, this time an electronic version. Fred Striz reported that the Structural Dynamics TC is producing a structural dynamics video. Benchmarking Subcommittee (Striz) Fred Striz reported that the test suite of MDO problems being developed at NASA Langley can be accessed at the following website: This includes a new CASCADE code (Complex Application Simulator for the Creation of Analytical Design) developed at SUNY/Buffalo by Christina Bloebaum. Fred is working on the report of the panel discussion and paper session on benchmarking and testing at the last MA&O Conference. He would like to include a session on benchmarking and testing in MDO at next year's MA&O Symposium and if there is enough interest, at the next SDM. If you are interested in writing a paper in this area, regard this as the (4 of 5)12/29/ :29:14 PM

261 MDO TC Meeting Minutes (4 April 1997) first Call for Papers, and contact Fred. Fred reported that he has the MBB fin benchmarking problem available to anyone interested. It consists of structural model data on disk with papers and reports covering previous comparisons. You must supply the aerodynamics. Contact Fred Striz if you are interested. MEETING SCHEDULE NEXT MEETING: Thursday, Oct. 9, 1997 at Henry VIII Hotel & Conference Center in St. Louis, MO, 8:00 AM-12:00 NOON. McDonnell-Douglas facility tour 1-5 PM. The meeting was adjourned at 23:15 hours. Respectfully submitted on 8/22/97, Allan Goforth Lockheed Martin Skunk Works Dept , Bldg Lockheed Way Palmdale, Ca Tel: (805) Fax: (805) Home Business Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: August 26, 1997 Michael Eldred, (5 of 5)12/29/ :29:14 PM

262 MDO TC Meeting Minutes (6 January 1997) PRELIMINARIES MINUTES OF THE MDO TC MEETING January 6, 1997 Reno, NV Chairman Jean-Francois Barthelemy called the meeting to order at 7:00 PM. Allan Goforth recorded the minutes. There was an introduction of members and guests. Members present were: Barthelemy, Goforth, Giesing, Yurkovich, Drela, Agrawal, Eldred, Gelhausen, Bhatia, McIntosh, Olds, and Fadel. Members Eastep, Rais-Rohani, and Raj were represented by V. B. Venkayya, Abdollah Arabshahi, and Brian Goble, respectively. Other guests were Andrew Santangelo, Jerry Heffner (AIAA), Bob Bell (AIAA Business Dev.), Tom Weeks (J. of Aircraft), Karl Bradshaw (AIAA), Emily Davis (AIAA), and Cathy Chenevey (AIAA). Thanks to these and their sponsoring organizations for attending. MEMBERSHIP DATABASE INFORMATION REVIEW AND VERIFICATION Current membership information, i.e., name, address, subcommittee membership status, was passed around for review and update by members present. All members should check this information on the web and send corrections to Mike Eldred. PRESENTATION OF AIAA STATUS Emily Davis made a presentation in which the following points were made: AIAA now has 29,931 members, a slight increase over last year. 29 AIAA Fellows were picked this year, and will be honored in May at the Awards Banquet. There are 3 new Corporate members (a total of 29 Domestic and 19 International Corporate Members). AIAA published 6 new books. A mid-march congressional visit is planned. The first year of providing AIAA Journal and Meeting Papers on Disk was successful. There have been over 200,000 hits since March on the AIAA website. Jerry Heffner from TAC (Technical Activities Committee) discussed how the MDOTC fits in with the basic AIAA organization. It was pointed out that virtually all the personnel making up the TAC organization are volunteers. In August, an activity called TAC Self-Examination was initiated. The purpose of this is to develop new initiatives which will make AIAA participation attractive to potential members. They want to make it clear to sponsoring organizations that there is a payoff in value returned (1 of 6)12/29/ :29:15 PM

263 MDO TC Meeting Minutes (6 January 1997) to that organization when there is participation in conferences, symposiums, etc. Some of the possible initiatives are: Assessment and evaluation of TAC with regard to meeting members needs in 2005 Development of Virtual Symposia Enhance International cooperation and collaboration Assessment of TAC effectiveness Assessment of AIAA Conferences These initiatives may lead to recommendations for TAC reorganization. BELLEVUE MDOTC MEETING MINUTES REVIEWED AND APPROVED MDO WHITE PAPER PROPOSAL FOR 1998 Joe Giesing presented slides of his plans for producing a TC white paper on MDO in Joe mentioned that the old white paper, from 1991, would be put on the web by the end of the month. Joe made a strawman outline for the white paper and sent it to the 16 people who expressed interest. He asked for comments and suggestions. Joe said the response was helpful, but not large. This led Joe to conclude the following: (1) that the outline may be too ambitious, (2) we have enough survey papers, and (3) we should present real-world MDO needs. Discussion lead to the idea of having "White Paper Sessions" at the 1998 MA&O Conference. These papers would present needs - not solutions in search of a problem. This idea will be developed further and discussed at the next TC meeting MEMBERSHIP SELECTION FOR MDO TC John Olds presented a review of the current roster for the TC, and discussed membership goals. It was noted that 50% of members will roll off the TC in 1998, and we will need critical replacements from NASA-Ames, Boeing, and McDonnell Douglas-St. Louis. The 1997 applicant pool includes 9 full members, 4 associates, and 2 international potential members. The TC membership committee recommended a "yea" vote on all the applicants. This motion was put to the TC and approved. The new TC members are Balling(BYU), Bolognese(NASA-Goddard), Chang(Lockheed-Martin Skunk Works), Gilje(TRW), Grossman(Virg. Tech), Human(NC A&T St.), Khot(AF-Wright Lab), Kolonay(AF-Wright Lab), Martin(GE Aircraft Eng), Mazzawy(UT Pratt&Whitney), Mosher(Aerospace Corp), Peraire(MIT), Petiau(Dassault, France), Schrage(Ga. Tech), and Suleman(IST, Portugal). AIAA SHORT COURSES Bob Bell, from AIAA, reported on AIAA short courses offered in He is trying to generate interest. He mentioned that they would be meeting later in the week at Reno to finalize plans. Any TC member (2 of 6)12/29/ :29:15 PM

264 MDO TC Meeting Minutes (6 January 1997) interested in developing a short course or tutorial should contact Bob. PRESENTATION BY DR. TOM WEEKS, EDITOR OF JOURNAL OF AIRCRAFT Dr. Weeks presented slides on the process of publication at the Journal. They keep close watch on the backlog of publications, since this is a measure of the stability of the Journal. Two types of backlog are tracked: accepted and pre-accepted. Accepted backlog consists of papers that have undergone review and revision, and are awaiting publication. Pre-accepted backlog is made up of papers which have been submitted, but are undergoing review and revision. Their problem is that, while pre-accepted backlog is holding fairly constant, accepted backlog is declining rapidly. This is mainly due to the fact that reviews and revisions are taking much longer to complete. Consequently, Dr. Weeks is asking the TC for help in identifying and motivating reviewers. Also, authors need to be motivated to provide timely revisions to their papers. In addition, he requested feedback from the TC on how the publication process could be improved. It was also mentioned that Frank Eastep will be an Editorial Board Advisor, as well as Associate Editor for the Journal. AIAA CONGRESSIONAL VISIT DAY Andrew Santangelo discussed the upcoming Congressional Visit Day this March. Andrew attended a planning meeting Monday in Reno. He will canvass the TC membership for suggestions by . Mike Eldred will put a link on our website to Andrew's to facilitate this. SUBCOMMITTEE REPORTS Applications Subcommittee (Radovcich-not present) No report. It was decided that this subcommittee needs a replacement for Radovcich, since he is unable to devote time to the task. ACTION ITEM: Joe Giesing will search for a new chairman. Awards Subcommittee (Thomas- not present) Jean-Francois reported. Harold Thomas is rolling off the TC in April, and Omar Ghattas will be replacing him as chair. Omar missed Reno because of illness. The process for selecting the best paper award at the MA&O was discussed. Now the process is to issue the award two years later at the next MA&O conference. There seemed to be general agreement that the award should be based on the paper, not the abstract. There was also agreement that the award should be presented as soon as possible after the MA&O meeting. Recommendations will be passed on to Omar, and the process will be formally defined. Rudy Yurkovich pointed out that he was a member of a group that arrived at criteria for evaluating awards, and sent a letter to Virgil Smith with recommendations. Rudy noted that the MDO award fails (3 of 6)12/29/ :29:15 PM

265 MDO TC Meeting Minutes (6 January 1997) most of the criteria. ACTION ITEM: Rudy will mail a copy of this letter to Omar. Congratulations to Vipperla Venkayya and Rafi Haftka, who were both named AIAA Fellows. The subcommittee will decide at the SDM meeting who to nominate for Fellow in Call for nominations for 1998 MDO Award will come out in Oct Conference Support Subcommittee (Chair Vacant at Present) Shreekant Agrawal reported on the current ASM conference. Of the MDO papers, 8 came from academia, 4 from research centers, and 1 from industry. There was a 30% rejection rate for MDO papers. Kumar Bhatia reported on the 97 SDM conference. Kumar received 41 papers, of which 27 were accepted (66% acceptance rate). There were 6 invited papers. We need a representative for the 98 SDM conference. Kumar will consider it - it was a lot of work. He mentioned there were 3 reviews of each paper. Paul Gelhausen reported that the 2nd World Aviation Conference will be held in October 25, 1997 in Anaheim. He wants to set up 2 MDO sessions. Papers can be full papers or not - slides may be presented alone. Paul is looking for help, as session chairs, etc. He will send to TC members on the subject. Education Subcommittee (Renaud - not present) John Olds mentioned that he is no longer required to prepare a question for the PE's exam, because the NSPE is dropping the Aerospace Professional designation, and the test will not be offered after this year. The education panel session at the MDO meeting in Seattle was well attended and enthusiastically received. Panelists included Bill Mason of VPI, Ilan Kroo of Stanford, Dan Schrage from Georgia Tech, Kumar Bhatia of Boeing, and Rudy Yurkovich of McDonnell Douglas. A paper session on engineering education was also a success. The education subcommittee would like to volunteer to organize a paper and a panel session at the 1998 MDO meeting. Internet Subcommittee (Eldred) Mike talked about changes to the web page. He has added an alternate membership list with no pictures which is much faster. Subcommittee reports are now being included, and subcommittee chairs are urged to send this information directly to Mike. He also noted that the old MDO white paper is being added. Liaison Subcommittee (Thomas - not present) Georges Fadel will be replacing Harold as subcommittee chair. Georges reported that Bob Canfield sent a report on the AI TC. They would like to participate in the next MA&O conference by organizing a special AI session. At their next meeting, the chairman will solicit a potential chairman for an MAO session on AI Applications for Design. (4 of 6)12/29/ :29:15 PM

266 MDO TC Meeting Minutes (6 January 1997) Rudy Yurkovich discussed the Applied Aero TC meeting which took place on the previous evening in Reno. Rudy mentioned that they had name tents at their TC meeting - this would be a great convenience, since most people on a TC are not acquainted with everyone else. The Applied Aero Chair is encouraging his TC members to branch out and support other technical areas - so there may be a chance to recruit some aerodynamic people for our TC. Publications Subcommittee (Livne - not present) Eli Livne is working with Tom Weeks to put together a Journal of Aircraft issue on MDO. He has some papers which are candidates for inclusion, but is looking for more. Benchmarking Subcommittee (Striz - not present) Jean Francois reported from Fred's written submittal. The MA&O Symposium in Bellevue featured a paper session on benchmarking, as well as a panel session moderated by Professor Haftka. ACTION ITEM: The subcommittee is compiling the ideas received on benchmarking during those sessions, and will have a full report at the next TC meeting in Florida. AIAA EVENT PLANNING REORGANIZATION Karl Bradshaw introduced Cathy Chenevey, who will be the events planner for the next MA&O Symposium 98. Karl said they had reorganized at headquarters. They have hired some new people and are trying to get more people involved in event planning so the body of knowledge is not lost if they decide to leave AIAA. Karl has done some research on possible locations for the next MA&O Symposium, and he will pass the information on to Ramana Grandhi. MEETING SCHEDULE NEXT MEETING: Monday, Apr.7, 1997 in Orlando, Florida 7:00-11:00 PM. Dinner at 6:00. The meeting was adjourned at 23:15 hours. Respectfully submitted on 3/27/97, Allan Goforth Lockheed Martin Skunk Works Dept , Bldg Lockheed Way Palmdale, Ca Tel: (805) Fax: (805) Home egoforth@themall.net Business egoforth@ladc.lockheed.com (5 of 6)12/29/ :29:15 PM

267 MDO TC Meeting Minutes (6 January 1997) Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: March 27, 1997 Michael Eldred, (6 of 6)12/29/ :29:15 PM

268 MDO TC Meeting Minutes(5 September 1996) PRELIMINARIES MINUTES OF THE MDO TC MEETING September 5, 1996 Bellevue, Wa. Chairman Jean-François Barthelemy called the meeting to order at 7:15 PM. Allan Goforth recorded the minutes. There was an intorduction of members and guests. Members present were: Barthelemy, Goforth, Rais-Rohani, Thomas, Bloebaum, Mistree, Striz, Messac, Haftka, Giesing, Yurkovich, Eldred, Seidel, Bhatia, Livne, Renaud, Grandhi, Ghattas, Canfield, Ewing, McIntosh, Karpel, Gurdal, Morris, Briggs, Olds, Majumdar, Gelhausen, Eastep, Fadel, and Lawrence. Guests attending were Chris Borland (Past Chariman), Jaroslaw Sobieski (NASA LaRC), Kemper Lewis (SUNY-Buffalo), Wei Chen (Clemson), Evin Cramer (Boeing), Prabhat Hajela (RPI), Johnsoo Lee (RPI), Mike Long (Cray Research/ SGI), and Johannes Schweiger (Daimler-Benz). Thanks to these and their sponsoring organizations for attending. SALT LAKE CITY MINUTES REVIEWED AND APPROVED DISCUSSION OF CURRENT MA&O CONFERENCE Chris Borland thanked everyone for their help in organizing the current symposium. Chris also introduced the team to head the next MA&O Conference: Ramana Grandhi from Wright State University will be the overall Chairman, with Bob Canfield (AFIT) as the Technical Chair. Christina Bloebaum mentioned that there were 360 attendees at the conference - this compares favorably to the 274 at the previous one. The general feeling was that the conference had gone very well. The panel discussions, in particular, seemed very popular. The discussion of the current symposium evolved into a general discussion of the approval process for papers. Rafe Haftka thought we should try harder to eliminate "bad" papers from the conference. Moti Karpel suggested that a date should be set by which papers could be withdrawn if the work wasn't complete. However, it was pointed out there seemed to be no correlation between late papers and "bad" ones. Another suggestion was to review briefly papers as they are submitted, but there was general agreement that this extra step would be time consuming. Fred Stritz suggested moving the papers to a "work in progress" session, if they were incomplete. Several TC members thought that the quality of the papers was generally very high at our conference, and that we should not be overly concerned with the few that didn't measure up. It was pointed out by Jean-François that any change to the selection process could be worked out by the new Chairs for the next conference. (1 of 5)12/29/ :29:16 PM

269 MDO TC Meeting Minutes(5 September 1996) Chris mentioned that we were forced into a short week because of hotel availability and Labor Day. He thought we might need to add a day to the next conference. This conference included two social events, and the general feeling among the TC was that this was about the right number. Jean-François brought up the issue of annual MA&O conferences and a discussion of this ensued. It was decided to delay any decision on annual meetings, and wait to see if attendance holds up. Joe Giesing suggested we tighten up on approval of papers a little and see how it goes. Location of the next conference was discussed, and an informal show of hands showed that Montreal and San Antonio were popular with the TC. Chris pointed out that this was a highly constrained problem, however, due to hotel availability, time of year, etc. WHITE PAPER ON MDO Jean-François brought up the possibility of writing a white paper on the state of MDO, similar to one produced in A discussion of this took place, resulting in a motion to produce such a white paper by the time of the next MA&O Conference - the format and content to be determined by the authors. The motion passed. Action Item: Joe Giesing will try to put together an outline by the Reno meeting. Jarek Sobieski initiated a discussion concerning the conflict between industry - MDO users, and Universities - MDO methodology developers. Industry typically wants software checked out with reallife problems, and the developers don't always do this. Jarek suggested setting up a clearinghouse for MDO problems on the Web, which would act as an interface between industry and academia. It might be included with the NASA problem suite, or with the TC Home page. Action Item: Jarek and Rafe Haftka will investigate to see what resources are required. SUBCOMMITTEE REPORTS Applications Subcommittee (Radovcich-not present) Nick had the idea of putting together a brochure on MDO, but it is not clear if he is able to work on it. Action Item: Joe Giesing will follow up with Nick Radovcich to see what he will be able to do for the subcommittee. Awards Subcommittee (Thomas) The best paper award at the MA&O was discussed. Harold got 5 volunteers to review approximately 20 papers. Frank Eastep said that the Journal of Aircraft would like to institute a "fast track" for publication of the better papers as chosen by the TC. He will work with Harold to pick the top 25 papers from the current conference. Harold also mentioned that he will be dropping off the TC after the SDM Conference, so a replacement will be needed. Action Item: Harold will decide on the criteria for judging best paper, and come up with a selection (2 of 5)12/29/ :29:16 PM

270 MDO TC Meeting Minutes(5 September 1996) process by the Reno meeting. Conference Support Subcommittee (Chair Vacant at Present) Joe Giesing reported Agrawal's notes from the Reno ASM conference. There were two MDO sessions with 13 papers presented - five were rejected. Paul Gelhausen reported that the 2nd World Aviation Conference will be held in October 25, 1997 in Los Angeles. This group has reduced the standards for their papers in order to get more up-to-date information. Kumar Bhatia, our SDM representative, inquired to the SDM TC about our participation in the rotating chair for the SDM Conference. This met with a negative response. He will continue to pursue this, at a low level, since our TC didn't express strong feelings on the matter. Kumar has received 39 papers for SDM 97. Last time there were 55 submitted, with 45 accepted. He would like to have an invited lecture at the start of each MDO session. This would be a 20 minute talk with 20 minutes for discussion. The TC generally supported this idea. Education Subcommittee (Renaud) John Olds has volunteered to come up with a test problem for Conrad Newberry's Professional Engineer's exam. John Renaud reported that the education panel discussion at the current conference was very successful. Internet Subcommittee (Eldred) Mike talked about changes to the web page. Membership list includes AIAA membership level and picture. Check to see if it's correct. If you have not sent a picture, please send either a GIF or JPEG format that is already shrunk to about the proper size. Subcommittee reports are now included, and subcommittee chairs are urged to send this information to Mike. Mike mentioned that the last issue of the newsletter has not gotten on the website. It was also brought up that we should register our web page with the major search engines. Action Item: Georges Fadel will take action to register our web page. Liaison Subcommittee (Thomas) Harold presented notes from Srinivas Kodiyalam, the MDO liaison to the Structures TC. Items included the following: (1) AIAA focus on standards for coverage of space launches. (2) Report on the 38th SDMtheme is "Vision 2000". (3) Upcoming Conferences - World Aviation Congress, International Adaptive Structures Conf., 3rd International Conf. On Composite Eng., 11th International Conf. On Composite Materials, Society of Engineering Science: 33rd Annual Meeting. (4) August Planning meeting of Structures TC. - Location: Wright Patt AFB. Rudy Yurkovich discussed the Applied Aero TC meeting which took place last June in New Orleans. They have received 116 abstracts and accepted 104 of these for Reno meeting. They have made some progress on developing a "fast track" process for some of the papers. Rudy mentioned that some editors are not in favor of this- they want peer review. Membership(Olds) (3 of 5)12/29/ :29:16 PM

271 MDO TC Meeting Minutes(5 September 1996) John has been active in trying to recruit new members. The response looks good. Applications were available at the current conference, and many were picked up by the attendees. Newsletter (Bloebaum) The last issue of the newsletter has been published. Publications Subcommittee (Livne ) Achille Messac put together MDO highlights for the December issue of Aerospace America. He thanked the TC membership for providing him with a lot of input. Benchmarking Subcommittee (Striz) Fred reported that the set of test problems developed at NASA-Langley is being readied for its official opening at or before the MA&O meeting. It has grown to three problem classes and a total of 17 cases. Sample test pages can be accessed under the following URL: The current MA&O Conference featured a full paper session on benchmarking and a panel discussion devoted to this topic. Fred also reported that he will be receiving a test case for the MBB fin benchmarking problem soon. There has been no progress on obtaining the Airbus wing model. MEETING SCHEDULE NEXT MEETING: Monday, Jan. 6, 1997 in Reno. 7:00-11:00 PM - Dinner at 6:30 SPRING MEETING: Monday, Apr.7, 1997 in Orlando 7:00-11:00 PM The meeting was adjourned at 23:15 hours. Respectfully submitted on 12/20/96, Allan Goforth Lockheed Martin Skunk Works Dept , Bldg Lockheed Way Palmdale, Ca Tel: (805) Fax: (805) Home egoforth@themall.net Business egoforth@ladc.lockheed.com (4 of 5)12/29/ :29:16 PM

272 MDO TC Meeting Minutes(5 September 1996) Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: December 20, 1996 Michael Eldred, (5 of 5)12/29/ :29:16 PM

273 MDO TC Meeting Minutes(15 April 1996) PRELIMINARIES MINUTES OF THE MDO TC MEETING 15 April 1996 Salt Lake City, Utah Chairman Jean-Francois Barthelemy called the meeting to order at 7:10 PM. Allan Goforth recorded the minutes. Members present were: Barthelemy, Goforth, Rais-Rohani, Thomas, Sepulveda, Bloebaum, Mistree, Striz, Messac, Haftka, Giesing, Kodiyalam, Yurkovich, Eldred, Seidel, Bhatia, Livne, Renaud, Grandhi, Radovcich, Ghattas, Canfield, Ewing, and McIntosh. Guests attending were Mike Long (Cray Research/SGI), Zafer Gurdal (Va. Tech), Moti Karpel (Technion-Israel), Miseille Gerard (AIAA), Emily Davies (AIAA), Carlos Orozco (U. of Va.), Christos Chamis (NASA Lewis), Doug Sagehorn (Raytheon), Ashok Belegundu (Penn. St.), and Martin Stettner (Daimler-Benz, representing Johann Krammer). Thanks to these and their sponsoring organizations for attending. MEMBERSHIP CHANGES Jean-Francois announced the selection of five new members for the TC. They are Dr. Frank Eastep from U. of Dayton, Dr. Mike Eldred from Sandia, Dr. Moti Karpel from Technion-Israel, Dr. Alok Majumdar from Sverdrup (MSFC), and Prof. Allan Morris from Cranfield Univ. (UK). The TC extends a cordial welcome to these very capable individuals. In addition, Past-Chairman Chris Borland has decided to retire from the TC, after seven years of perfect attendance. Thanks to Chris for all the great work he did for the TC during that long timespan. NEW WEB SITE The TC web site has been moved to RENO MINUTES REVIEWED, CORRECTED, AND APPROVED PLANNED OPTIMIZATION CONFERENCE Farrokh Mistree presented ideas for an optimization conference which is to be held in Florida during March of The focus of this conference is Engineering Design and Optimization in Industry, and Dr. Ashok Belegundu of Penn. St. will be the conference chairman. There will be substantial industry participation with the purpose of establishing a dialog among academia and industry. There will also be international participation. They want to establish a true dialog - what works, what doesn't, what are industry's problems, and where do we go from here. They are seeking the following things from our TC: (1 of 6)12/29/ :29:17 PM

274 MDO TC Meeting Minutes(15 April 1996) (1) Co-sponsorship by AIAA, (2) Inclusion of a flier in MDOTC newsletter, (3) Links from AIAA and TC websites to their website, and (4) participation of AIAA members in the conference. The conference is planning on 11 or 12 full-length papers. The rest of the participants will come with ideas - not complete, but evolving, expressed on two-page position papers. The four-day conference is expecting to attract about 65 people, with perhaps 15 or so invited. Poster-board sessions are also planned. They are trying to keep expenses to a minimum - approximately $500. In the following discussion, it was pointed out by Rudy Yurkovich that getting AIAA sponsorship will require considerable effort. A more informal type of support was discussed, and the conclusion was that the TC could add something to the newsletter, put links on our website, and perhaps even write a letter of support, but that formal sponsorship by AIAA was not possible at this time. Anyone interested in participating in the conference should contact Farrokh. AIAA REORGANIZATION Emily Davies, Staff Liaison for Technical Activities, gave a presentation on the new organizational structure of the AIAA. Headquarters has moved from Washington to Virginia, basically for financial reasons. A study concluded two years ago that the AIAA should be reorganized. Many layers of management have been eliminated, and the AIAA is now organized around projects. The new organization makes it easier to find help, and a new 800 telephone line has been added. The technical committees, consisting of 2500 volunteers, make up the largest part of the organization. AIAA membership is now at about 30,000. AIAA now recognizes that TC's have a much broader function than just to host conferences. Miseille Gerard, who was brought in for business development, then spoke about the future of AIAA and how we could help. AIAA was doing no marketing until recently. She wants to work with the TC to establish long-range goals, and is eager to work on improving processes to achieve these goals. All conference papers will now be put on CD-ROM, and will also be printed on paper, because surveys showed that libraries wanted hard copy also. Abstracts from as far back as 1960 have been added to the CD-ROM database. Eventually, they will probably go to all electronic publishing, but surveys showed that their customers are not ready for that yet. The process of making a conference CD-ROM now takes about 12 weeks, which is too long a time before the conference. Authors often have trouble getting papers in six weeks before a conference. Even though authors generally submit disks as well as hardcopy, the disks must be scanned and copied to CD. ELECTION OF VICE-CHAIRS Mr. Joe Giesing of McDonnell Douglas and Dr. John Renaud of Notre Dame were nominated and elected by acclamation to the positions of Vice-Chairman/Technical and Vice-Chairman/ Communications, respectively. INDUSTRY VISION FOR MDO (2 of 6)12/29/ :29:17 PM

275 MDO TC Meeting Minutes(15 April 1996) Jean-Francois reported the results of combined subcommittees at NASA who were tasked with reviewing MDO progress. One of their conclusions was that Industry needed to make clear what it expected and required from MDO, possibly including areas where research is needed. Much discussion took place concerning the scope and purpose of this task, which might be taken up by industry members of the TC. It was decided to assemble the members from industry and any other interested parties in a separate meeting the next day to continue the discussion. SUBCOMMITTEE REPORTS Applications Subcommittee (Radovcich) Harold Thomas sent Nick an example of a project which failed because MDO was not used. Nick is investigating the idea of putting together a kind of sales brochure for MDO, which may include items such as this. This would show examples of optimization problems and indicate what kind of payoffs are obtained by using MDO. The applications subcommittee has not met since Reno. Awards Subcommittee (Thomas) The MDO Award was discussed by Harold. It will be given at the MA&O Conference, and the recipient is chosen by a selection committee of five from our TC. Nominations come from the AIAA, and these have been received. A recipient has not been chosen yet because only two of the selection committee members are attending this SDM conference. The possibility of giving a best paper award at the MA&O was discussed. There is a problem with giving the award based on the abstract or on reviews by session chairmen. It seems to be impossible to read through all the papers. In addition, the subcommittee has nominated Dr. Venkayya for AIAA Fellow. Conference Support Subcommittee (Santangelo - not present) Jean-Francois presented the report. Three conferences are being supported at this time. Ramana Grandhi reported on the current SDM conference - 11% of papers were rejected this year. There were many MDO papers at this year's SDM, and 7 sessions were devoted to MDO. Kumar Bhatia will be our representative at the SDM conference in Christina mentioned that at last year's SDM, some papers were chosen for poster sessions without the author's consent; she is opposed to this practice. Shreekant Agrawal wanted to remind everyone that the abstract deadline for next year's Reno conference is May 17. The other conference we support is the Global Aviation Conference, held in the fall, which is a joint conference with the SAE. Paul Gelhausen is our representative for this. Education Subcommittee (Renaud) A report was provided by John. The following items were mentioned: The MDO TC review procedure for short courses has been finalized. A copy of this procedure is being forwarded to Prof. Murthy at Purdue. The MA&O Conference in Seattle will feature one paper session dealing with MDO education and one panel session which will address this subject. The panel will be composed of representatives from industry, government, and academia. John is looking over the material required for Conrad Newberry's test problem for the Professional Engineer's exam. He will put something on the web when (3 of 6)12/29/ :29:17 PM

276 MDO TC Meeting Minutes(15 April 1996) he has it ready and anyone interested can participate in coming up with the problems and required documentation. Internet Subcommittee (Thomas) Harold talked about changes to the web page. Membership list includes AIAA membership level and picture. Check to see if it's correct. If you have not sent a picture, please send either a GIF or JPEG format that is already shrunk to about the proper size. Subcommittee reports are now included, and subcommittee chairs are urged to send this information to Harold. Related items of interest are now linked to our website. Liaison Subcommittee (Thomas) Harold reported that there were no new reports, since the last meeting was just three months ago. They still need liaisons for Materials TC, GNC TC, Standards TC and AI TC. Harold said that the Liaison job is getting easier because more TC's are establishing web pages. It is not really necessary to attend the meetings. The task is to filter the MDO content out of their minutes. Bob Canfield volunteered for the AI slot. Rafi Haftka passed out a flyer on an upcoming design competition which uses MDO to design and build the smallest airplane which is capable of performing a specific mission. It must fly a specific course and photograph four letters marked on the ground. Kumar Bhatia is seeking suggestions for speakers for the 1997 SDM Conference, for the plenary session and Awards Luncheon. Farrokh Mistree reported that he is the General Chair for the September 1998 ASME Conference in Atlanta. He wants to put this on the record, since there have been conflicts in the past. MA&O Conference Subcommittee (Bloebaum) Christina had several handouts, including the newsletter. A list of session chairs was also passed out - the authors and chairs should be getting packages from the AIAA soon. The conference generally has five parallel sessions, with six sessions occurring twice. Also work-in-progress sessions of fifteen minutes each will be held. These facts give us a large total number of papers ( ~ 210). Work-in-progress papers will be given an AIAA number, and the author's will be asked to write a two page overview which will appear in the proceedings. There are 38 sessions, four of these being panels. The people organizing the panel sessions are Fred Striz (Benchmarking in MDO), Jim Rogers (Managing the Design Process), John Renaud (Issues in Engineering Education), and Christina is temporarily heading up the Industry panel session. She is looking for an Industry person to take this over, however. These panel session chairs are themselves organizing the sessions and will contact other TC members for help. Christina proposed a plan for electing the new General Chair for the MA&O Symposium, and she passed out a handout which included the responsibilities of the General Chair and the Technical Chair (who is appointed by the General Chair). Also included was the process of selection for the new General Chair. Briefly stated this process was the following: Between the AS and SDM Conferences, an announcement will be made that the present committee (General and Technical Chair) is accepting nominations. This announcement should be made to all present and past TC members, since these people are all eligible. If the nomination is not a selfhttp://endo.sandia.gov/aiaa_mdotc/communications/mdotc_min.apr96.html (4 of 6)12/29/ :29:17 PM

277 MDO TC Meeting Minutes(15 April 1996) nomination, there must be assurance that the nominee is willing to serve. Nominations should be written and should outline the resources that the individual can commit to the task and any experience/ background which might make him/her appropriate. Between SDM and MDO, the committee will review nominations and prioritize selections. This will be sent to the MDO TC Chair for comments, which he will relate to the General Chair. The present General Chair will then make the selection for the next General Chair prior to the MA&O Symposium. The new General Chair is encouraged to select a new Technical Chair before the MDO. A discussion of the responsibilities and the selection process ensued. It was decided to add two modifications to the proposal: (1) If available from AIAA, a profile of desirable attributes for the Chairs will be added to the proposal, and (2) the announcement for nominations will be sent to members of ISSMO. This proposal was seconded and approved by voice vote of the TC. Publications Subcommittee (Livne) Eli reported that the subcommittee is planning an issue of Journal of Aircraft devoted to MDO. He hopes to select papers from the MA&O Conference for this. Eli would like to get the papers from AIAA, as early as possible, to facilitate this process. He will also need help in reviewing the papers, to see which ones are suitable. TC members may be asked to review one paper for this purpose. Eli mentioned also that he would like to get someone else to put together the annual optimization article for the December issue of Aerospace America. Achille Messac volunteered for this task. Benchmarking Subcommittee (Striz) Fred reported that the set of test problems developed at NASA-Langley is being readied for its official opening at or before the MA&O meeting. It has grown to three problem classes and a total of 17 cases. Sample test pages can be accessed under the following URL: A tech transfer agreement between USAF and Daimler-Benz for an Airbus wing model is still in the works. The subcommittee is attempting to get disk space on AIAA machines to store some of the larger benchmarking cases. The MA&O Conference will feature a session on benchmarking and a panel discussion devoted to this topic. ACTION: Fred will circulate an request asking for input as to what questions will be addressed by the panel. MEETING SCHEDULE NEXT MEETING: Thursday (Plenary Meeting) & Friday (Subcommittee Meetings), Sept. 5&6, 1996, 7:00-10:00 PM, MA&O Conference in Bellevue WINTER MEETING: Monday, Jan. 6, 1997 in Reno, 7:00-11:00 PM (5 of 6)12/29/ :29:17 PM

278 MDO TC Meeting Minutes(15 April 1996) SPRING MEETING: Monday, Apr. 7, 1997 in Orlando, 7:00-11:00 PM The meeting was adjourned at 23:15 hours. Respectfully submitted on 6/22/96, Allan Goforth Lockheed Martin Skunk Works Dept , Bldg Lockheed Way Palmdale, Ca Tel: (805) Fax: (805) Home Business Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: June 25, 1996 Michael Eldred, (6 of 6)12/29/ :29:17 PM

279 Latest MDO TC Meeting Minutes( 18 January 1996) PRELIMINARIES MDO TC Meeting Minutes 18 January 1996 Reno Chairman Jean-Francois Barthelemy called the meeting to order at 8:35 hours. Allan Goforth recorded the minutes. Other members present were: Past Chairman Borland, Radovcich, Agrawal, Bhatia, Bloebaum, Drela, Fadel, Gelhausen, Ghattas, Giesing, Haftka, McIntosh, Mistree, Raj, Santangelo, Thomas, and Yurkovich. Otto Sensberg attended representing Johann Krammer. Special thanks to those and their sponsoring organizations for consecutive attendance. LOS ANGELES MINUTES REVIEWED, CORRECTED, AND APPROVED SUBCOMMITTEE REPORTS Conference Support Subcommittee (Santangelo) Andrew Santangelo is stepping down from the chair of this subcommittee, and is looking for a replacement. Andrew reported that the MDO committee hosted two full sessions at this year's Aerospace Sciences Meeting and Exhibit (ASM). The sessions were well attended. Shreekant Agrawal will be the MDO representative for the 1997 ASM conference. At this time, the ASM is planning for two MDO sessions, Monday morning and afternoon, for 1997 in Reno. Our TC meeting schedule will have to take this into account. Kumar Bhatia volunteered to be the MDO representative for the 1997 SDM Conference. Education Subcommittee (Renaud - not present) A report was provided by John and presented by Christina. The following items were mentioned: 1. A panel session on engineering education at the 1996 MA&O will be held. John will be leading efforts to organize this. Contact him if your are interested in participating or have any input. 2. NASA Langley has put together an MDO Test Problem Suite which is available at the following web site: Sharron Padula was the lead on this project at Langley. 3. A formal procedure for approving sponsorship of AIAA Short Courses was proposed. Awards Subcommittee (Thomas) The purpose of the subcommittee and the process of upgrading membership status for the AIAA was discussed. This is explained in the AIAA Handbook, which is connected to our Web Page. Nominations (1 of 7)12/29/ :29:19 PM

280 Latest MDO TC Meeting Minutes( 18 January 1996) for AIAA Fellow must be in by July 15 - five written recommendations are necessary (AIAA encourages them to be from other AIAA Fellows). The subcommittee will decide on a list of candidates to be voted on by the entire TC at the April SDM meeting. The MDO Award will be given at the MA&O Conference, and the recipient is chosen by our TC. A discussion of our participation in the SDM Award selection was brought up, since there are now more MDO papers at the SDM Conference than Materials papers. Chris said there was once discussion of making the MDO a first-tier participant in the SDM Conference but that was not approved. ACTION: Jean-Francois will investigate the status of our involvement in the SDM Award selection. Liaison Subcommittee (Thomas) ISSMO - The society held its first world congress on structural and multidisciplinary optimization (WCSMO) in Goslar Germany in May. Elections for officers and an executive committee were held at the Congress. Rafi Haftka was elected new President of ISSMO. Jarek Sobieski is on the executive committee, and Fred Stritz is on their Benchmarking Committee. ISSMO will cosponsor the next MA&O Conference at Bellevue, and will organize the review of abstracts from Europe. Rafi is preparing for the ISSMO 2nd World Congress to be held in Zakopane Poland June 16-20, ISSMO would like to see more MDO presence at this congress, and hopes for help from the AIAA MDO TC.. He needs help in promoting the conference, and in making the transition from Structures to MDO. Abstracts are due in Fall Contact Rafi if you are interested - he especially needs non-structures people. SDM TC- This TC met in October. Mody Karpel will teach an Aeroelasticity Short Course stressing current applications at the next SDM. The education subcommittee is putting together a high school science fair booklet, citing demonstration projects. The TC is trying to move to Web site. Applied Aero TC - (June 95 Meeting) Discussed no paper - no podium rule. They decided that the author will be allowed to present if he brings copies of his paper to the meeting. It was reported that the goal of publishing AIAA papers on CDROM and saving approximately $100 per volume looks feasible. (Jan 96 Meeting) Bob Bell AIAA Staff Business Dev. gave a report on the reorganization of AIAA HQ. This was completed six months ago. AIAA is now split into seven teams. TC's are now part of member services. It was noted that attendance was down at Reno this year. The Applied Aero TC has a web site: ACTION: Jean-Francois will contact AIAA to see if we can receive a presentation on the new organizational structure at a future meeting. Aircraft Design TC - AIAA sponsors two design competitions each year, one individual and the other a team competition. The design TC is responsible for judging the competition. Problems are picked by the AIAA. The suggestion was made that the MDO TC should contribute a design problem to the competition. ACTION: John Renaud, chair of the Education Subcommittee, will contact the Design TC to see how (2 of 7)12/29/ :29:19 PM

281 Latest MDO TC Meeting Minutes( 18 January 1996) we can help them. We still need liaison representatives for five other TC's: 1) Materials, 2) Guidance & Control, 3) Standards, 4) Propulsion, and 5) Artificial Intelligence. Newsletter Subcommittee (Bloebaum) There was a discussion of whether the newsletter should be continued in printed form, since we are trying to use the web as much as possible for communications. Christina would like to find a replacement as editor. It was decided that there will be at least two more printed issues, possibly three, but that there will be a transition to the web. It will still be necessary to have an editor for the web page. This person will be a member of the new Internet Subcommittee ACTION: Christina will continue the newsletter for two more issues until we convert completely to the web. Applications Subcommittee (Radovcich) Nick is investigating the idea of putting together a video illustrating MDO applications. This would show many examples of actual optimization problems and the solution process. Perhaps this will help define the meaning of MDO by example, if not formally, to the engineering community at large. Benchmarking Subcommittee (Striz - not present, presented by Harold Thomas) As mentioned in the Education Subcommittee report, a set of test problems is being developed by NASA-Langley. This now consists of five cases. Venkaya is working to get an MDO model of the Airbus wing which will be donated to the MDO TC by Daimler-Benz. Dr. Krammer of Daimler-Benz has volunteered to donate to us an MDO model of an MBB fin in NASTRAN format. Fred Striz will be coordinating benchmarking activities with ISSMO. There is a session on benchmarking at the MA&O Conference - contact Fred if you can review abstracts or want to participate in a panel discussion. Publications Subcommittee (Livne - not present, presented by Jean-Francois) Eli has been talking with one of the new TC members about the possibility of publishing a design challenge in the Journal of Aircraft. This has been done before by guidance and control. If you have any suggestions for this contact Eli. AIAA PROPOSAL - TEST PROBLEM DEVELOPMENT Conrad Newberry presented a proposal to the TC regarding problem development for the AIAA sponsored Aerospace Engineering Registration Examination. The people who put together this examination need help in coming up with problems/solutions. Conrad proposed that the TC consider development of 1 or 2 problems a year which would be included on the test. The problems developed by the TC should take approximately minutes to solve, and are open-book type problems. Conrad will send a package detailing what is required. He estimates the paperwork necessary to document the problem will take about 4-6 hours to put together. The first problem would be due at the end of this year. (3 of 7)12/29/ :29:19 PM

282 Latest MDO TC Meeting Minutes( 18 January 1996) AIAA would like for us to commit to one or two problems (with solution) per year. This proposal was referred to the Education Subcommittee for consideration and recommendations. MA&O CONFERENCE - BELLEVUE Chris Borland reported on efforts to secure speakers for the conference. He is trying to get Air Force Chief Scientist Dr. Edward Feigenbaum, one of the country's leading experts in artificial intelligence, to speak at the plenary session. Dr. John McMaster of Boeing has agreed to be the luncheon speaker on Thursday. He is an expert in biological fluid mechanics and is famous for his "bird and bee lecture". A Wednesday reception and tour of the Museum of Flight has been set up. Chris is looking for suggestions for the Spouses Program. Chris has brochures available to anyone interested in finding out about the areas attractions. A tour of the Boeing plant is still a possibility, but it seems that accommodating large tour groups is probably not possible. It may be possible to arrange for a tour for TC members only - this would probably take place Saturday after the Conference. Christina summarized her written planning report for the TC. The Call for Papers went out in the November issue of Aerospace America. In addition, 14,000 copies of the Call were mailed out to members of AIAA, ASME, and previous attendees. AIAA has made arrangements for 6 parallel sessions if we need them - last conference had five. A layout of the rooms for the sessions was included in the report. There was also a list of superchairs, who have responsibility for getting papers reviewed in their areas of expertise A tentative Conference Schedule was also part of the handout. This schedule allows for 228 papers - last time we had 176. Christina also talked about the industry panel sessions planned for the conference. This has worked very well at other conferences when it has been tried. She would like it to cover all industries, not just aerospace. She is soliciting names of people who would make good participants on the panel - if you have ideas contact Christina. TC OPERATIONS REVIEW Jean-Francois proposed a restructuring of the TC organization, based on the TC Review which was begun at the last meeting. The TC structure would be divided into three tiers - Planning, Technical, and Communications. Subcommittees would be arranged under these general headings. The TC Chair would head Planning, and the Technical and Communications Branches would be headed by Vice-Chairs. The TC Chair and Vice-Chairs would be elected for two year terms by the TC. After a lively discussion of the proposals, and some modifications, the TC voted on and approved the new organizational structure. Details of the new organization will be available on the TC web site. TC MEETINGS Jean-Francois proposed to continue meeting for day-long sessions at each of our three yearly meetings (ASM, SDM, AETOC/MA&O). There was strong resistance from the membership, primarily because this interferes with technical sessions. It was agreed to maintain one full-day (or the equivalent) meeting every other year at the MA&O Conference, and otherwise, to revert to the standard 4 hour evening (4 of 7)12/29/ :29:19 PM

283 Latest MDO TC Meeting Minutes( 18 January 1996) session. Each subcommittee is to meet at least once (physically or by teleconference) in-between or before the full committee meetings MDO MANUAL ON THE WEB Harold Thomas reported on the status of the TC manual on the web. Included information on the Web site is the operations manual, membership list, subcommittee list, latest newsletter, and latest minutes. These are all hyperlinked together, so you only need to get to one site. The address is com/~thomas/mdotc. Please check out the information on these sites and send any corrections to Harold Thomas at and Jean-Francois at Also a picture of all TC members is to be included in the membership list. You can send a picture electronically to Harold (jpg or gif file), or if you do not have scanning capability, send a photograph to Achilles Messac at Northeastern University, who has volunteered to digitize it. In sending material to Harold for the web site, html format is preferred, with ASCII text a second choice. Rafi Haftka has volunteered to maintain a mirror site for the TC files on the web. MEMBERSHIP ISSUES Chris Borland reported on membership issues. Ten members are in their last year of the 3-year term on the TC. With only four new US applicants for the TC, it appears that we will not have a problem with too many members, and will remain at the level. Although a notice is placed in the June/July Aerospace America issue, not much else has been done about recruiting. The suggestion was made to distribute an announcement of membership availability electronically. The overall makeup of the TC was discussed, with the idea that we should recruit members from other industries, such as automobile manufacturers. Lack of members representing general aviation, which may be coming back to life, was discussed, and Sam McIntosh volunteered to make some contacts in that area. We will make an effort to advertise the TC at the MA&O Conference. ADDITIONAL TECHNICAL ACTIVITIES Pradeep Raj was asked by Jean-Francois to serve as the focal point for additional technical activities. Traditionally, we have engaged in some technical activities - benchmarking is one example. Pradeep did not receive any suggestions before the meeting, but would like to hear suggestions from TC members. He did talk with Venkaya, who is presenting a paper which may be apropos at the SDM Conference. People seem to have their own idea of what MDO is, and this makes it difficult to focus on specific technical issues. Christina suggested that a discussion of what MDO is could be held on the Tuesday night preceding the Bellevue MA&O Conference. We already have a room reserved. ACTION: Christina will work to set this up. Another useful technical activity would be to somehow extract a knowledge base from technical presentations at the conferences. AGARD does this, but they have approximately 10% of the number of (5 of 7)12/29/ :29:19 PM

284 Latest MDO TC Meeting Minutes( 18 January 1996) papers which we do at our meetings. The question arose as to whether we should have technical presentations at the TC meetings, and this generated some discussion. It was decided that this would be an appropriate matter to be taken up at the next meeting, after everyone has time to think about it. ACTION: At the SDM Conference we will address what we should do technically as a TC. NEW BUSINESS Farrokh Mistree mentioned that he, Sobieski, and others are putting together a "Gordon" Conference. These conferences are like workshops conducted in a relaxed, reflective manner with time to think about and discuss the presentations which are made. This should take place in Florida during March or April, The theme is "How Optimization is Used in Engineering". Farrokh will have more information available at the April SDM meeting. Nick Radovcich posed the question, " Can we identify a project that failed because of lack of MDO?" Jean-Francois stated that this seemed like a perfect topic for the MA&O discussion session. MEETING SCHEDULE NOTE THAT THE NEXT MEETING TIME HAS BEEN CHANGED! NEXT MEETING: Monday, Apr.15, 1996 in Salt Lake City (1st day of SDM Conf.) 7:00-10:00 PM FALL MEETING: Thursday & Friday, Sept. 5&6, 1996, 7:00-10:00 PM, MA&O Conference in Bellevue WINTER MEETING: Monday, Jan. 6, 1997 in Reno. 7:00-10:00 PM The meeting was adjourned at 18:00 hours. Respectfully submitted on 10/25/95, Allan Goforth Lockheed Martin Skunk Works Dept , Bldg Lockheed Way Palmdale, Ca Tel: (805) Fax: (805) Home @compuserve.com Business egoforth@ladc.lockheed.com (6 of 7)12/29/ :29:19 PM

285 Latest MDO TC Meeting Minutes( 18 January 1996) Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: April 24, 1996 Michael Eldred, (7 of 7)12/29/ :29:19 PM

286 Latest MDO TC Meeting Minutes( 18 September 1995) PRELIMINARIES MDO TC Meeting Minutes 18 September 1995 Los Angeles Chairman Jean-Francois Barthelemy called the meeting to order at 18:45 hours after an elegant gourmet meal. Allan Goforth recorded the minutes. Members present were: Sepulveda, Thomas, Livne, Gelhausen, Messac, Briggs, Goforth, Agrawal, and Giesing. Past Chairman Borland was also present. Special thanks to those and their sponsoring organizations for consecutive attendance. The guests and visitors were Todd Beltracchi of Aerospace Corp., Otto Sensberg of Daimler-Benz Aerospace - Germany, Dudley Smith of the University of Oklahoma, Doug Neil of Universal Analytics, and Karl Bradshaw of the AIAA. UPDATED ROSTER AND SUB-COMMITTEE MEMBERSHIP An updated roster for the TC and sub-committee membership list was passed out by Jean-Francois. Please review this for accuracy and send corrections to Jean-Francois. NEW ORLEANS MINUTES REVIEWED, CORRECTED, AND APPROVED TC PROCESS REVIEW Jean-Francois presented slides outlining the TC operations, functions, and responsibilities. Some items relating to TC operations are currently being reviewed and were broken down into the following areas: 1. TC REACH - The TC's primary function is to interact with the AIAA by providing input (membership, highlights, awards,...), by participating in conferences, and by engaging in technical activities (benchmarking, propulsion, applications,...). The success of the technical activities has been limited. Jean-Francois wants to solicit ideas and opinions about whether we should engage in more technical activities, and if so, what those activities should be. If you have ideas along these lines, please contact Pradeep Raj, who will be the focal point in this area. 2. TC OPERATIONS - Most work is done by individuals in intense work periods before meetings. Should we change our mode of operation? How many times should we meet, and for how long? Can we maximize effectiveness during meetings and minimize travel requirements? Jean- Francois will act as the focal point in this area, so please contact him with your ideas. 3. TC MANUAL - The TC manual needs to be rewritten. Current manual is a collection of disjointed parts. (1 of 5)12/29/ :29:20 PM

287 Latest MDO TC Meeting Minutes( 18 September 1995) 4. TC MEMBERSHIP - Process of selecting members is being reviewed. Should we change our approach to selecting/rotating members? This process should broaden committee diversity, including representation by discipline, and representation by industry/academia/government. Please contact Chris Borland with any ideas on this. The makeup of the committee was further discussed - committee has been dominated by structural specialists in the past. It was suggested that the discipline of costing has an important place in MDO and possibly should have two sessions at the next MA&O conference. MA&O CONFERENCE - SEATTLE Karl Bradshaw from the AIAA is the new Meeting Director for the biennial Seattle MA&O Conference (replacing Julie Walker), so we will be working closely with him in order to bring the meeting together. Karl's phone number is (202) , and his address is karlb@aiaa.org. A conference planning report was passed out by Chris. Call for papers should be coming out in the November (possibly October) Aerospace America. AIAA has made arrangements for 6 parallel sessions if we need them - last conference had five. Included in the report was a list of superchairs, who have responsibility for getting papers reviewed in their areas of expertise. Anyone wanting to be added to this list, contact Christina Bloebaum (clb@eng.buffalo.edu). Christina is the Technical Chair of the Conference. Anyone with ideas concerning speakers at the conference, please contact Chris Borland. SUBCOMMITTEE REPORTS Planning Subcommittee(Barthelemy) The inclusion, on the planning subcommittee, of the chairs of the various subcommittees was discussed as a new approach to facilitating communication within the TC. Chairs will participate in the planning committee's activities with the intent of representing the membership of their subcommittees. Proposals for activities or policies may be drafted in the planning subcommittee for further consideration, modification or reframing by the whole TC. The planning subcommittee considered the review of four areas of TC activities. For each area, one focal point was identified. The focal point is to develop a draft proposal for his area of review to be available to the membership, both on the Web and by , by the middle of November. Full membership involvement begins now, by sending suggestions to the focal points. Once the proposals are available, the membership then has another month to comment. The focal points are then to finalize their proposals which they will present for approval at our Reno meeting and submit for an up or down vote. Proposed modifications will then be documented in our TC manual. While each review must consider all aspects of the activity considered, this is not an exercise in change for the sake of change, rather it is an opportunity to look at what we are doing, how we are doing it, and to determine if there is any value added in changing some aspects of the way we do business. To avoid devoting too much of our energy to this exercise, we will essentially conclude it at our next meeting The four areas for review are as follows: 1. TC OPERATIONS: Barthelemy will be the lead for this review. The objective is to address TC (2 of 5)12/29/ :29:20 PM

288 Latest MDO TC Meeting Minutes( 18 September 1995) organization, TC meeting schedule and format and any other issue that could affect the productivity of the TC. 2. TC TECHNICAL ACTIVITY INVOLVEMENT: Raj will be the lead for this review. The TC has had several attempts at carrying out technical activities. At this point we have benchmarking which looks at standard test problems, as well as education which puts together short technical courses, publications which deals with highlights and special issues of journals and conference support where we organize technical sessions or review papers. The last three activities are traditional TC involvement and there is a sense from the membership that more technical activities are warranted. Yet previous attempts have not always succeeded. 3. TC MEMBERSHIP: Borland will be lead for this review. Memberships begins with inviting qualified technical people to apply, selecting new members so that the TC's membership becomes more diverse, represents better the different disciplines at play in aerospace design and balances properly representation by industry, academia and government. 4. TC OPERATIONS MANUAL: Thomas will be lead for this review. Our current manual, now available on the Web, is quite incomplete and sometimes quite inaccurate. We will review the outline of the manual, its content, as well as the process by which we keep it current. Awards Subcommittee (Thomas) The purpose of the subcommittee and the process of upgrading membership status for the AIAA was discussed. The call for nominations for the MDO award will be in the October Aerospace America issue. Benchmarking Subcommittee (Striz - not present presented by Dudley Smith) A set of test problems is being developed by NASA-Langley. These should be available for benchtesting on the World Wide Web around the time of the 1996 SDM Conference. An MDO model of the Airbus wing will be donated to the MDO TC. Discussions with the AIAA are being held to see if we can locate some of the larger benchmarking models on AIAA computers, so individual companies will not have to supply these resources ( disk space, etc.). The question of the format necessary and the standards to be applied for benchmark testing was discussed. ACTION: Todd Beltracchi of Aerospace Corp. will get a copy of his paper on this subject to Fred Striz. Conference Support Subcommittee (Santangelo - not present) A representative for the 1997 ASM conference, who must also attend the planning session at the 1996 meeting, was needed. Shreekant Agrawal volunteered for this task. In addition, volunteered to provide support at the 1996 Design Conference in Los Angeles. ACTION: Jean-Francois will contact Andrew Santangelo concerning these conference support representatives. Liaison Subcommittee (Thomas) Representatives are needed for Materials, GNC, Standards, Propulsion, and AI. Reports were not available from the representatives to other TC's. ACTION: Thomas will contact liaison members and assemble reports. (3 of 5)12/29/ :29:20 PM

289 Latest MDO TC Meeting Minutes( 18 September 1995) Publications Subcommittee (Livne) Annual Aerospace America article on MDO has been done. Discuss ensued about possibility of pushing for a dedicated issue of AIAA Journal or Journal of Aircraft dedicated to MDO. A joint collaboration of the Publications and Benchmarking Subcommittees was proposed to establish and publish a standard set of problems and solutions for MDO problems. ACTION: Eli will contact Fred Striz. They will look into what's involved, and Eli will report on conclusions at Reno. Farrokh Mistree has written a paper which has been reviewed by several TC members. There was a discussion about how to publish this - should it be an MDO TC paper, or should Farrokh publish it? ACTION: Jean-Francois will contact Farrokh and discuss the issue. Newsletter Subcommittee (Bloebaum - not present) We want to make an effort to get the newsletter out within a month of each TC meeting. Education Subcommittee (Renaud - not present) A report was provided by John. The following items were mentioned: 1) A session/panel on engineering education at the 1996 MA&O will be held. John and Christina will be coordinating. Contact them if your are interested in participating. 2) Planning is underway for an AIAA workshop on work-flow management to be given at the MA&O Conference. 3) ISSMO Education Subcommittee wants to coordinate activities with our Education Subcommittee. Applications Subcommittee (Radovcich - not present) Nick is probably going to be the new chairman. ACTION: Jean-Francois will contact Nick for report. MDO TC INFORMATION ON THE WORLD WIDE WEB Harold Thomas distributed information concerning Web access for TC members. All TC members should obtain a copy of this (perhaps it will appear elsewhere in the newsletter). Included information on the Web site is the operations manual, membership list, subcommittee list, latest newsletter, and latest minutes. These are all hyperlinked together, so you only need to get to one site. The operations manual address is Please check out the information on these sites and send any corrections to Harold Thomas at thomas@neptune.net and Jean-Francois at j.f. barthelemy@larc.nasa.gov. Since Harold is providing this service to the TC, he asked to be allowed to include a message saying that his consulting firm is sponsoring this page. A motion to this effect was made, seconded, and approved by the TC. NEW BUSINESS There is a meeting on MDO September 26, at NASA-Langley which should be of interest to our TC. MEETING SCHEDULE (4 of 5)12/29/ :29:20 PM

290 Latest MDO TC Meeting Minutes( 18 September 1995) NOTE THAT THERE IS A CHANGE IN OUR USUAL SCHEDULE! NEXT MEETING: Thursday, Jan. 18, 1996 in Reno (Last day of ASM Conference) - meeting tentatively scheduled for the whole day Thursday. SPRING MEETING: Wednesday, April 17, 1996 in Salt Lake City - meeting tentatively scheduled for the whole day Wednesday. FALL MEETING: Sometime during the week of the MA&O Conference, September 4-6, 1996 in Seattle. The meeting was adjourned at 2305 hours. Respectfully submitted on 10/25/95, Allan Goforth Lockheed Martin Skunk Works Dept , Bldg Lockheed Way Palmdale, Ca Tel: (805) Fax: (805) Home @compuserve.com Business egoforth@ladc.lockheed.com Back to Meeting Minutes list Back to MDO TC Home Page Last Updated: April 24, 1996 Michael Eldred, mseldre@sandia.gov (5 of 5)12/29/ :29:20 PM

291 MDO TC Subcommittee Reports MDO TC Subcommittee Reports Applications Subcommittee Reports Awards Subcommittee Reports Education Subcommittee Report: January 2002 ( PowerPoint File ) Publications Subcommittee Reports MA&O Symposium Support Subcommittee Reports Back to MDO TC Home Page Last Updated: 02 January 2002 Tony Giunta aagiunt@sandia.gov 12:29:23 PM

292 MDO TC Newletters MDO TC Newletters NOTE: The June 1996 newsletter is the final edition. The newsletter effort has been discontinued in favor of disseminating information directly from the MDO TC Web site. MDO TC Newletter No. 22, June 1996 MDO TC Newletter No. 21, April 1996 MDO TC Newletter No. 20, Dec MDO TC Newletter No. 19, July 1995 MDO TC Newletter No. 18, April 1995 Back to MDO TC Home Page Last Updated: January 10, 1997 Michael Eldred, 12:29:23 PM

293 MDO TC Newsletter No. 20: Dec 1995 MDO TC Newsletter No. 20: Dec 1995 FROM THE EDITOR: Christina L. Bloebaum Happy Holidays Everyone! I hope this finds you all enjoying your holiday season and preparing your abstracts for the next MA&O Conference! Please remember that the deadline for full paper abstract submittals is January 19th and the deadline for WIP abstracts is March 1st. Also remember that while electronic submissions are possible (as described in the call), only text format is permitted. Also remember that George Rozvany has kindly agreed to serve as European Paper Coordinator which means those who are closer to Germany can submit to his address rather than mine in Buffalo. Look forward to seeing you in Reno and remember to submit interesting items to the newsletter. CHAIRMAN'S CORNER: Jean-Francois Barthelemy Our TC has been in operation for over six years and has produced a string of impressive accomplishments. From the running of successful conferences to special publications and short courses. It is time for us to take stock and assess where we have been, where we are and where we are going. We are reviewing our operations to better serve the MDO community at large. You will read the details in the minutes further in this newsletter. Essentially, Chris Borland (cjb2552@mu.ca.boeing.com) is reviewing our membership process, Harold Thomas (thomas@neptune.net) our TC manual and its distribution, Pradheep Raj (raj@lasc.lockheed.com) the TC technical involvement and I am reviewing the TC operations. Each reviewer is to provide a proposal for comments in advance of the Reno meeting. The proposals will be distributed electronically for comments by all. The comments are to be factored in modified proposals to be presented at our upcoming meeting in Reno. I strongly encourage you to review the proposals and to offer your comments to the reviewers. Should you want to offer inputs on any of those subjects, please do contact the lead reviewer directly. Our next committee meeting is Thursday 18 January 1996, the last day of the Aerospace Sciences Meeting in Reno, NV. Check in Aerospace America for information about hotels. We will need to spend most of the day in plenary or subcommittee meetings. While I intend to distribute an agenda closer to the meeting, we will be devoting one plenary meeting to reviewing the proposals to modify our operations as a TC and another one to conduct normal TC business. The remaining of the day is set aside for subcommittee meetings. I am exploring with AIAA opportunities for a social event at the end of the day. I am looking forward to seeing you in Reno. Jean-Francois Barthelemy 804/ (phone) (1 of 7)12/29/ :29:25 PM

294 MDO TC Newsletter No. 20: Dec / (FAX) MINUTES OF THE MDO TC MEETING: LA, California, September 18, 1995 PRELIMINARIES Chairman Jean-Francois Barthelemy called the meeting to order at 18:45 hours after an elegant gourmet meal. Allan Goforth recorded the minutes. Members present were: Sepulveda, Thomas, Livne, Gelhausen, Messac, Briggs, Goforth, Agrawal, and Giesing. Past Chairman Borland was also present. Special thanks to those and their sponsoring organizations for consecutive attendance. The guests and visitors were Todd Beltracchi of Aerospace Corp., Otto Sensberg of Daimler-Benz Aerospace - Germany, Dudley Smith of the University of Oklahoma, Doug Neil of Universal Analytics, and Karl Bradshaw of the AIAA. UPDATED ROSTER AND SUB- COMMITTEE MEMBERSHIP An updated roster for the TC and sub- committee membership list was passed out by Jean-Francois. Please review this for accuracy and send corrections to Jean-Francois. NEW ORLEANS MINUTES REVIEWED, CORRECTED, AND APPROVED TC PROCESS REVIEW Jean-Francois presented slides outlining the TC operations, functions, and responsibilities. Some items relating to TC operations are currently being reviewed and were broken down into the following areas: 1. TC REACH - The TC's primary function is to interact with the AIAA by providing input (membership, highlights, awards,...), by participating in conferences, and by engaging in technical activities (benchmarking, propulsion, applications,...). The success of the technical activities has been limited. Jean-Francois wants to solicit ideas and opinions about whether we should engage in more technical activities, and if so, what those activities should be. If you have ideas along these lines, please contact Pradeep Raj, who will be the focal point in this area. 2. TC OPERATIONS - Most work is done by individuals in intense work periods before meetings. Should we change our mode of operation? How many times should we meet, and for how long? Can we maximize effectiveness during meetings and minimize travel requirements? Jean- Francois will act as the focal point in this area, so please contact him with your ideas. 3. TC MANUAL - The TC manual needs to be rewritten. Current manual is a collection of disjointed parts. 4. TC MEMBERSHIP - Process of selecting members is being reviewed. Should we change our (2 of 7)12/29/ :29:25 PM

295 MDO TC Newsletter No. 20: Dec 1995 approach to selecting/rotating members? This process should broaden committee diversity, including representation by discipline, and representation by industry/academia/government. Please contact Chris Borland with any ideas on this. The makeup of the committee was further discussed - committee has been dominated by structural specialists in the past. It was suggested that the discipline of costing has an important place in MDO and possibly should have two sessions at the next MA&O conference. MA&O CONFERENCE - SEATTLE Karl Bradshaw from the AIAA is the new Meeting Director for the biennial Seattle MA&O Conference (replacing Julie Walker), so we will be working closely with him in order to bring the meeting together. Karl's phone number is (202) , and his address is karlb@aiaa.org. A conference planning report by Bloebaum was passed out by Chris. Call for papers should be coming out in the November (possibly October) Aerospace America. AIAA has made arrangements for 6 parallel sessions if we need them - last conference had five. Included in the report was a list of superchairs, who have responsibility for getting papers reviewed in their areas of expertise. Anyone wanting to be added to this list, contact Christina Bloebaum (clb@eng.buffalo.edu). Christina is the Technical Chair of the Conference. Anyone with ideas concerning speakers at the conference, please contact Chris Borland. SUBCOMMITTEE REPORTS Planning Subcommittee (Barthelemy) The inclusion, on the planning subcommittee, of the chairs of the various subcommittees was discussed as a new approach to facilitating communication within the TC. Chairs will participate in the planning committee's activities with the intent of representing the membership of their subcommittees. Proposals for activities or policies may be drafted in the planning subcommittee for further consideration, modification or reframing by the whole TC. The planning subcommittee considered the review of four areas of TC activities. For each area, one focal point was identified. The focal point is to develop a draft proposal for his area of review to be available to the membership, both on the Web and by , by the middle of November. Full membership involvement begins now, by sending suggestions to the focal points. Once the proposals are available, the membership then has another month to comment. The focal points are then to finalize their proposals which they will present for approval at our Reno meeting and submit for an up or down vote. Proposed modifications will then be documented in our TC manual. While each review must consider all aspects of the activity considered, this is not an exercise in change for the sake of change, rather it is an opportunity to look at what we are doing, how we are doing it, and to determine if there is any value added in changing some aspects of the way we do business. To a! void devoting too much of our energy to this exercise, we will essentially conclude it at our next meeting. The four areas for review are as follows: 1. TC OPERATIONS: Barthelemy will be the lead for this review. The objective is to address TC organization, TC meeting schedule and format and any other issue that could affect the (3 of 7)12/29/ :29:25 PM

296 MDO TC Newsletter No. 20: Dec 1995 productivity of the TC. 2. TC TECHNICAL ACTIVITY INVOLVEMENT: Raj will be the lead for this review. The TC has had several attempts at carrying out technical activities. At this point we have benchmarking which looks at standard test problems, as well as education which puts together short technical courses, publications which deals with highlights and special issues of journals and conference support where we organize technical sessions or review papers. The last three activities are traditional TC involvement and there is a sense from the membership that more technical activities are warranted. Yet previous attempts have not always succeeded. 3. TC MEMBERSHIP: Borland will be lead for this review. Memberships begins with inviting qualified technical people to apply, selecting new members so that the TC's membership becomes more diverse, represents better the different disciplines at play in aerospace design and balances properly representation by industry, academia and government. 4. TC OPERATIONS MANUAL: Thomas will be lead for this review. Our current manual, now available on the Web, is quite incomplete and sometimes quite inaccurate. We will review the outline of the manual, its content, as well as the process by which we keep it current. Awards Subcommittee (Thomas) The purpose of the subcommittee and the process of upgrading membership status for the AIAA was discussed. The call for nominations for the MDO award will be in the October Aerospace America issue. Benchmarking Subcommittee (Striz - not present presented by Dudley Smith) A set of test problems is being developed by NASA-Langley. These should be available for benchtesting on the World Wide Web around the time of the 1996 SDM Conference. An MDO model of the Airbus wing will be donated to the MDO TC. Discussions with the AIAA are being held to see if we can locate some of the larger benchmarking models on AIAA computers, so individual companies will not have to supply these resources ( disk space, etc.). The question of the format necessary and the standards to be applied for benchmark testing was discussed. ACTION: Todd Beltracchi of Aerospace Corp. will get a copy of his paper on this subject to Fred Striz. Conference Support Subcommittee (Santangelo - not present) A representative for the 1997 ASM conference, who must also attend the planning session at the 1996 meeting, was needed. Shreekant Agrawal volunteered for this task. In addition, Paul Gelhausen volunteered to provide support at the 1996 Design Conference in Los Angeles. ACTION: Jean-Francois will contact Andrew Santangelo concerning these conference support representatives. Liaison Subcommittee (Thomas) Representatives are needed for Materials, GNC, Standards, Propulsion, and AI. Reports were not available from the representatives to other TC's. ACTION: Thomas will contact liaison members and assemble reports. Publications Subcommittee (Livne) Annual Aerospace America article on MDO has been done. Discuss ensued about possibility of pushing for a dedicated issue of AIAA Journal or Journal of Aircraft dedicated to MDO. A joint collaboration of the Publications and Benchmarking Subcommittees was proposed to establish and publish a standard set (4 of 7)12/29/ :29:25 PM

297 MDO TC Newsletter No. 20: Dec 1995 of problems and solutions for MDO problems. ACTION: Eli will contact Fred Striz. They will look into what's involved, and Eli will report on conclusions at Reno. Farrokh Mistree has written a paper which has been reviewed by several TC members. There was a discussion about how to publish this - should it be an MDO TC paper, or should Farrokh publish it? ACTION: Jean-Francois will contact Farrokh and discuss the issue. Newsletter Subcommittee (Bloebaum - not present) We want to make an effort to get the newsletter out within a month of each TC meeting. Education Subcommittee (Renaud - not present) A report was provided by John. The following items were mentioned: 1) A session/panel on engineering education at the 1996 MA&O will be held. John and Christina will be coordinating. Contact them if your are interested in participating. 2) Planning is underway for an AIAA workshop on work-flow management to be given at the MA&O Conference. 3) ISSMO Education Subcommittee wants to coordinate activities with our Education Subcommittee. Applications Subcommittee (Radovcich - not present) Nick is probably going to be the new chairman. ACTION: Jean-Francois will contact Nick for report. MDO TC INFORMATION ON THE WORLD WIDE WEB Harold Thomas distributed information concerning Web access for TC members. All TC members should obtain a copy of this (perhaps it will appear elsewhere in the newsletter). Included information on the Web site is the operations manual, membership list, subcommittee list, latest newsletter, and latest minutes. These are all hyperlinked together, so you only need to get to one site. The operations manual address is: Please check out the information on these sites and send any corrections to Harold Thomas at thomas@neptune.net and Jean-Francois at j.f.barthelemy@larc.nasa.gov. Since Harold is providing this service to the TC, he asked to be allowed to include a message saying that his consulting firm is sponsoring this page. A motion to this effect was made, seconded, and approved by the TC. NEW BUSINESS There is a meeting on MDO September 26, at NASA-Langley which should be of interest to our TC. MEETING SCHEDULE NOTE THAT THERE IS A CHANGE IN OUR USUAL SCHEDULE! (5 of 7)12/29/ :29:25 PM

298 MDO TC Newsletter No. 20: Dec 1995 NEXT MEETING: Thursday, Jan. 18, 1996 in Reno (Last day of ASM Conference) - meeting tentatively scheduled for the whole day Thursday. SPRING MEETING: Wednesday, April 17, 1996 in Salt Lake City - meeting tentatively scheduled for the whole day Wednesday. FALL MEETING: Sometime during the week of the MA&O Conference, September 4-6, 1996 in Seattle. The meeting was adjourned at 2305 hours. Respectfully submitted on 10/25/95, Allan Goforth Lockheed Martin Skunk Works Dept , Bldg Lockheed Way Palmdale, Ca Tel: (805) Fax: (805) Home @compuserve.com Business egoforth@ladc.lockheed.com Please send your comments and contributions for the next MDO TC Newsletter to: Professor C. L. Bloebaum Department of Mechanical and Aerospace Engineering 1009 Furnas Hall State University of New York at Buffalo Buffalo, New York address is: clb@eng.buffalo.edu work phone is: (716) x2231 departmental phone is: (716) FAX is: (716) AIAA MULTIDISCIPLINARY DESIGN OPTIMIZATION TECHNICAL COMMITTEE 1994/95 Chairman: Jean-Francois Barthelemy (6 of 7)12/29/ :29:25 PM

299 MDO TC Newsletter No. 20: Dec 1995 Members: Shreekant Agrawal Kumar G. Bhatia Christina L. Bloebaum Carl M. Bosch Clark Briggs Robert Canfield Peter C. Coen Mark Drela Mark S. Ewing George Fadel Paul Gelhausen Omar Ghattas Joseph Giesing Edward A. Goforth Ramana V. Grandhi Raphael Haftka Srinivas Kodiyalam Johann Krammer Charles Lawrence Eli Livne Samuel C. McIntosh Achilles Messac Farrokh Mistree S. N. B. Murthy Henry Neimeir Jerry Newsom John R. Olds Paul Pierson Nick Radovchich Masoud Rais-Rohani Pradeep Raj David C. Redding John E. Renaud Gerald Seidel Abdon E. Sepulveda Gary Stanley Alfred G. Striz Harold Thomas Rudy Yurkovich Assoc. Member: Andrew Santangelo Past Chairman: Christopher Borland Back to Newsletter list Back to MDO TC Home Page Last Updated: April 24, 1996 Michael Eldred, (7 of 7)12/29/ :29:25 PM

300 MDO TC Newsletter No. 19: July 1995 MDO TC Newsletter No. 19: July 1995 FROM THE EDITOR Christina L. Bloebaum Hello All! This newsletter is a bit bare of miscellany but packed with minutes. Please remember that you can anything at all to me that you think might be of interest to the MDO community and I will put it in the newsletter. You can also send it to me via snail mail (by post office, that is) or FAX. Remember that the next Multidisciplinary Analysis and Optimization Symposium is only a little more than a year away. The Call for Papers will be sent out within the next few weeks so that you can start preparing those abstracts. Be sure you read the instructions VERY carefully, since any abstracts that are not responsive to the Call will be rejected. CHAIRMAN'S CORNER Jean-Francois Barthelemy This first `Chairperson's Corner' of my tenure as TC Chair must begin with a heartfelt Thank You for your confidence. I am honored to have been selected to chair the committee and you have my pledge that I will do so with all my energy. As I indicated in my brief remarks in New-Orleans, I believe this committee to be yours, I know that the membership will make the difference into what the committee achieves and contributes. I therefore see my responsibility as one of coordination and facilitation as well as communication with AIAA. The committee has had impressive accomplishments since its creation in Under Jarek Sobieski's pioneering leadership, it sprang from an idea in a few people's minds to a coherent organization. It produced a number of important publications, helped run very successful biennial meetings in San Francisco and Cleveland and participated in several other respected forums. The membership has progressively evolved from a dedicated group of mostly structural optimization specialists to an eclectic organization of multidisciplinary and disciplinary experts. Chris Borland's tenure has seen expansion in these areas, particularly the very successful Panama City MA&O meeting and the planning for the upcoming Bellevue MA&O meeting. The MDO community is getting more coverage in the technical press and our second AIAA highlight is being written. In the words of Chris Borland, we are indeed in interesting times as the aerospace industry that we mostly serve is undergoing tremendous reshaping. There is clear consensus that continued profitability is keyed to a multidisciplinary approach to problem solving, whether in performance design, life-cycle cost engineering or in process management. Our committee is poised to be a major contributor in this (1 of 10)12/29/ :29:26 PM

301 MDO TC Newsletter No. 19: July 1995 reshaping. I believe that it is timely that we reflect on where we have been, where we are and where we are going and I intend to devote our next meeting to beginning this process. I believe that we must review the mission of the committee as well as its operations. It is an appropriate time for us to look at all our activities, decide which have served their purpose, which need to continue as planned, which need to be carried on differently and which need to be started. While I want the Planning Subcommittee to facilitate this exercise, I want it to be clear that every committee member is expected to participate. I urge all of you to attend our next meeting prepared with your reflections and suggestions. To enhance this process, I am enlarging the Planning Subcommittee membership to include its current members and all subcommittee chairs. I see this as a means to providing a better communication mechanism within the committee as each subcommittee carries out the work in this review while the Planning Subcommittee proposes a process and integrates the suggestions. The results of this review are likely to require changes in our operations and I want those documented in our operations manual. Harold Thomas is working on getting an updated version of the operations manual available on WWW. I consider this version a draft that will be modified by the result of our review and should be finalized as soon as possible, no later than when our membership is renewed in the Spring of Many thanks to Harold for taking the initiative on this. While our committee reviews its mission and operations, normal business will continue and planning is well underway for the next MA&O conference in Bellevue, WA 4-6 September Chris Borland will chair and Christina Bloebaum will serve as Technical Program Chair. The call for paper will be available shortly and mailed by AIAA. I am grateful that chairs from previous MA&O have volunteered their expertise and agreed to serve on an Organizational Support Committee while Prof. George Rozvany has offered to coordinate European contributions. Our next committee meeting is Monday 18 September 1995, the evening before the beginning of the Aircraft Technology and Operations Congress in the Sheraton Hotel (check AIAA announcements for details). The Planning Subcommittee is to meet between 16:00 and 18:00, while the full membership meeting will be 18:00-22:00. I am looking forward to seeing you there. Jean-Francois Barthelemy 804/ (phone) 804/ (FAX) j.f.barthelemy@larc.nasa.gov MINUTES OF THE MDO TC MEETING Reno, Nevada, January 9, 1995 The meeting was called to order at 1837 hours by chairman Christopher Borland. Nick Radovcich recorded the minutes. For member, guests and visitors present, see attached list. Special Thanks to those and their sponsoring organizations for consecutive attendance. Join a Sub-committee. MEMBERSHIP CHANGES AND ELECTIONS (2 of 10)12/29/ :29:26 PM

302 MDO TC Newsletter No. 19: July 1995 PRESENTATION David Riley of the TAC Finance Committee gave a presentation on "Everything you always wanted to know about AIAA Finances (and were glad you didn't ask) or "Where does all the money go?". The bottom line issues revolved around the base and the cost added to the base. The base budget has cyclic highs and lows. David suggested that much could be accomplished if the lows could be filled in with other functions which will attract support from the members. The cyclic nature of the attendance are not well understood. The even year and location of a conference are just some of the factors. The added cost (to the base) comes from the organizing committee requested services. Costs like slide projectors, VTC's, etc. are supplied by a third party supplier or by the facilities where the conference is being held. A simple request like refreshments in the afternoon sessions comes to 2-4 $ per serving. The added costs are increasing. INTRODUCTION OF MEMBERS AND VISITORS PANAMA CITY MINUTES REVIEWED, CORRECTED, AND APPROVED ROSTER AND SUB- COMMITTEE MEMBERSHIP WILL BE UPDATED Chris passed out AIAA MDO TC Subcommittees brochure. He asked for input for corrections. SUBCOMMITTEE REPORTS Conference Support (Santangelo) Aerospace Sciences 95 - Santangelo, MDO first half in the morning was well attended. The Wed session needs help because four people bailed out. Much discussion on the form of paper versus informal presentations. No conclusions except to note that AIAA policy is no paper no podium. 37th SDM April 10-12, New Orleans - Bloebaum (not present; no report) Design Technical Conference - Minneapolis (? not listed in the AIAA Meeting Schedule) - John Renaud will be the liaison st Aircraft Engineering, Technology, and Operations Congress in Los Angeles Mariott Hotel Airport Sept This could be the site of our Fall meeting. Current MDO Symposium; Sept 7-9, 1994 in Panama City, Florida - 5th AIAA/AF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization. Sobieski General Chair, Berke, Borland, Rozvany, AA). 110 papers were from academia. MDO Symposium Borland reporting: Christina Bloebaum is the Technical Chairperson. Received much material from Sharon Padula's Panama City team. The Jackson Hole site will not work. (3 of 10)12/29/ :29:26 PM

303 MDO TC Newsletter No. 19: July 1995 Working with Julia Walker on Bellevue Hyatt near Seattle. Conflict with ASME 9/ Next target is the 9/16-20 with a possible switch with ASME date. Working on Boeing supporting a reception at Museum of Flight and tour. This will be in stead of a boat ride. The next option is a tour of the Boeing Everett Plant. This is a major undertaking and would add another day especially for those from the East coast. Liaison-Straub Needs a lot of help- many vacant posts; Straub reported that he will be leaving after the SDM meeting. Structural Dynamics TC - no report GNC: no report Air Breathing Propulsion: no report Propulsion TC: no report Structures TC: no report HSCT:? Education- Renaud (not present - Todd reported) Remind everyone of the call for papers due 2/1/95. Chris said he did not know of any offerings. Publications - Salama (not present Borland reported) Many thanks to Eli Livne for his Highlights Article in the Aerospace America. A discussion about distributing material via CD's. Two issues - software and practical considerations for updates required in iterations. Newsletter - Bloebaum (not present) All MDO newsletters will be on the world wide web aero.stanford.edu/mdotc.html. Awards- Neill (not present) Thomas reported. Associate fellow nominations are not as competitive as first assumed. However, fellow nominations are very competitive. Senior members elections are almost automatic; Some discussion as to what that really means. Anyway, the process is proceeding. Planning- Borland Applications for Membership (May 95 - April 98) are in. 14 Received with a good mix of industry, government and academia. However, the applications are heavy on Structures and light on other disciplines. There are 14 members leaving (unless request to continue). If we accept all the applications, MDO will be over the 35 limit. However, this does not appear to be a problem at AIAA. Benchmarking- Venkayya (not present) Beltracci says that real progress in bench marking has be slow at best. The direction of this activity is not clear. (4 of 10)12/29/ :29:26 PM

304 MDO TC Newsletter No. 19: July 1995 Reporting Guidelines (sub-committee of one, and after leaving - zero) - integrating the comments of three reviewers. Good samples at a case level is required. Todd's background is in Mechanical Engineering and feels that he could cover that. He has little understanding of thermodynamics and structure optimization. Guidelines for engineering results - we need people with aircraft design experience. There is a lack of background to establish standards here. However, some has accepted Todd's paper as the guideline for students to report results. Chris- is there room to have an educational guideline? Todd - yes, he has an example with source code. The main focus is accessibility. Discussed possibility of working this form into MDO papers. This issue will be further explored in the next call for MDO papers. WE NEED MEMBERS OF THIS TC TO CARRY ON THIS WORK AFTER TODD LEAVES. Applications- Coen (not present) no report Propulsion - new chair Chris with limited travel budgets, electronic communication between sub-committee members will probably be required in the planning of their activities. none PROPOSAL (Raj Pradeep) New Membership "Care Package": Outline of TC/TAC Framework History, mission, vision Sub-committee structure with charters Roster (proposal for care package accepted; include with acceptance letter) New Membership Selection Committee Review Application, Maintain and Update Roster (in place) Planning Sub-committee redefined Future activities - conferences, etc. (in place; as is) Present and review 3-year plan once/year ( no action items) Recommend and investigate Short Courses Publications of Proceedings on CD-ROM ( already discussed) Liaison and Subcommittee reports mailed ahead of time Discussed - another candidate for World Wide Web - need a directory and how to use. The liaison person would review newsletters from other TC and produce a one page summary to be included in the MDO newsletter. This could make the time at TC meeting more productive. CHAIRMAN ANNOUNCEMENTS NEW BUSINESS (5 of 10)12/29/ :29:26 PM

305 MDO TC Newsletter No. 19: July 1995 none TC next meeting; time and place- The next MDO TC meeting was set for 1930 hours Monday April 10, 1995 at New Orleans- SDM. The meeting was adjourned 2207 hours. Respectfully submitted on 3/30/95 Nick Radovcich Lockheed Aeronautical Systems Co. Dept 73-HA, Zone 0988 Marietta, GA Tel: (404) Fax: (404) MINUTES OF THE MDO TC MEETING New Orleans, LA, April 10, 1995 The meeting was called to order at 1930 hours by chairman Christopher Borland. Nick Radovcich recorded the minutes. For member, guests and visitors present, see attached list. Special Thanks to those and their sponsoring organizations for consecutive attendance. MEMBERSHIP CHANGES AND ELECTIONS Chris Borland, following the steps of Jarek Sobieski, passed the gravel to Jean Barthelemy. Chris assumes the Past-Chairman. Many thanks for a job well done and making the TC better. Many Thanks to the members ( and their supporting organizations) for their service on the TC: Sobieski (NASA), Beltracchi (Aerospace Corp), Berke (NASA), Gallman (NASA), Harry (TRW), Hill (NASA), Kroo (Stanford), Neill (Universal Analytics), Salama (JPL), Straub (McDD), Taylor (Old Dom. U.), Venkayya (AF Wright L), Wainfan (Mc DD); Associates: Bell (Aerospace Corp), Sikes ( PDA Eng). Welcome to the new Members: Agrawal (McDD), Briggs (JPL), Canfield (AFIT/ENY), Fadel (Clemson U.), Ghattas (CMU), Giesing (McDD), Haftka (UofF), Kodoyalam (GE), Lawremce (NASA), Messac (NorthE. U.), Pierson (LockMart), Rais-Rohani (MissStU), Seidel (NASA), Stanley (LockMart), Thomas (StrOptSpec), Santangelo (MichTechCorp). Harold Thomas became the new chair for Liaison Subcommittee, replacing Straub and also Awards replacing Neill. Clark Briggs became the new chair for Publications replacing Salama. Alfred Striz with Raphael Haftka became co-chairs for Benchmarking replacing Venkayya. none PRESENTATIONS (6 of 10)12/29/ :29:26 PM

306 MDO TC Newsletter No. 19: July 1995 INTRODUCTION OF MEMBERS AND VISITORS RENO MINUTES REVIEWED, CORRECTED, AND APPROVED Minutes were distributed at the meeting. They were not in the news- letter. ROSTER AND SUB-COMMITTEE MEMBERSHIP WILL BE UPDATEDS Chris passed out Roster for update. SUBCOMMITTEE REPORTS 6th MA&O (1996) - Bloebaum (Tech-chair)/Borland (General Chair) Bloebaum reports Around middle of January all the abstracts will be collected, sorted out, and sent out to the super chairs. The super chairs will then distribute them for reviews in twenty categories. A sign-up sheet for super chairs (10-15) was distributed. Christina will contact the super chairs in September. Concerned about drop off in attendance during the last days of technical presentations and the attraction of one paper which drains off the attendance from the other papers. Wants inputs about selecting two or three papers to be presented without competition, and about work in progress. The projected growth of the conference requires the consideration of expanding multiple sessions, providing for shortened presentations, or extending the length of the conference. There was extensive discussions on the introduction of 20 and 30 minute presentations; increasing the rejection rates and keeping the numbers the same as last time, having a poster session (no), and a 1-2 hour overview from industry (yes). There was no significant discussion on lengthening the conference. The members are urged to consider these options and reply back to Chistina before next meeting. Chris - a tour of the Boeing plant at Everett is planned for Friday afternoon or maybe Saturday. Airline schedules for going East from Seattle Friday night are not many except for some redeyes. Conference Support - Santangelo (not present - Borland reporting) st Aircraft Engineering, Technology, and Operations Congress in Los Angeles Mariott Hotel Airport Sept Borland. Had one MDO abstract in the High Speed Civil Transport to give a flavor of the MDO process th AIAA Aerospace Sciences Meeting in Reno Jan Santangelo rep th Structures/SDM Conference in Salt Lake City Apr ; Adapt Structures and Dynamics Specialist Apr Mistree/Grandhi rep. attending the organizing meeting at this time. Christina reported on the interactive plenary sessions of which MDO had 7 papers. These were selected on basis of their high quality which were germane to the subject. There were first (7 of 10)12/29/ :29:26 PM

307 MDO TC Newsletter No. 19: July 1995 and second place awards of $500 and some software. Liaison-Thomas Currently has a list of 5 members on this sub-committee. Will report on Structure Dynamics Oct 13 meeting. They were unhappy with the poster sessions. Christina had reports that these were the best of the papers. No resolution of the different field of visions. Assignments - Fred Straub for SDM Paul Gelhausen for A/C John Renaud for GNC Rudy Yurkovich for Applied Aero Open - Structures and Propulsion, John Renaud - Roster update Education- Renaud (not present) Bloebaum reported, written report distributed. 1. Guidelines for Reporting Engineering Optimization Results (T. Beltracchi) - Todd reports that Kroo will put a copy of this guideline on the WWW at Stanford and it was submitted as a paper to next fall's ASME design Automation Conference. 2. MDO Test Problem - Larry Green (l.l.green@larc.nasa.gov) and Natalia Alexandrov (natalia@tab00.larc.nasa.gov) are compiling a suite of MDO test problems in a problem description form (equations, analysis tools used, etc.) Notre Dame has submitted 10. This project is in the early stage. Contact the principles for access or for making contributions MDO Conference will include a session/panel on Engineering Education. (See Christina's Comments in the MDO newsletter) There are five programs funded by NASA for industry interaction. 4. Thanks to those committee members who submitted MDO papers to the 1995 ASME Design Automation Conference, Boston next September and who participated in the review process. Publications- Salama (not present Borland reported) Repeated the many thanks to Eli Livne for his Highlights Article in the Aerospace America. A discussion about distributing material via CD's. Two issues - software and practical considerations for updates required in iterations. Newsletter - Bloebaum All MDO newsletters will be on the world wide web aero.stanford.edu/mdotc.html. Need more timely secretary inputs. Chris complemented Christina on the newsletter quality and its timely publication. Awards- Neill (not present Thomas reporting) There were a number of nominations from the last time. Nomination deadline is June 15. Planning- Borland Thanked the outgoing members for their service and welcomed the new members (see Elections). Bench marking- Venkayya (8 of 10)12/29/ :29:26 PM

308 MDO TC Newsletter No. 19: July 1995 A status of work done and what needs to be done. Discussion was far ranging. Revisited what makes a good test case. Some discussion as to direction of the subcommittee. One question - "Who is the Customer". No converts. Striz and Haftka became new co-chairs. Applications- Coen ( not present) no report. Propulsion - new chair LIST OF ACTION ITEMS 1. Comments on Christina questions posed under 1996 MDO. 2. Yes on industry overview - Christina 3. Work in process; How many paper slots? - to Christina 4. Exchange of newsletters between TCs Words of advice from past-past-chairman - Sobieski none CHAIRMAN ANNOUNCEMENTS NEW BUSINESS TC next meeting;time and place- The next MDO TC meeting was set for 1800 hours Monday, September 18, 1995 at AETOC, Los Angeles. Buffet will be served. The meeting was adjourned 2017 hours. Respectfully submitted on 7/17/95 Nick Radovcich Lockheed Martin AeronauticalSystems Dept 73-HA, Zone 0988 Marietta, GA Tel: (404) Fax: (404) AIAA MULTIDISCIPLINARY DESIGN OPTIMIZATION TECHNICAL COMMITTEE 1994/95 (9 of 10)12/29/ :29:26 PM

309 MDO TC Newsletter No. 19: July 1995 Chairman: Jean-Francois Barthelemy Members: Shreekant Agrawal Kumar G. Bhatia Christina L. Bloebaum Carl M. Bosch Clark Briggs Robert Canfield Peter C. Coen Mark Drela Mark S. Ewing George Fadel Paul Gelhausen Omar Ghattas Joseph Giesing Edward A. Goforth Ramana V. Grandhi Raphael Haftka Srinivas Kodiyalam Johann Krammer Charles Lawrence Eli Livne Samuel C. McIntosh Achilles Messac Farrokh Mistree S. N. B. Murthy Henry Neimeir Jerry Newsom John R. Olds Paul Pierson Nick Radovchich Masoud Rais-Rohani Pradeep Raj David C. Redding John E. Renaud Gerald Seidel Abdon E. Sepulveda Gary Stanley Alfred G. Striz Harold Thomas Rudy Yurkovich Assoc. Member: Andrew Santangelo Past Chairman: Christopher Borland Past Chairman: Christopher Borland Back to Newsletter list Back to MDO TC Home Page Last Updated: April 24, 1996 Michael Eldred, (10 of 10)12/29/ :29:26 PM

310 MDO TC Newsletter No. 18: April 1995 MDO TC Newsletter No. 18: April 1995 FROM THE EDITOR: Christina L. Bloebaum Hello everyone. Looking forward to seeing you all at SDM, which is right around the corner. I am announcing a slightly different approach to the newsletter, which will be implemented immediately following the SDM Conference, as long as no one has any strong objections. Instead of sending the newsletter out right before a conference, I propose it be sent out right after. This should make it much easier for everyone to get submissions to me, since most TC members will be in attendance at the meetings. You can either hand your submissions to me directly at the conference or /send them to me immediately following. We can discuss this at the TC meeting on Monday, April 10, at the SDM Conference. I have included an editorial that came across the internet on Cray and his recent filing for Chapter 11. I found it to be quite interesting and hope you do as well. Good reading! CHAIRMAN'S CORNER:Chris Borland Dear Fellow TC Members, The old Chinese curse says "May you live in interesting times," and we certainly do. Most of you are aware of recent upheavals in the Aerospace Industry, and although the developing situations (which seem to change minute by minute) may be disheartening and disorienting to many, I hope that we can look at as an opportunity for further insight and growth. Many of the reorganizations that we hear about may actually give some opportunity to consider the way business is done, and the chance to establish some new paradigms. If we try to think about what is really needed, a more enlightened approach to cross-functional and interdisciplinary activities is clearly a prime candidate. The excellent ground work that the MDO community has established over the past several years should be a starting place for even more advancement in the future. However, I think we still have a selling job to do as to MDO's long term worth and how it will affect the business's bottom line. The more good examples of practical applications and results that can be shown the easier this job will be. Please keep this in mind as we press on into the ever-exciting future. (Off the soap box). The 6th Multidisciplinary Analysis and Optimization Symposium will be held at the Hyatt Regency Bellevue Hotel in Bellevue, Washington, on September 4-6, Dr. Christina Bloebaum of the State University of New York at Buffalo has agreed to serve as Technical Program Chair, and I will serve as General Chair. Julie Walker of AIAA and I have visited the facility and think it will be well suited to our meeting. It is located in downtown Bellevue, about 20 minutes from downtown Seattle and minutes from the Airport by Shuttle. There are many interesting shops and eating places located both within the hotel complex and nearby, and for your significant others the world-famous Bellevue Square (1 of 10)12/29/ :29:28 PM

311 MDO TC Newsletter No. 18: April 1995 Shopping Mall and Art Museum is across the street. This is the optimum time of the year to visit the Pacific Northwest, and we hope to offer a variety of interesting activities to supplement the usual excellent technical program. Since this is the week following Labor Day weekend, some of you may wish to spend a few extra days enjoying our expected fabulous weather and scenery (no guarantees!) More details will be announced at upcoming TC meetings and in the newsletter. Our next TC meeting will be held in conjunction with the Structures, Structural Dynamics, and Materials Conference in New Orleans. The meeting will be Monday, April 10, at 7:30 PM, following a reception at 6:30 PM. This is our "no meal" meeting, so hit the reception and eat all the free goodies you can! This will be my last meeting as Chairman, and at its conclusion the virtual gavel will pass into the capable hands of Jean-Francois Barthelemy. Hope to see you all there. Regards, Chris Borland AGENDA FOR UPCOMING MDO MEETING Monday, April 10 at the AIAA 36th Structures, Structural Dynamics and Materials.Conference in New Orleans, LA. The meeting will start at 7:30 PM. There is a reception scheduled for 6:30 PM, so we will not be serving food. Room will be posted or in the TC meeting list available at the registration desk. 1. Meeting called to order 2. Introduction of members and visitors 3. Minutes Review, Correction, and Approval 4. Update of roster 5. Subcommittee reports: Conference Support - Santangelo MA&O (1996) - Borland Liaison - Straub Education - Renaud Publications - Salama Newsletter - Bloebaum Awards - Neill Planning - Borland Benchmarking - Venkayya Applications - Coen Propulsion -? 6. Chairman's announcements 7. Business from the floor 8. Introduction of New Chairman 9. Upcoming TC meeting information 10. Adjourn 9037 CASH-STARVED CRAY COMPUTER CLOSES, SEEKS CHAPTER 11 (2 of 10)12/29/ :29:28 PM

312 MDO TC Newsletter No. 18: April NEWS FLASH by Norris Parker Smith, Editor at Large, HPCwire Why did Seymour Cray's company, Cray Computer Corporation (CCC), descend into bankruptcy despite his unmatched contributions to computing, his remarkable skills at computer architecture and manufacturing, and his exceptional persuasiveness? How will the absence of CCC affect the high-performance market -- and the high-performance computing community? The answer to the first question consists of a few simple propositions: The world changed; Seymour Cray tried hard to keep up with those changes without compromising his own vision of high-performance computing; Toward the end, he tried very hard indeed. Adjusting prices downward and yielding to the demands of modern marketing, he accepted that the grace, ingenuity and redoubtable performance of his solutions might not be enough to close sales; Despite these efforts, he could not obtain the customers he needed so desperately; If solid revenue had been in reach, he might have been able to raise more funds; Neither hope came true in time. Just a few weeks ago, stockholders approved an additional stock issue. Placement was attempted outside the United States in order to avoid the delay required for SEC filing. The foreign investors evidently decided that the risk was too great. Lack of cash forced CCC to close and most of CCC's 350 workers were dismissed. THE IRONY OF ORDINARINESS Two clauses in these statements require further examination -- "The world changed" and "his own vision of high-performance computing." How has the world changed? Some commentaries on CCC's decision to seek the protection of Chapter 11 have attributed it to a decline of supercomputing brought about by the loss of easy defense money and the proliferation of killer microprocessors. This is mostly to the point, but supercomputing has not declined. It is, in fact, thriving to a degree never approached while Seymour Cray and supercomputer were identical in the public mind, like Einstein and relativity. Supercomputing is thriving because it has changed so much that the old term -- always half-description, half-slogan -- has acquired misleading implications. The days of expensive, delicate machines, presided over by specialists and used mostly by people with exceptional requirements, are passing. (3 of 10)12/29/ :29:28 PM

313 MDO TC Newsletter No. 18: April 1995 Supercomputing has become ordinary; just another way to do computing. In this perspective of his long and productive career, this outcome means that Seymour Cray's lifework has been a remarkable success. Ironically, as Mr. Cray defined the objectives of CCC and the character of its products, it was unable to find a place in a world of ordinariness. Seymour Cray has always accomplished the extraordinary and he wanted to do it one more time. GOLDEN YEARS In the golden years, supercomputing supported one profitable medium-sized company, Cray Research, three Japanese emulators that probably rarely made much genuine profit doing it, and a few small companies pursuing different paths, like Thinking Machines (TMC) and Intel's supercomputing (now scalable) computer division. Both TMC and Intel were dependent to some degree on outside funds -- DARPA subsidies for Thinking Machines and support for Intel's parallel-processing venture from the central treasury at Intel headquarters where the money is made. Dozens of would-be Craylets rushed to occupy a narrow niche called mini- supercomputers. Only Convex survived, doing well yet significantly smaller than Cray Research. Thus, there was only one influential, self-sustaining operation in the industry, Cray Research. It was shaped to a remarkable degree by Seymour Cray's personal creativity, persistence and skill. If one includes the earlier years at Control Data when Seymour Cray was beginning to establish his way to do heavy-duty computations, the span extends to almost two decades. In modern times, few individual creative persons have shaped so much of a significant technology for so long. FOUR CHANGES In recent years, however, supercomputing has changed in four ways: 1. A raid-the-junkyard philosophy has been adopted. Microprocessors, other components and, in some cases, whole modules are borrowed from workstations or other technologies -- thus reducing costs and making it easier to raise reliability. 2. It has become yet another corporate phenomenon. Big companies like IBM, Digital, AT&T and Hewlett-Packard are now playing important roles. Silicon Graphics, which started a number of years after Cray Research concentrating upon specialized graphics workstations, now has more than twice the revenues of Cray Research. It has, with considerable success, gone into the lower end of supercomputing -- almost as a sideline. 3. Sales are increasing greatly. At the lower end (prices under $2 million), sales in the scientific/ technical market alone are expected to reach about $1.5 billion this year, 50 percent more than the highest figure reached during the golden age. For years, despite intermittent effort, supercomputing made few inroads into commercial markets -- perhaps three times as large as the scientific market. Although much skepticism remains among commercial customers, significant (4 of 10)12/29/ :29:28 PM

314 MDO TC Newsletter No. 18: April 1995 progress is now being made. 4. Ironically, sales are growing primarily in the lower levels, in systems with a few dozen -- or fewer -- processors and various strategies to share a central memory. In principle, Seymour Cray would be at home with this kind of architecture. Indeed, his efforts at CCC -- the CRAY-3 and CRAY-4 -- were in the most basic terms shared-memory multiprocessor systems with similar numbers of processors. The big difference nowadays: each multi-megaflop (soon to be gigaflop) processor of a typical sharedmemory multiprocessor sells for a few tens of thousands of dollars, not a couple of million. In late 1994, CCC brought its price per GFLOPS for the CRAY-4 down toward the levels of its competitors, but the change came too late. ADAPTATION This is not simply a reenactment of that great drama of American nostalgia, the worthy individualist whose high-quality small business or delightful country store is squeezed out by faceless, homogenizing corporate giants. The troubles of CCC can be illuminated by considering Cray Research which retained the imprint of Mr. Cray for some years after he left it, and Seymour Cray's historical baseline customers: the code-breaking/intelligence agencies and the big federal laboratories. Since the late 1980s, Cray Research has been seeking to adapt to the realities of a changing world. It has been a protracted struggle marked by the extrusion of two of the main protagonists: Steve Chen and Seymour Cray himself. Mr. Cray left in 1989 to, in effect, set up his own country store, operated according to his distinctive principles. Cray Research has gone on to expand its product line to a degree that would have been high heresy in earlier decades. It has now embarked upon a reconsolidation based on a multi-layer configuration, also pursued by Convex and other makers, that may now become a prevailing solution, especially for largescale problems and the ascent of Mt. Teraflop. Some new models even include memory caches, another heresy. Various euphemisms are applied by Cray Research and others, but "cluster" is the simplest description of the top layer of these proposed hierarchies, where nodes consisting of shared-memory systems are aggregated into a distributed supersystem. ANAGRAM OF LATENCY For a purist like Seymour Cray, cluster is just an anagram of latency. Bandwidths may be rising sharply (5 of 10)12/29/ :29:28 PM

315 MDO TC Newsletter No. 18: April 1995 and cleverness can disguise the effects of high latency, but it is inescapable. Seymour Cray has always preferred straightforward, simple solutions, combined with a willingness to invest much money and originality in the computational infrastructure that makes simplicity possible. His favorite mathematical statement is, in effect: "the best connection between two components is the shortest possible line." He rejected fancy ideas like caches that, in his view, introduced self-defeating complexities. Mr. Cray also emphasized fundamental virtues: plenty of bandwidth, especially to memory, careful attention to memory management, and a sound balance among processor power, memory and I/O. He quietly criticized, for example, parallel systems that claimed huge aggregate performance but were so imbalanced that actual capabilities were a small percentage of the claimed performance. HIGH OVERHEAD CCC was established in the hopes of achieving exceptional performance while pursuing these pure goals. In doing so, Mr. Cray largely avoided the borrow-parts-don't-make-them philosophy that now dominates most of high-performance computing. His strategy was to fit very fast processors into innovative, compact packages. The chips would be fast because they would be based on gallium arsenide (GaAs) rather than silicon. Mr. Cray chose, moreover, the most demanding of two basic ways to use GaAs. This led to much frustration and delay. Finally CCC acquired its own GaAs foundry. More time was spent achieving acceptable yields with this brittle, unfamiliar material. The intricate design and compact dimensions of the processor nodes required special light-fingered robots. Both were remarkable accomplishments, and Seymour Cray relished as always his ability to reach goals that others had scoffed at. Nevertheless, these accomplishments were also causes of added expense and delay. CCC thus ended up with exceptionally high manufacturing overhead while other vendors of highperformance systems were increasing modularity to keep costs down. Furthermore, many competitors were moving toward production rates in the hundreds of units per year while CCC's costs would be spread over a dozen or so units at best. None of these burdens would have been crippling if CCC's first product, the CRAY-3, had offered distinctively higher performance compared with preceding models and could sell into an unoccupied marketing window. Instead, Cray Research's C-90 reached the market at about the same time with similar performance. As CCC spokesmen later acknowledged, the timing was bad. CCC did make one tentative sale, to Lawrence (6 of 10)12/29/ :29:28 PM

316 MDO TC Newsletter No. 18: April 1995 Livermore National Laboratory (LLNL) for support of the Department of Energy's nationwide research program. In December 1991 when CCC was unable to meet delivery/performance goals, the order was cancelled. A small CRAY-3 was later placed at the National Center for Atmospheric Research (NCAR) where, after some time and effort, it became ready for production work. This was not followed, however, by an actual sale. DEDICATED, LOYAL CUSTOMERS From his early days at CDC, Seymour Cray depended upon a foundation of dedicated, loyal customers that could be counted upon to buy the single-digit serial numbers -- and thus provide cash flow for expenses required by later manufacturing and sales. This roster included national laboratories like LLNL, National Science Foundation-supported sites like NCAR and, later, the national supercomputing centers. Above all, Mr. Cray looked toward the cryptanalysis/image analysis/signal analysis requirements of federal intelligence agencies. Once again, these were the customers that Seymour Cray counted upon to put CCC on track toward customer acceptance and adequate cash flow. It never worked out. These agencies chose to stay with Cray Research which offered similar performance and much better prospects of financial stability. Even worse, these agencies became deeply interested in clustering -- of classical C90 vector supercomputers and, later, of Cray Research's new J90 scaled-down, modernized, shared-memory multiprocessors. Seymour Cray pressed ahead with the CRAY-4, an even-more-so machine with tighter design parameters and roughly twice the per-node performance of the CRAY-3. If CCC had not already spent all the money it could get, the CRAY-4 might have won some customers away from Cray Research's counterpart, the T90. Now, no one will ever know for sure. WIDER EFFECTS Most customers and competitors have undoubtedly anticipated -- and discounted -- the departure of CCC for some time. That would have been considered an inescapable outcome if it were not for the unique aura of Seymour Cray's name and personality. For most observers, timing was the only question. Now that uncertainty has ended, Cray Research may (7 of 10)12/29/ :29:28 PM

317 MDO TC Newsletter No. 18: April 1995 find it somewhat easier to sell T90s, due for volume shipment during the latter half of this year. The T90 will need all the luck it can get. The market for upper-end vector machines has shrunken, due to loss of market share to scalable parallel systems and to shared-memory devices like Cray's own J-series as well as decline in the supply of defense money. It would be a shame if CCC's technological achievements in taming GaAs and robotic manufacture would be allowed to gather dust. Seymour Cray himself suffers from his status (despite his own best efforts) as a mysterious celebrity as well as a highly-talented computer designer. This could be damaging: people have very short memories about celebrities and even shorter attention spans. Despite the unfortunate course of Cray Computer, however, Seymour Cray should -- and, it is to be hoped, will -- continue to receive respect for his persistence as well as his imagination and the contributions made during a long and unique career. Above all, his emphasis on the fundamentals on well-balanced systems deserves continuing reiteration. If Mr. Cray wishes to moderate somewhat his habit of silence, his comments could be valuable contributions to the ongoing dialogue of high-performance computing. Seymour Cray, like many quiet men, combines a gentle humor with a well-developed sense of irony. He was probably amused to hear that a hasty reporter in Minnesota misunderstood the initial news of CCC's filing for bankruptcy and told the world that Cray Research was seeking Chapter 11. This led to much fuss and a distinct outflow of resumes before the truth was re-established. Supercomputing may have become ordinary, yet the name Cray has not. It still commands respect -- and, at times, can cause confusion. HPCwire has released all copyright restrictions for this item. Please feel free to distribute this article to your friends and colleagues... HUMOR Excerpt from the Buffalo News - Ann Landers (Message from the Editor: I hope that no one will find this offensive. It is certainly not meant to be so in any way, shape, or form.) Why God never received tenure at any university He had only one major publication. It was in Hebrew. (8 of 10)12/29/ :29:28 PM

318 MDO TC Newsletter No. 18: April 1995 He had no references. It wasn't published in a refereed journal. Some doubt He wrote it Himself. He may have created the world, but what has He done since? The scientific community can't replicate His results. He never got permission from the ethics board to use human subjects. When one experiment went awry, He tried to cover it up by drowning the subjects. He rarely came to class and just told students, "Read the Book". Some say He had His Son teach the class. He expelled His first two students. His office hours were irregular and sometimes held on a mountain. Although there were only 10 requirements, most students failed. DESIGN EDUCATION INNOVATIONS C. L. Bloebaum In March of 1993, ASME held a conference entitled Innovations in Engineering Design Education in Orlando, Florida. The papers from the conference have been published by ASME as the Innovations in Engineering Design Education: Resource Guide (ISBN ). An awards program was established to identify the most noteworthy of these papers and were published in a separate cover entitled "Innovations in Mechanical Engineering Curricula for the 1990's". The overall award winner was a paper entitled "Reverse Engineering and Re-Engineering in Capstone Design", by G.A. Gabriele, L.N. Myrabo, J. Pegna, H.J. Sneck, and B.L. Swersey, from Rensselaer Polytechnic Institute. These are wonderful papers that I suggest everyone read - whether in academia or not. Remember, we will be having a session on Engineering Education at the next MDO conference so start thinking now! Please send your comments and contributions for the next MDO TC Newsletter to: Professor C. L. Bloebaum address is: Department of Mechanical and Aerospace Engineering clb@kronos.eng.buffalo.edu 1009 Furnas Hall departmental phone is: (716) State University of New York at Buffalo work phone is: (716) x2231 Buffalo, New York Fax is: (716) (9 of 10)12/29/ :29:28 PM

319 MDO TC Newsletter No. 18: April 1995 AIAA MULTIDISCIPLINARY DESIGN OPTIMIZATION TECHNICAL COMMITTEE 1994/95 Chairman: Christopher Borland Members:J.-F. Barthelemy Todd J. Beltracchi Laszlo Berke Kumar G. Bhatia Christina L. Bloebaum Carl M. Bosch Peter C. Coen Mark Drela Mark S. Ewing John W. Gallman Paul Gelhausen Edward A. Goforth Ramana V. Grandhi David P. Harry III Gary C. Hill Johann Krammer Ilan M. Kroo Eli Livne Samuel C. McIntosh Farrokh Mistree S. N. B. Murthy Douglas J. Neill Henry Neimeir Jerry Newsom John R. Olds Pradeep Raj David C. Redding John E. Renaud Mokhtar Salama Abdon E. Sepulveda Friedrich Straub Alfred G. Striz Arthur C. Taylor III Vipperla Venkayya Barnaby Wainfan Rudy Yurkovich Associate Kevin D. Bell Andrew Santangelo Gregory D. Sikes Members: Harold Thomas Past Chairman: Jaroslaw Sobieski Back to Newsletter list Back to MDO TC Home Page Last Updated: April 24, 1996 Michael Eldred, (10 of 10)12/29/ :29:28 PM

320 Download TC files Download TC files UNDER CONSTRUCTION This page is intended for the easy dissemination of electronic documents to TC members and Web site visitors. Currently downloadable documents include: Postscript version of operations slides: operations.ps Back to MDO TC Home Page Last Updated: May 3, 1996 Michael Eldred, 12:29:29 PM

321 Conferences Supported by the MDO TC Conferences Supported by the MDO TC World Aviation Congress 99, October 19-21, 1999, San Francisco, CA, USA. 38th AIAA Aerospace Sciences Meeting and Exhibit, January 10-13, 2000, Reno, NV, USA. 41st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, April , Westin Peachtree Plaza Hotel, Atlanta, GA, USA. 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, September , Long Beach, CA, USA. Other conferences with MDO content (not sponsored by AIAA). AIAA's calendar of conference and short course events. Back to MDO TC Home Page Last Updated: October 13, 1999 Michael Eldred, 12:29:29 PM

322 Conferences/Events with MDO Content Conferences/Events with MDO Content INFORMS Fall 1999 Meeting, November 7-10, 1999, Philadelphia Marriott Hotel, Philadelphia, PA, USA. ASME 2000 International Design Engineering Technical Conferences and the Computers and Information in Engineering Conference, September 10-13, 2000, Omni Inner Harbor Hotel, Baltimore, Maryland, USA. Conferences sponsored by the MDO TC. Back to MDO TC Home Page Last Updated: October 13, 1999 Michael Eldred, 12:29:30 PM

323 Short Courses Supported by the MDO TC Short Courses Supported by the MDO TC Optimal Design in Multidisciplinary Systems, AIAA Professional Development Short Course, St. Louis, MO, August 31-September 1, Software Tools and Techniques for Reducing Time and Cost in the Design Cycle, AIAA Professional Development Short Course, St. Louis, MO, August 31-September 1, AIAA's calendar of conference and short course events. Back to MDO TC Home Page Last Updated: July 15, 1998 Michael Eldred, 12:29:30 PM

324 White Papers and Publications Prepared by the MDO TC White Papers and Publications Prepared by the MDO TC A new White Paper on Industrial Experience with MDO consists of several invited papers and a summary report from the 1998 Symposium on Multidisciplinary Analysis and Optimization. Current State of the Art On Multidisciplinary Design Optimization (MDO), An AIAA White Paper, ISBN , September Multidisciplinary design optimization highlights article for annual "Year In Review" issue of Aerospace America (each December). Back to MDO TC Home Page Last Updated: June 1, 1999 Michael Eldred, mseldre@sandia.gov 12:29:31 PM

325 AIAA Technical Committee AIAA Technical Committee on Multidisciplinary Design Optimization (MDO) White Paper on Current State of the Art January 15, , American Institute of Aeronautics and Astronautics, Inc., posted on the Internet by permission PREAMBLE AIAA has established a Technical Committee for Multidisciplinary Design Optimization (TC-MDO) with the following charter: "To provide an AIAA Forum for those active in development, application, and teaching of a formal design methodology based on the integration of disciplinary analyses and sensitivity analyses, optimization, and artificial intelligence, applicable at all stages of the multidisciplinary design of aerospace systems". One of the functions the TC-MDO established for itself is to provide the aerospace community with a periodic assessment of the state-of-the-art in its field beginning with this White Paper. The task of developing this initial White Paper was led by Daniel Schrage assisted by Todd Beltracchi, Laszlo Berke, Alan Dodd, Larry Niedling, and Jaroslaw Sobieski. All members of the TC/MDO reviewed several drafts of the White Paper in its editorial process. A list of the TC-MDO members is included as Appendix II. FOREWORD This White Paper's purpose is threefold. First, it explores the need for bringing the diverse disciplinary design technologies involved in development of aerospace vehicles and expounded upon in the other chapters in this volume into a concerted action. This approach is necessary to create advanced aerospace vehicles that must be competitive not only in terms of performance, but also in terms of (1 of 41)12/29/ :29:35 PM

326 AIAA Technical Committee manufacturability, serviceability and overall life-cycle cost effectiveness. Second, it reviews some of the recently evolved means by which such concerted action may be implemented in a systematic and mathematically-based manner referred to as the Multidisciplinary Design Optimization (MDO) technology. Third, it points out major directions for research and development. The discourse is divided into six sections. The first section presents the need for the MDO technology in the historical context of progress in aerospace. In the second section, the emphasis is on the multidisciplinary nature of the aerospace design process. The human element in that process is discussed in the next section as the key component in any design-oriented technology. The fourth section is devoted to computing as the essential part of the design infrastructure. In the fifth section, the attention shifts to sensitivity analysis and optimization methods that form the core of the MDO technology. Finally, the concluding section identifies the development directions for realization of the MDO benefits. I Introduction and Background A. History of Aerospace Systems Design B. The Need for MDO II Multidisciplinary Aspects of Design A. Engineering Design Disciplines B. Concurrent Engineering Disciplines C. Supporting Disciplines III Human Interface Aspects of Design A. Design Decision Making B. Meta Design IV Computing Aspects of Design A. Information Architecture TABLE OF CONTENTS (2 of 41)12/29/ :29:35 PM

327 AIAA Technical Committee B. High Performance Computing V Optimization Aspects of Design A. System Level Optimization B. Decomposition and Sensitivity Analysis C. Concluding Remarks on Optimization VI Transitioning to the MDO Environment VII Conclusions VIII The Role of the AIAA MDO TC References Appendix I: Survey of the Industry MDO Practices Appendix II: AIAA TC MDO Membership Roster I. INTRODUCTION AND BACKGROUND A. History of Aerospace Systems Design During the pioneering years of aviation, the aircraft designer frequently was the central figure and the jack-of-all-trades -- designer as well as main resource person in aerodynamics, structures, materials, propulsion, and manufacturing, often also test pilot, entrepreneur and founder of great enterprises. The Wright Brothers, Glen L. Martin, Breguet, DeHavilland, Fokker, Heinkel and Sikorsky are just a few of the names which come readily to mind. Creative spirit, clear grasp of essentials, and confidenceinspiring, self-assured personality were their characteristic traits. The knowledge necessary to design an airplane was of a practical kind and for many years it was no more than could be stored in the mind of a capable individual. This first period came to an end in the early 1930s. Evaluation of wind tunnel tests in aerodynamics, thin shell analysis in structures, thermodynamic efficiencies in propulsion, processing and forming techniques in production - each of them developed into a field of specialization. The design engineer could not possibly keep abreast of all developments and had difficulty coordinating the different inputs coming from various specialists. Yet the solid engineering background and the long experience of the (3 of 41)12/29/ :29:35 PM

328 AIAA Technical Committee typical design engineer provided the know-how and the balanced judgment to translate new theoretical knowledge into flying hardware. Thus the senior design engineer had to evolve into what would today be called the systems engineer. This period lasted from the years of exciting technical progress in the 1930s, through the years of mass production during World War II, to the expansion of air transportation in the 1950s. A few prominent names during this period are Johnson, Northrop, McDonnell, Douglas, and Hughes. This period of time also produced rocket pioneers, such as Goddard, Oberth, Korolev and Von Braun. In the late 1950s a slow change in attitude occurred throughout aircraft design. Partly due to the impetus given by missiles, rockets, and spacecraft which are one of a kind single use systems that used a new set of design guidelines, and partly due to the demands of the military who were striving for maximum performance, the importance and prestige of analytical specialists soared. Specialists were needed to expand the limits of scientific knowledge and to reach for ever higher performance. The best minds were attracted by the challenges of research and development which usually meant estrangement from design. As a result, the design engineer's prestige declined. The analytical specialist was often the originator of novel ideas and the design engineer became the implementor as he translated these ideas into practice. Then, around 1970, began the big slump in the aircraft industry coupled with a decline in the civilian and military space programs which led to a reduction of the engineering force by about 25%. Simultaneously, two developments of great potential impact and far-reaching effect on aircraft design began to take place. First. computer-aided design came of age and has now relieved the design engineer of much of the earlier drudgery regarding the menial aspects of design. Second, the procurement policy of the military underwent a thorough change. The earlier drive of maximum performance had been superseded by a new quest for balance among performance, life-cycle cost, reliability, maintainability, vulnerability, and other "-ilities". This trend is reflected in the design requirements growth for advanced aeronautical vehicles in Figure 1. A major reason for this emphasis was the control of life cycle costs which are determined by the design concept and thus are very difficult to change significantly past this stage as illustrated in Figure 2. The experience of the 1960s had shown that for military aircraft the cost of the final increment of performance usually is excessive in terms of other characteristics and that the overall system must be optimized, not just performance. The same lesson had been learned earlier by the airlines when meticulous cost accounting had pointed toward possible savings due to improved reliability and maintainability [1]. Cost- effectiveness for an airliner is mostly economic. The aircraft must generate sufficient revenue in excess of operating costs that the purchase investment is more profitable than investing the same amount of money elsewhere. A similar shift of concern toward cost, supportability, launch availability, and reliability in orbit began to occur for similar reasons more than a decade earlier in the space launch vehicles and spacecraft. The 1980's brought about a number of thrusts both in government and industry to improve U.S. productivity and the quality of products. There has been an on-going quiet revolution in industry for the past ten years to make the necessary corporate, organizational and technical changes to compete successfully in an increasingly competitive global marketplace. These changes occurred first in the automotive and electronics industries, which were receiving intense competition for their products from (4 of 41)12/29/ :29:36 PM

329 AIAA Technical Committee Japan, but in the late 1980's had spread to the Aerospace industry. Many of the initiatives in government, particularly the Department of Defense (DoD), can be traced to recommendations from President Reagan's Blue Ribbon Commission on Defense Management (Packard Commission) for improving the weapon system acquisition process. Policy formulation from these recommendations has come in the form of general acquisition streamlining and the Total Quality Management (TQM) Program. Other initiatives can be traced to the DoD's desire to take advantage of emerging information and computing technologies and the environment they provide. The DoD - initiated Computer-Aided Acquisition and Logistics Support (CALS) Program is one example. As these initiatives have been implemented, there has been increased realization that in engineering, especially design, lies the greatest opportunity to improve product quality and provide concurrency of product and process phases to reduce development time. This realization has resulted in the recent emphasis on concurrent engineering (CE). CE has been defined as a systematic approach to the integrated, concurrent design of products and related processes, including manufacturing and supportability [2]. This definition is intended to emphasize from the outset consideration of all elements of the product life cycle from concept through disposal, including quality, cost, and schedule with traceability to user requirements. In most cases CE is envisioned as a modem application of systems engineering in an integrated computing environment. To date the CE emphasis has been on concurrent consideration of the life cycle phases, as illustrated in the top half of Figure 3, for the two-fold goal of improving quality by allowing the natural coupling among these phases influence the design decisions, and compressing the overall design process timetable. Close examination of the Design Phase of the CE process reveals potential benefits from rearranging the traditional disciplinary tasks from the conventional sequential order into concurrent activities shown in the bottom half of Figure 3. The designer can exploit the synergism of the interdisciplinary couplings provided that effective mathematical tools and methodologies are available. Thus, the Multidisciplinary Design Optimization (MDO) methodology that combines analyses and optimizations in the individual disciplines with those of the entire system is a technology that enables extension of the CE concept to the Design Phase. B. The Need for Multidisciplinary Design Optimization (MDO) Design consists of a hierarchical sequence of steps. It begins with ideas, missions and concepts, takes successively firmer shape until the configuration can be frozen, continues with the practical considerations about hardware, and leads to a set of manufacturing instructions and airworthiness documentation. This evolutionary process usually is depicted as phases from conceptual to preliminary to detail design and then manufacturing and production, as illustrated in Figure 4. As this process evolves design freedom decays rapidly while knowledge about the object of design is increasing as illustrated in Figure 5. As the design process goes forward designers gain knowledge but lose freedom to act on that knowledge. It was demonstrated mathematically in [4] that this natural evolution may lead to suboptimal designs. (5 of 41)12/29/ :29:36 PM

330 AIAA Technical Committee Traditionally, for aircraft and most other aerospace systems, design synthesis and optimization of the overall conceptual system has been based on achieving a fuel balance and a minimum weight configuration through parametric variation of a few critical design parameters i.e. wing loading, aspect ratio, etc. This aerospace approach to design synthesis is illustrated in Figure 6. Since aerodynamics and propulsion are the critical disciplines to achieving a fuel balance and vehicle performance, they are emphasized and the greatest level of effort is expended in these areas as illustrated in Figure 5. As the system design moves into the preliminary design phase and the initial configuration is frozen, hardware design considerations begin to dominate and the structures discipline begins to play a more dominant role. In the detailed design phase the controls discipline plays an increasing role as flight dynamics and handling quality improvements usually are necessary to achieve an acceptable flightworthy system. Also, the transition to production places a much bigger emphasis on manufacturing, cost, and to some extent supportability. The obvious problem with this traditional approach is the short conceptual design phase with an unequal distribution of disciplines which does not allow use of design freedom to improve quality and integrate disciplines for optimization. Also, the balanced design sought by the requirements growth in Figure 1 cannot be achieved. This was also a major conclusion from a recent industry survey conducted by the MDO technical committee. The results of this survey have been included as Appendix I. In recent years there has been an increased emphasis on integrating the structures and controls disciplines into the design at an earlier time. For the structures discipline the increased use of advanced materials with their flexibility and reliability based structural design philosophies has been one force for this emphasis. Another force is the use of composite materials for aeroelastic tailoring, as it couples a structural detail (using skin fiber orientation angle) with the flexible wing aerodynamics and, ultimately, the aircraft performance. The controls discipline has really become an upfront partner. Control configured vehicles offer significant opportunities for expanded flight envelopes and enhanced performance through relaxation of inherent stability margins. Flight control state of the art is perhaps best epitomized by the space shuttle digital fly-by-wire control system which provides control of the vehicle from on-orbit maneuvering, through atmospheric entry, from Mach 25 to a horizontal landing using blended reaction and aerodynamic controls. Full authority digital fly-by-wire flight control has been incorporated in operational military aircraft such as the F/A-18. Application to civil aircraft, prompted by potential performance advantages in aerodynamics, structures, and operations has been initiated. However, concerns over reliability, maintainability, cost, and integrity of such systems has delayed its application in the U.S. although the A-320 AirBus has a digital fly by wire system for use throughout normal flight. Control configured vehicles offer significant opportunities for expanded flight envelopes and enhanced performance though relation of inherent stability margins. In addition, ultralight-weight actively controlled space structures offer a weight reduction over conventional space structures. The ultimate goal of control integration is to maximize total aircraft performance. This goal can only be achieved by a balanced multidisciplinary design as portrayed in Figure 7 [5]. Aerospace vehicles are engineering systems whose performance depends on interaction of many disciplines and parts and whose behavior is governed by a very large set of coupled equations. In practice, engineers deal with these equations by partitioning them into subsets corresponding to the (6 of 41)12/29/ :29:36 PM

331 AIAA Technical Committee major disciplines, such as aerodynamics, structures, flight controls, etc. In this process of pragmatic partitioning, the couplings among the subsets tend to be reduced in number because it is burdensome to account strictly for them all. Couplings are retained or neglected judgmentally on the basis of what is known or assumed about their strength in a particular vehicle category. Generally speaking, the more advanced the vehicle, the more such couplings should be accounted for. Rotary wing aircraft or rotorcrafts are an excellent example of a highly coupled aerospace system. The multidisciplinary complexity of a rotorcraft, such as a helicopter is illustrated in Figure 8. Unsteady aerodynamics and vortex interaction cause excitation of complex structural dynamics to form a unique aeroelastic phenomenon which is further complicated by a direct coupling with the flight control system to trim the aircraft. The interaction that takes place among the disciplines of aerodynamics, aeroelasticity, structures and materials, and flight mechanics and controls in a typical flight condition is a series of feedback loops as illustrated schematically in Figure 9. The coupling of these disciplines is illustrated in matrix form in Figure 10 by referring back to the feedback loops of Figure 9. Principal and supporting disciplines are identified for each loop. If this off-diagonal coupling was not present, a linear superposition of research conducted by individual researchers at different locations could be combined. However, the coupling is strong, requires an interdisciplinary approach, and is one reason why progress in advancing rotary wing aircraft technology has been difficult. A similar coupling problem is evident on other advanced aerospace systems, although the interaction of disciplines would be different, such as the aerodynamics - propulsion - structures - controls coupling in hypersonic vehicles. The design synthesis flow chart using fuel balance for the Aerospace Plane is illustrated in Figure 11 [6]. While multidisciplinary integration can be associated with the traditional aerospace disciplines aerodynamics, propulsion, structures, and controls there are also the life cycle areas of manufacturability, supportability, and cost which require integration. After all, it is the balanced design with equal or weighted treatment of performance, cost, manufacturability and supportability which has to be the ultimate goal of multidisciplinary integration. Therefore, the multidisciplinary integration aspects of aerospace system design include the traditional disciplines of aerodynamics, propulsion, structures, and controls, as well as the life cycle disciplines of manufacturability, supportability and cost. The goal of this total multidisciplinary integration is illustrated in Figure 12. The changes in Figure 12 from Figure 5 are that the conceptual designer's time has been doubled to capture more knowledge and use more design freedom; the detail design time has been reduced by one third based on the use of more upfront design, and a more evenly distributed effort of disciplines is provided in the conceptual and preliminary design phase. The dashed line projection from the "Knowledge about Design" curve reflects the requirement that more knowledge will have to be brought forward to the conceptual and preliminary design phases. The dashed line projection from the "Design Freedom" curve reflects the need to retain more design freedom later into the process in order to act on the new knowledge gained by analysis, experimentation, and human reasoning. The change in the shapes of the two curves would alleviate the paradox that was discussed in conjunction with Figure 5. That change might be achieved through better integration of multi -and interdisciplinary design, analysis, and optimization. Obviously, another goal is to reduce the design time in order either to shorten the process duration or to develop a broader selection of optimized alternative designs in the constant elapsed time. (7 of 41)12/29/ :29:36 PM

332 AIAA Technical Committee A clearly defined objective and sufficient budget to accomplish it is also required for multidisciplinary integration to work. The space station is an example of a system where much upfront design has been performed, but no flight hardware has been built as the funding has been in a continuous state of flux leading to one costly redesign after another. Of course, an aerospace vehicle constitutes an integrated system by virtue of its physics, thus integration is a physical fact and hardly needs any advocacy for its existence. Therefore, when we postulate integration, we advocate research and development of means to help engineers master the interdisciplinary couplings and to enable them to exploit the associated synergism, toward improved efficiency and effectiveness of the design process and better quality of the final product. Consistent with the above, an integrated design process may be defined as one in which: (1) Any new information originated anywhere (in any discipline) in the design organization is communicated promptly to all recipients to whom it matters: (2) When a change of any design variable is proposed, the effects of that change on the system as a whole, on its parts, and on all the disciplines are evaluated expeditiously and used to guide the system synthesis. It is evident that (1) relies on the technologies for data management and graphic visualization, while (2) is based on synthesis, analysis and sensitivity analysis. Together, the above attributes form a capability for design optimization to be executed in a symbiosis of the human mind and the computer. Since the technologies of (1) are well cared for by other AIAA TC's and thrive on the marketplace, it is logical for AIAA TC-MDO to focus its efforts on the technologies underlying (2) which are much less known and, therefore, underutilized: design synthesis, sensitivity analysis, optimization methods, melding the human mind and computer capabilities, and effective organization of engineering to exploit these technologies. II. MULTIDISCIPLINARY ASPECTS OF DESIGN A. Engineering Design Disciplines The traditional engineering disciplines for aerospace vehicles include aerodynamics, propulsion, structures and controls. While these individual disciplines are considered fairly mature for many aircraft applications, there are advances in each discipline, due to theoretical, computational and methodology breakthroughs, that foster substantial payoffs and additional research. Emphasis in recent years, however, has been on the advances that can be achieved with research of the interaction between two or more of the disciplines. Also, new disciplines, such as electromagnetics, for low observability, without a statistical database need to be addressed. For advanced and particularly complex aerospace vehicles this (8 of 41)12/29/ :29:36 PM

333 AIAA Technical Committee interdisciplinary approach is often essential owing to the strong couplings among the disciplines and subsystems and, again, the lack of statistical data and human experience. B. Concurrent Engineering Disciplines While the engineering design disciplines, their interdisciplinary interaction, and optimization of the product are the primary focus for this technical committee it would be remiss if it didn't address their incorporation in the broader set of Concurrent Engineering (CE) disciplines. As depicted in Figure 5 the addition of manufacturing, supportability and cost to the traditional engineering disciplines constitute the set of CE disciplines, with quality being the CE objective function for optimization. The prerequisite task for that addition is development of realistic, reliable, and easy to use mathematical models for manufacturing, supportability, and cost. In contrast to the traditional engineering disciplines, such models are currently inadequate and this inhibits their incorporation in a formal MDO methodology. Obviously, for military systems cost and operational effectiveness and the tradeoff between them receives high priority [7]. C. Supporting Disciplines Multidisciplinary design optimization of aerospace vehicles cannot take place without substantial contributions from supporting disciplines. The identified supporting disciplines and methodologies are the Human Interface Aspects of Design, Intelligent and Knowledge-Based Systems, Computing Aspects of Design and Information Integration and Management. III. HUMAN INTERFACE ASPECTS OF DESIGN The engineering design process is recognized as a two-sided activity as illustrated in Figure 13. It has a qualitative side dominated by the human inventiveness, creativity, and intuition. The other side is quantitative, concerned with generating numerical answers to the questions that arise on the qualitative side. The process goes forward by a continual question-answer iteration between the two sides. The MDO methodology discards the "push button design" idea in favor of a realistic approach that recognizes the role of human mind as the leading force in the design process and the role of mathematics and computers as indispensable tools. It is clearly recognized that while conceiving different design concepts is a function of human mind, the evaluation and choice among competing, discretely different concepts, e.g., classical configuration vs. a forward swept wing and a canard configuration, requires that each concept be optimized to reveal its full potential. This approach is consistent with the creative characteristics of the human brain and the efficiency, discipline, and infallible memory of the computer. The middle ground between the two sides of design is occupied by the quasi-intelligent and knowledgebased systems. The area of intelligent and knowledge - based systems deals with a broad variety of ways in which the science and technology of Artificial Intelligence (AI) could contribute to the theory and practice of engineering design. The potential contributions cover much more than what are commonly (9 of 41)12/29/ :29:36 PM

334 AIAA Technical Committee inferred to as expert systems. Expert systems as generally implemented with current techniques. have very limited means of knowledge representation and deduction. The problems of design synthesis using multidisciplinary design optimization will usually require more powerful abstractions than provided by the current paradigm of expert systems [8]. A. Design Decision Making The engineering process can be viewed as a series of decisions which gradually define a new product in more and more detail. As the product evolves from conceptual to preliminary design, to detail design, and then production, the details of the decision making process change radically but its general nature remains the same. Therefore, it can be seen that decision making is at the heart of design. Many different types of decisions must be made in even the simplest case. One must decide where first to look for similar solved problems, how much time should be spent looking at modifications to past or current designs versus new development, which aspects of the design are most important, and how other disciplines are affected. A schematic of how decision makers, using human expertise and expert systems drive the design process is illustrated in Figure 14. These decisions are made in the design process in an environment of uncertainty and risk. Uncertainties come in various forms and the design team faces both upstream and downstream uncertainties. Upstream uncertainties include, for example: uncertainty in the specification of design requirements. This uncertainty relates to the possibility of modification of the original specification that is being designed to. Such changes occur frequently in weapon systems procurements and cause havoc in the design process in terms of schedule slippage and cost increase. Design of space launch vehicles is fraught with uncertainties as to the future mission parameters that may vary in a broad range or vehicle modifications that result in a stretched design. Oftentimes, downstream uncertainties may reflect a lack of knowledge as to the environment in which the product will be used or uncertainties in future availability of spare parts. Uncertainties in manufacturing processes, such as process variability, are also examples of downstream uncertainties from a design standpoint [9]. B. Meta Design Design viewed as decision-making implies the need to plan the decision-making process. Meta-Design "The design of the design process" addresses the planning activity. As illustrated in Figure 6the aerospace industry has developed a general synthesis and analysis which has proved successful for developing aerospace vehicles from helicopters to spacecraft. However, the existing design process has been geared principally to producing designs optimized for performance considerations without equal regard to cost, schedule, producibility, supportability or quality. As illustrated in Figure 12 design decisions and tradeoffs may have to be reordered among multidisciplines and different decisions may be required. A more flexible design process than illustrated in Figure 6 is required. Plans for integrating CAD/CAE/CAM tools, analysis tools, and design data bases should be directed toward executing a specific concurrent engineering design methodology. The type of design methodology used will depend on the type of design problem being addressed. Implementing a different computer integration scheme for each design methodology would pose a considerable burden in terms of software development. An (10 of 41)12/29/ :29:36 PM

335 AIAA Technical Committee alternative approach entails developing a flexible design system capable of supporting the activities of methodology development (meta-design) and methodology execution (design) for multiple design problems. Such a system would be compatible with the evolving idea of a flexible acquisition process and would be analogous to a flexible manufacturing system in that it could be rapidly reconfigured to support products of many different designs. An analytical approach to meta-design that involves providing a framework that allows the design methodologies to be developed and evaluated is addressed in [10]. IV. COMPUTING ASPECTS OF DESIGN Computer technologies have been changing the environment of engineering design. Therefore, these technologies are a major supporting discipline for MDO. Powerful analysis and simulation programs and CAD workstations are contributing to better solutions. These developments, in turn, are creating new difficulties. In an environment where most of the computer activities still involve stand-alone programs, design engineers often spend 50-80% of their time organizing data and moving it between applications. Integrated processing with database system support should eliminate many of these error-prone manual activities. Data must be shared between disciplines and within disciplines with all the applicable quality, consistency and integrity checks. It should be emphasized that the MDO methodology calls for extending the type of data available to the designer by the new category of the derivative, or trend data that directly answer the "What If?" questions about the entire vehicle system. Examples of such trend data are the derivative of the aircraft range with respect to the wing aspect ratio, incorporating the aerodynamics-structure interaction, or the derivative of the seat-mile operational cost with respect to the take-off gross weight, accounting for the coupling of the structures, aerodynamics, and propulsion. Since the continual concern about the "what if" questions is what a creative design is all about, having a capability to answer such questions expeditiously and comprehensively will constitute a quantum jump in the design process effectiveness and efficiency. A. Information Architecture Several parallel efforts have been and are being undertaken to identify an information framework for integrated design. As a result of a NSF workshop [11], a strong recommendation was made for the establishment of a national research program on engineering information management and suggested that the components include: Engineering Product and Process Description Engineering Information Dynamics and Data Models Very High Level Languages and User Interface Engineering (11 of 41)12/29/ :29:36 PM

336 AIAA Technical Committee Decision Support Systems Conclusions from this NSF workshop were that this research will require the concerned joint efforts of industry, government and academia and that it will require multidisciplinary teams from such areas as engineering, computer science, social science and mathematics. Another ongoing effort is the work by the Computer-Aided Acquisition and Logistics Support (CALS)/ Concurrent Engineering (CE) Mechanical Systems Framework Subtask Group. They have concluded that the information architecture must allow a large multi-disciplinary group to behave as a tightly knit inter disciplinary team, in a concurrent manner in creating product definition information. This architecture includes: concurrent product and process definition, product development team, product life cycle data, and knowledge of customer needs. The architecture may be seen as consisting of an Enterprise Integration framework and an Integrated Information Management System backbone. The Enterprise Integration includes: Product Definition, Process Definition, Configuration Management. Information Exchange, Team Organization, Validation, Metrics, and Enterprise Policy. These elements are peculiar to the enterprise itself. Yet there is an Information Management System that integrates the elements of the enterprise by means of a shared database environment. This includes: Information Modeling, Tool Integration, Information Integrity, Information View, Information Management, Communication, and Resource Definition. The Subtask Group has been assessing the existing environment for Concurrent Engineering from the above stated perspectives. Key topics include: 1) Information architecture, 2) Data exchange standards, such as the Product Data Exchange Specification (PDES), 3) Design - by - Feature, 4) Object - Oriented data management technologies, 5) Storage of (and access to) properties and constraints, material characteristics, and manufacturing methods; and the ability to create (user-specified) multiple views, intelligent libraries, and part, feature, and process information. A first draft of requirements for concurrent engineering information architecture has been completed by the CALS/CE Frameworks Subtask Group [l2]. B. High Performance Computing The term "supercomputer" is commonly used to denote computing power, but the definition of power in a computer is highly inexact and depends on many factors including processor speed, memory size, and so on. Secondly, there is not a clear lower boundary of supercomputer power. IBM 3090 computers come in a wide range of configurations, some of the largest of which are the basis of supercomputer centers at university, government and industry locations. Finally, technology is changing rapidly and (12 of 41)12/29/ :29:36 PM

337 AIAA Technical Committee with it our conceptions of power and capability of various types of machines. Therefore, the general term, "high performance computers (HPC)", is a term that includes a variety of architectures. One class of HPC consists of very large, powerful machines, principally designed for very large numerical applications, such as those encountered in science and engineering. Parallel processing assumes that a problem can be broken into large independent pieces that can be computed in separate processors. Currently, large mainframe HPC's such as those offered by Cray, IBM are only modestly parallel, having as few as two up to as many as eight processors. The trend is toward more parallel processors on these large systems. Some experts anticipate as many as 512 processor machines appearing in the near future. The key problem to date has been to understand how problems can be set up to take advantage of the potential speed advantage of larger scale parallel processing [l3]. A NASA Grand Challenge for high performance computing in aerosciences has been put forth as the integrated multidisciplinary design of aerospace vehicles and their numerical simulation throughout a mission profile [l4]. The goal is to demonstrate the utility of advanced parallel computer systems, including hardware, software and algorithms, capable of delivering teraflop performance for the design of a new generation of aerospace vehicles. Such a demonstration requires separate developments within a number of disciplines as well as the tight integration of those disciplines. Figure 15 and 16 provide some indication of the computational complexity and the present state of the art for two disciplines: aerodynamics and structural analysis. The underlying assumption is that a single simulation must be completed in 15 minutes. Figure 15 shows a range of configuration complexities from an airfoil through a wing to a full aircraft. Figure 16 also shows a range of computational requirements relative to past and present high performance computers. Again, the configuration complexity moves from a simple laminated material through a component to a full aircraft. The computational requirements implied by these figures are severe in their own right. When one thinks of coupling these and other disciplines that are equally computationally demanding through optimization formulation that requires repeated evaluation of these models the "challenge" is truly "grand" [l4]. To meet that challenge, the MDO technologist recognizes that the usable computing speed is a product of the hardware speed and the algorithm speed. In other words, one cannot get very far by using a multiprocessor computer for executing a method that originated [in a] serial computer environment. It follows that to extract full computational potential from a new type of a computer, one needs to invest a development effort in new solution algorithms comparable to the effort that went into the hardware development itself. V. OPTIMIZATION ASPECTS OF DESIGN Optimization methods have been combined with design synthesis and parametric analysis and used in the aerospace industry for the past forty years. The graphically displayed "carpet plot" is a characteristic of this legacy. In the first two decades the most commonly used techniques were graphical methods. Graphical methods were straight forward and easily understood, and had the obvious advantage of showing at a glance the entire interval of interest, calling attention to the function peaks, valleys, and (13 of 41)12/29/ :29:36 PM

338 AIAA Technical Committee other instructive features. The important limitation of these methods is that they can paint such a clear picture for only up to three or four variables in one figure, and require large computer resources for generating data points for constructing the plots. For greater number of variables, the combinatorial explosion sets in that would multiply the figures into volumes, and volumes into libraries with the attendant loss of the easy comprehension and interpretation. During the past two decades much progress has been made in numerical optimization that offers an alternative to the above. Any design can be defined by a vector in multidimensional space where each design variable represents a different dimension. Since we cannot see in more than three dimensions, the general case is beyond our power of visualization. Yet the principle is the same as when we assume only two variables in a base plane and plot above this plane a curved surface representing the objective function which depends on the two variables and which is to be optimized. The objective function may express cost, weight, range, aerodynamic or propulsive efficiency, return on investment, or any combination of parameters. It is subject to functional constraints in accordance with given relationships between variables and parameters and to upper or lower bounds of variables. The side constraints define the permissible part of the curved surface where the optimum value has to be found, e.g. limits due to minimum sheet thickness, maximum stress, stalling speed, etc. Thus, in a formal notation, the quantitative side of the design problem may be formulated as a problem of Nonlinear Mathematical Programming (NLP): (1). " find X such that f(x,p) is at minimum constrained by g(x,p)< 0 and h(x,p)= 0" where X is a vector of the design variables and X min and X max represent variable bounds, P is a vector of constant parameters, f is an objective function, g is a vector of inequality constraints, and h is a vector of equality constraints. Thus, in contrast to the graphical methods, the MDO technology mathematically traces a path in the design space from the initial toward improved designs (with respect to some figure of merit) and does it operating on a large number of variables and functions simultaneously - a feat beyond the power of human mind. However, the visibility of the reasons for the design decisions corresponding to the twists and turns of the search path remain obscured inside a "black box". Making these reasons visible to the designer and presenting graphically the salient features of the design space is a challenge that the MDO technology must recognize and meet, in order to inspire confidence in the optimization results. Post optimality and parameter sensitivity analysis can provide much information that can raise the confidence of the designer. The idea of formulating a design problem in rigorous, mathematical terms, introduced in [15], had spawned a vast body of literature, including comprehensive survey papers, e.g., [l6], [17], [18], and [38], and has become a key component in the MDO methodology. Consistent with its origin, the MDO methodology has thrived to the largest extent in design of light-weight, aerospace structures, but is spreading to other engineering disciplines and non-aerospace applications. The MDO-type methods were particularly successful in space flight for trajectory optimization. Optimization has been applied to trajectory design problems for the past 25 years. Analytic optimization has been applied to solving two (14 of 41)12/29/ :29:36 PM

339 AIAA Technical Committee and three burn orbit transfer problems for mission planning (estimating payload transfer capabilities). Boosters (Space Shuttle, Titan, Delta, Atlas) and upper stages (IUS, Centaur, PAM) use some form of trajectory optimization to design flight profiles to maximize payload (or reserve fuel) to some orbital conditions. Reentry problems have also been optimized to obtain maximum cross range or down range trajectories. Additionally the NASP trajectory will have to be optimized to obtain maximum payload to orbit i.e. improvements in the structure or engine efficiency will lead to new trajectories. These individual improvements must be weighed against total system performance to orbit (or some other objective, cost, reliability, or maintainability) to determine if the new system is worth the development cost. It should be noted that optimization does not remove the designer from the loop, but it helps conduct trade studies. The users should be [warned] not to accept solutions without careful examination, because if constraints are omitted from the problem they can often be violated by the optimization which can reduce safety factors and lead to system failure. Formulation of the design problem for a system life cycle or concurrent engineering concept can be accomplished as a multi-objective optimization problem [l9]: (2). " find X such that F(f i,(x,p)) is at minimum constrained by g(x,p) < 0 and h(x,p) = 0; where X min < X < X max ;" which differs from the single objective formulation in Equation 1 by recognizing a set of individual objective functions f i, i = 1--->NF, which often may be contradictory. The functional relation f( ) may be as general as admitting all f i 's on equal footing and rendering F a vector, or as specific as a weighted sum of the f i 's which reduces F to a scalar. By specifying f( ), the designer defines the desired balance of the various objectives f i. The multiobjective formulation represents a translation of the customer's ranked requirements and goals, via the engineering theories and models underlying the design concept, into a mathematical statement of the design problem [9], [l 8]. Numerical optimization capabilities lag in comparative fidelity as characterized by the number of variables describing a design for optimization and for analysis (simulation). Equations are solvable routinely in analysis for tens of thousand, cautiously for hundreds of thousands, and as tour de force for over a million variables. Optimization variables for Nonlinear Mathematical Programming algorithms can not go beyond a few hundred to describe a design, unless there is some special problem structure that can be exploited then the number can be extended to ten thousand. Optimality Criteria (OC) methods do not have any limitation on the number of variables and problems with a million variables have been demonstrated, but they apply only if certain conditions are satisfied, considerably limiting classes of problems for which OC methods may be used. For example they are not applicable in problems whose analysis combines governing equations of very different physical phenomena as is typical for multidisciplinary applications such as the aerodynamics-structures-vehicle performance problem. In contrast, in some applications involving a single physical phenomenon, the OC techniques may be very effective even though they yield only a close approximation to a constrained minimum. The classic example of this is the Fully Stressed Design (FSD) technique that works well for homogeneous material structures but becomes questionable for structures with material mixtures of varying strength to (15 of 41)12/29/ :29:36 PM

340 AIAA Technical Committee weight ratios. Post-optimization analysis of optimal design for sensitivity of the optimal solution to parameters P is often useful for quick assessment of the impact of changes to the original problem formulation [20], [21], [40]. For instance, if the P values needed to specify the F, g, and h functions in Equation 1 or Equation 2 may vary in an uncertainty range, it may be practical to optimize the design for the most probable P first. Subsequently, a range of new optimum designs may be approximated by extrapolation in the neighborhood of the nominal design using the derivatives of the optimal F and X. For example, consider a launch vehicle trajectory that has been designed to maximize reserve fuel a given mission. If the mission parameters (payload weight, target orbit, or launch vehicle specifications) change significantly then the trajectory for the vehicle must be reoptimized to find the trajectory that maximizes the reserve fuel for the new mission parameters. The optimum sensitivity analysis may also be very useful in multi objective optimization (Equation 2) for evaluation of the effect of the weighting factors subjectively introduced for converting a set f i 's to a scalar F. Parameter sensitivity analysis is influenced by numerical conditioning of the underlying problem and solution accuracy, therefore careful implementation is required to obtain good results [41]. A. System Level Optimization Why System-Level, Multidisciplinary Optimization? That question needs to be posed and answered first because a typical disciplinary specialist often tends to strive toward improvement of the objectives and satisfaction of constraints defined in terms of the variables of his discipline. In doing so he generates side effects that other disciplines have to absorb, usually to the detriment of the overall system performance. A classic example is aerodynamic design of a transport aircraft wing for a high lift-to-drag ratio by increasing the wing aspect ratio that may result in a structural weight penalty needed to alleviate flutter. That weight penalty subtracts from the performance benefit of the high lift-to-drag ratio and may actually result in a lower performance comparing to a reduced aspect ratio wing. To examine the issue in more detail, consider first an approach to airframe structural sizing that is often used for a long-range, subsonic transport aircraft. It may be summarized as follows: 1. Develop aerodynamic shape optimal for the cruise aerodynamic performance (basically, maximizing the L/D). 2. Minimize structural weight under the stress and aeroelastic constraints, including flutter, taking into account that the structural deflections affect the aerodynamic loads and vice versa. 3. From the cruise aerodynamic optimal shape subtract the structural deflections obtained for the optimized structure under that condition to establish a jig shape. This will assure that the ideal (16 of 41)12/29/ :29:36 PM

341 AIAA Technical Committee aerodynamic shape will be attained at least at one point during the cruise leg of the mission. Let us now see what would happen, if we used this approach to a supersonic transport (SST) flying a mission depicted in Figure 17 whose Mach number diagram may look as illustrated in Figure 18. It is a subsonic/supersonic mission and let us suppose that we used the supersonic stage in the above sizing approach. Since there is only one jig shape, if we use it up for the supersonic stage, we will end up having to accept whatever shape the airframe deforms to under the subsonic stage cruise condition. That shape may be aerodynamically suboptimal and cause a drag penalty of deltad1 relative to the shape aerodynamically optimal for that condition. If we refer to the subsonic stage in the sizing procedure, we just move the drag penalty to the supersonic stage but do not remove it. To remove or, at least, drastically reduce that drag penalty we have to recognize that there is a three-way mutual dependence of the aerodynamic loads-structural sizingdeflected shape that we, as structures engineers can manipulate to our advantage by changing the structural stiffness, its magnitude and distribution, over the airframe. Without invoking the notion of formal optimization as yet, suppose that by judgment we increase the wing stiffness in the outboard area to reduce the elastic wing twist that contributes to the drag penalty under the subsonic stage cruise condition (the optimal supersonic shape has remained optimal because we compensated by the jig shape). That may cost a structural weight penalty of deltawi which is, in general, bad for the performance. However, if drag is reduced from deltadi to deltad2 < deltad1, generally a good influence, the performance analysis can be referred to evaluate the deltawi against (deltadl<deltad2) as a trade-off. The trade-off may come out positive or negative depending on the objective and usually there is a wide choice. A few examples are: the minimum take-off gross weight (TOGW) for given range, payload, and mission profile; the maximum payload for a given range, TOGW, and mission profile. The above trade-off example is also only one of many. Suppose that the wing is strength-critical in 2.5g pull-up. Then, we may wish to allow the outboard wing more twist flexibility so that it can wash out thus alleviating the wing root bending moment and reducing the structural weight at the price of increased drag of the wing elastically deformed during the subsonic cruise. Many such trade-offs have to be considered simultaneously, and a complicating factor is that they have to be resolved not only to end up with a positive net impact on the performance objective(s) but they also have to be solved without violating the constraints imposed by each of the participating disciplines, e.g., flutter, allowable stress, vehicle stability, controllability, etc. It is clear that the human judgment needs help from the computer for resolution of such a multitude of trade-offs. Leaving the above example and returning to the generic discussion, it may be asserted that the user demand that drives the development of multidisciplinary analysis and optimization has been intensifying because: 1. major new aircraft design projects become fewer and farther apart in time, hence the past experience becomes less available as a guide in making the design decisions; (17 of 41)12/29/ :29:36 PM

342 AIAA Technical Committee 2. advanced aircraft tend to be an enormously complex system of interacting parts and disciplines and its ultimate performance hinges on the myriads of numerical interplay, some of them very subtly and beyond the power of human judgment to evaluate precisely. The ubiquitous challenge of design may be phrased as "How to decide what to change, and to what extent to change it, when everything influences everything else". The integrated design process that was defined at the end of Section IB is intended to meet the above challenge by creating an environment on the quantitative side of design (Figure 13) in which the designer's decision making will be supported with a comprehensive, and quickly generated, numerical information presented in an easy-to-interpret format. It is not the purpose of this paper to systematically survey the state-of-the-art in the methodology for creation of the above environment or to endorse a particular approach or technique. Rather, its purpose at this point is to illustrate emergence of a new methodology for multidisciplinary design optimization by a few examples of methods whose initial application experience has been encouraging. It is generally agreed that the challenge posed by the quantitative side of an advanced aircraft design as a complex system needs decomposition that breaks the large, intractable problem into smaller subproblems while maintaining the couplings among the subproblems. In the design office, this approach maps well onto the natural organization of engineers into groups by disciplinary and task specialization. It preserves and nurtures the advantages of the division of labor, including the concurrency of operations - the time-honored principle of industrial management first articulated by Adam Smith in the classic work "The Wealth of Nations" nearly 250 years ago [23]. B. Decomposition and Sensitivity Analysis The decomposition approach stems from the realization that the analysis and sensitivity analysis that generate data optimization algorithms need may easily account for more than 90% of the total computational optimization cost. Hence the recent emphasis on the efficient sensitivity analysis that exploits modularity in application to complex systems. Numerous decomposition schemes have been proposed in literature and, undoubtedly, more will be developed in the future. For the purposes of this discussion it will suffice to name as two basic examples the methods for a hierarchic decomposition and a non-hierarchic decomposition. Hierarchic decomposition. The concept of a hierarchic decomposition for engineering design was introduced in [24] using the algorithm from [25] as means for efficient calculation of the optimum sensitivity derivatives. Examples of this type of decomposition applied to structures may be found in [26], and a demonstration of its usefulness in multidisciplinary optimization to aircraft configuration was given in [27]. The hierarchic decomposition method exploits a special way in which the computational and decision making operations may be arranged in the design process of an engineering system. The arrangement is illustrated in Figure 19. Each box represents analysis and optimization of a subset of the entire system problem. The analysis information flow is topdown from the "Parent" black-box to the "Daughter" black-box. For example, a finite element analysis of the entire airframe may be a Parent that (18 of 41)12/29/ :29:36 PM

343 AIAA Technical Committee transmits the boundary forces to a Daughter wing substructure and the natural vibration frequencies and modes to another Daughter representing aeroelastic behavior. The topdown flow ends when it reaches the bottom level of the black-box pyramid. Then, each black box solution is available and the optimizations begin progressing from the bottom level up. Inputs received by a Daughter from a Parent are frozen as constant parameters for the duration of optimization performed inside of the Daughter black-box. Moving up to the Parent, one transmits the results of the Daughter optimization augmented with the derivatives of these results with respect to the parameters that the Parent has sent to the Daughter. These derivatives enable the Parent optimization to account by linear extrapolation on the effect of the Parent design variables on each Daughter constraints. The procedure continues to the top of the pyramid. The top Parent represents the system level objectives and constraints and is controlled by the system level design variables. The effects of these variables on all the black-boxes in the pyramid below are accounted for by the optimum sensitivity derivatives transmitted from below. Since the procedure is based on first derivatives, it takes a few iterations to converge. Each iteration consists of the analysis sweep top-down and the optimization sweep bottom-up. With careful implementation the optimization on successive iterations becomes more efficient if warm/ hot start capabilities are used. Since the Daughters do not communicate at the same level (no information transmission among sisters), the individual black box analyses and optimizations at each level may be performed in parallel. Non-hierarchic decomposition. The non-hierarchic decomposition method allows for information multidirectional transmission among the black-boxes forming a system as depicted in Figure 20 for an example of a flexible, actively controlled wing. A system like this cannot be arranged into a Parent- Daughter pyramid shown in Figure 19. Its optimization may be executed as a single operation for the entire system and is guided by the system sensitivity measured by the derivatives of the system behavior (response) variables with respect to the system design variables. The derivatives may be computed without finite differencing on the entire system analysis by a technique that: 1. solves the system at a baseline design point, 2. computes the partial sensitivity derivatives of the output from each black-box with respect to its input from other black-boxes and with respect to the design variables, 3. uses the above partial derivatives as coefficients to form a set of simultaneous, linear, algebraic equations whose solution yields the system sensitivity derivatives. A review of various types of decomposition, including the hierarchic and non-hierarchic approaches, was provided in [28]. The mathematical concept underlying the non-hierarchic approach was introduced in [29] and [30]. Its applications in aerospace design were compared to that of the hierarchic decomposition in [31], and an example of its industrial use was described in [32]. Common to (19 of 41)12/29/ :29:36 PM

344 AIAA Technical Committee optimization by both hierarchic and non-hierarchic decomposition is its reliance on the sensitivity analysis as a generic numerical method in engineering analysis [33] as well as a disciplinary method of the type described for structures in [34] and for aerodynamics in [35]. How to decompose a system. When the system at hand is new and there is no past experience in guiding its decomposition, one may benefit from the use of a formal technique that converts a set of randomly sequenced black-boxes into a set ordered into a hierarchic, nonhierarchic, or a mixed, hierarchic/nonhierarchic arrangement. The technique formalism requires that each black-box be defined as a source and a recipient of information. As a source, the blackbox sends information through its vertical sides, horizontally, to the left and to the right. This definition is illustrated in Figure 21. Initial random sequencing is presented by a diagonal chain of modules shown in Figure 22. The execution sequence is initially assumed to proceed from the upper left corner to the lower right corner and the modules are positioned randomly along the diagonal. Each off-diagonal dot marks a data interface indicating that the output moving along the horizontal line is directed along the intersecting vertical to the recipient module. The dots in the upper right triangle mean feeding the data forward (downstream), by the same token the lower triangle dots mean feedback (upstream). Each instance of a feedback calls for an iteration because module A upstream depends on the output from a successor module B downstream. By a systematic row and column permutation executed by a computer program, the random picture of Figure 22 may be transformed into an ordered sequencing shown in Figure 23. The transformation goal was to eliminate as many feedback instances as possible. It was not possible to eliminate them all in this particular case. However, their number was reduced and the remaining feedback instances have been clustered. That clustering suggests decomposition shown in Figure 24. It is a hybrid decomposition, hierarchic with respect to the clusters, each represented by a box in the pyramid, and non-hierarchic inside each cluster. Software tools became recently available for generating this type of decomposition from the initial, unorganized set of computational modules as described in [36]. C. Concluding Remarks on Optimization The above examples of methods now under development and testing should not be regarded as the last word but only the beginning in evolution of a new methodology for quantitative support of the design process. One common thread of the examples discussed in the foregoing is the concern about creating an environment in which the engineer's mind and computer interact drawing on the best resources of each. This concern is expected to alleviate misgiving some practicing engineers may have about the formal design methodology that was offered, on occasion in the past as an "automated design". That was a misrepresentation that might have been an underlying cause of the lag of applications behind the theoretical developments noted in the survey in [16]. The other common thread is the concern about modularity of implementation necessary to ensure flexibility, open-endedness, and ability to accommodate a variety of the information sources, including (20 of 41)12/29/ :29:36 PM

345 AIAA Technical Committee judgmental estimates, statistics, references, and experiments, in addition to computer programs. Modularity is also seen as a prerequisite for exploiting the computer technology progress in multiprocessor machines and distributed computing. Finally, there is a pervading concern for making the information exchanged among disciplinary specialists quantified and precise to provide a basis for the qualitative discourse these specialists are engaged in. With these concerns in mind, one may foresee further developments as encompassing new algorithms for decomposition, disciplinary and system sensitivity analysis, effective search and optimization of the design space, and AI-based tools making all this user-friendly. The central role of the disciplinary and system sensitivity analyses was apparent in the above method examples. Disciplinary sensitivity analysis by quasi-analytical approach is now routine only in structures and immediate emphasis is needed on developing a similar capability in CFD - the other major consumer of computer resources in aircraft design. The system optimization will become well-rounded when all contributing disciplines are liberated as much as possible and practical from the tedium of finite differencing by augmenting their analyses with sensitivity algorithms. Progress in the techniques for search and optimization in the design space is also important for the overall effectiveness and efficiency of the methodology as are procedures for tying together that search with analysis, sensitivity analysis, and approximate analysis, including the approach of statistically-fitted response surface methods. Improvements in the search techniques are needed for effective identification of multiple local minima - a vexing problem that thus far lacks a rigorous mathematical solution for cases with more than a few variables. One should also keep in the field of view the optimality criteria as an alternative to the search of the design space. Finally, the development should be kept open to accommodate innovations such as the self-learning neural nets, and genetic algorithms, to mention but a few examples of the cutting-edge approaches. As always in methodology development, the ultimate test of usefulness is in applications. Therefore, a systematic cooperation of the theoreticians, implementers, and users who apply the tools and influence the theory and implementation with their observations and wishes must be an intrinsic part of that development. The benefits from introduction of the new methodology will be amplified if that methodology is applied early in the design process where most of the leverage is available. VI. TRANSITIONING TO THE MDO ENVIRONMENT The previous sections of this white paper have reviewed different aspects of MDO. This section will provide some thoughts on how to evolve to a concurrent engineering (CE) environment and the role MDO for aerospace systems will play in this transition. The goal is to achieve the compression of the tasks in the Design Phase illustrated in Figure 3 and redistribution of the effort among the engineering disciplines as indicated by the horizontal bars in Figure 12. The expected end result is more design freedom retained longer into the design process and more information about the object of design gained earlier in the process as portrayed by the curves in Figure (21 of 41)12/29/ :29:36 PM

346 AIAA Technical Committee To accomplish the above one needs to develop an environment for the integrated design process as defined at the end of Section IB The following specific tasks should constitute that development: 1. Identify information exchange requirements - each discipline describes its input and output information. 2. Establish unified numerical modeling parameterized in terms of the design variables - a consistent vehicle geometry must be the basis for all mathematical models, and changes to the geometry must be centrally coordinated. 3. Establish a data management system for a quick and easy location and transfer of the information needed by the engineers and by the computational tasks, and for generation of good initialization data for the optimization tasks. 4. Develop mathematical models for manufacturing, reliability, supportability, and life cycle cost, to augment the classical discipline models for a complete implementation of the CE idea. 5. Assemble an efficient design-oriented analysis capability. A design-oriented analysis is tailored to support applications in design characterized by: repetitive use with only a subset of the input changed in each repetition, need for sensitivity data, use of the mathematical models of varied degree of refinement to trade accuracy for computational cost. 6. Efficiently generate discipline design sensitivities. 7. Assemble a system sensitivity analysis for vehicle optimization - system design variables will be identified and used to quantify the effects of design changes on the system behavior. 8. Improve optimization algorithms for effective handling of very large number of design variables, disjoint and nonconvex design spaces, multiple minima, and multiobjectives. 9. Improve post-optimum sensitivity analysis for greater computational efficiency, and for effectiveness in the extrapolations across the points where the set of active constraints changes its membership (see [20] for the description of a problem caused by changes in the active constraint set). 10. Develop a method for systematic developments and evaluation of design changes toward meeting the objectives and constraints in form of an iterative, multidisciplinary optimization process. The above development will result in a new, higher level of the state-of-the-art in engineering design. It is anticipated that industries, government laboratories, and universities will all contribute building blocks. There will be an accumulation of generic and proprietary, product-tailored tools, and of partial implementations of the entire process. Pilot projects will accumulate experience, demonstrate benefits, (22 of 41)12/29/ :29:36 PM

347 AIAA Technical Committee and build confidence. Gradually, a complete, new, integrated design process will evolve and be used for creating aerospace vehicles. That process will be a logical expansion to the Design Phase of the CE concept defined in [37]. The most important ten CE characteristics from the above reference (slightly rephrased for the context of this discussion) and their relationship to MDO are listed in Table 1 to emphasize once again the view of MDO as a key new component in CE. In that development, the AIAA TC-MDO has a role described in Section VIII. TABLE I TEN CHARACTERISTICS REQUIRED FOR THE CURRENT ENGINEERING PROCESS CHARACTERISTICS Compreh. Sys. Eng. Proc. Using Top-Down Design Approach Strong Interface with Customer Multi-Function Sys. Eng. and Design Teams 4 Continuity of the Teams 5 6 Practical Eng. Optim. of Product & Process Characts. Design Benchmarking Through Creation of a Dig. Prod. Model WHAT IS REQUIRED Authoritative, but Particip. Top Mgt ; System Eng. Mgt. Plan (SEMP) ; Automated Config. Mgt/Control Methods for Translation of Voice of Customer Into Prod/Process Characts. Management and Peer Acceptance; Equal or Near Equal Analysis - Cap. Training org. accept and Incentive Program Methods for Incorp. Qual. & Quant. Optim. Methods Design by Feature Methods Plus Data Exchange Stands MDO RELATIONSHIP Decomposition Optim. Methods Decomposition and Sensitivity Analysis Compat. of Num. Optim. Methods with Other Methods Sensitivity Analysis and Optim. Methods (23 of 41)12/29/ :29:36 PM

348 AIAA Technical Committee Simul. of Product Perf. and Manuf. Process Experiments to Confirm/Change High Risk Predictions Early Involvement of Subcontractors/Vendors Corporate Focus on Contin. Improve. & Lessons Learned Destrib. Simul. Cap. with Varying Levels of Fidelity Design of Experiments Methods for Variability Reduction of High Risk Characs. Accept. by Top Mgt. and Peers Plus Organ. Decomposition Design Tracking and Library Access through an Autom. Config. Mgt./ Control System Sensitivity Analysis and Optim. Methods Decomposition Decomposition, Sensitivity Analysis and Optim. Methods. VII. CONCLUSIONS Multidisciplinary Design Optimization (MDO) has been rapidly gaining recognition as a new, engineering discipline that assumes a key role in development of advanced aerospace vehicles whose common characteristic is that they are complex engineering systems. In its role of a catalyst and conciliator of the disciplinary requirements and interactions, MDO becomes as important for success of design as any traditional engineering disciplines. MDO has been reviewed in the historical context of the aerospace design process evolution and in the context of the present day and future challenges posed by advanced aircraft and spacecraft. If this White Paper were written a decade ago, in all likelihood it would have emphasized design optimization for improved performance. The recently evolved understanding that performance is only a subset of the overall product quality that must include the cost of development, manufacturing, and maintenance has replaced that emphasis in this paper with one that includes the entire life cycle of the aircraft or spacecraft, with the cost of that life cycle as one of the key objectives. This meshes very well with idea of Concurrent Engineering whose main goal is to move the manufacturing and supportability considerations upstream into the design process in order to compress the entire development and to assure that these considerations get in the design process an attention equal to that traditionally afforded the vehicle performance. This basic idea of Concurrent Engineering - the compression of the major life cycle phases of Design, Manufacturing, and Maintenance that were sequentially arrayed heretofore - applies also to the phase of design. That phase also may be "compressed" in the sense of staggering the conventional sequence of operations and decisions. MDO is seen as a means by which to achieve the above compression by bringing more information about the entire life cycle and the vehicle performance and cost aspects earlier into the design process. This will enable engineers to make design decisions on a rational basis that gives equal consideration to all the influences disciplines exert on the system, directly, or indirectly through their complex interactions. Doing this early in the process exploits the leverage of the uncommitted design variables. (24 of 41)12/29/ :29:36 PM

349 AIAA Technical Committee On the other hand, it is equally important to extend the MDO-based approach to the later phases of the design process in order to take advantage of the new information that becomes available during that process through creative thinking, analysis, experimentation, and exploration of alternatives. In order to do that, the design variables that in the conventional design process are decided and set early, need to be retained as free variables much longer into the process. Using the MDO technology one may achieve this because the overall methodology of system analysis, and optimization based on sensitivity data remains the same throughout the process. The variable element is analysis that deepens as the process moves on. The MDO methodology is well-suited to blend in the above analysis the traditional, performanceoriented design considerations with those posed by the remainder of the life cycle because it is generic and capable of including anything represented by a mathematical model, whether that model is derived rationally or established heuristically. However, it is necessary to develop such models first and this is one of the several specific developments identified in the White Paper. Another development direction of a high pay-off potential pointed out is toward the probabilistic methods, multiobjective capability, and facilities to accommodate the "soft" (negotiable) constraints as distinct from the hard constraints in optimization - as required by the applications of MDO extended to manufacturing, maintenance, and economics. The key premise expounded for the MDO approach in the White Paper is that it is not a "push button" design. Instead, MDO is an environment in which the human ingenuity combines with the power of mathematics and computers in making design decisions. The boundary between the formal mathematical methods and the human judgment is, of course, fluid. Nothing should prevent an engineer either from delegating a repetitive tedious routine to a formal method or from substituting judgment for a formal method or from overriding the method results. Based on that premise, the MDO-enhanced design process has the clear potential for radically improved product quality achieved by systematic exploration of the alternatives created by human ingenuity and bringing each of these alternatives to the optimal state among which a fair choice can be made by engineer's judgment. VIII. THE ROLE OF THE AIAA MDO TC The TC-MDO should be a focus for MDO activity, providing a forum through which the efforts of researchers can be disseminated to users and potential users in industry and government establishments. At the same time, feedback from users will establish future requirements and goals. In order to maintain such a forum, the TC should seek membership among all engineers and computer specialists, involved in design, and design support, of aerospace vehicles of all major categories such as aircraft, launch vehicles, spacecraft, missiles, transatmospheric vehicles, etc. To achieve the goals called for by its charter, the TC should undertake the following tasks: (25 of 41)12/29/ :29:36 PM

350 AIAA Technical Committee (1) DEFINE the technological sphere of interest in multidisciplinary design optimization regarded as a new engineering discipline and one of the key elements in concurrent engineering and total quality management. (2) GATHER information on MDO - university research - industry practices and applications - government research and requirements (3) EDUCATE - upper and middle management in industry and government - R&D engineers in industry and government - university graduate and post graduate students (4) GUIDE research efforts by suggesting areas for study, and future goals. To accomplish these tasks the following TC-MDO subcommittees have been formed: (1) White Paper - Act as a focal point for a periodic generation of a white paper expressing the collected views of the TC and describing state-of-the-art in integrated MDO. (2) Computer Technology and Optimization - Act as a focal point for information concerning optimization algorithms and their application and advances in computer technology. (3) Education - Act as a focal point on all issues relating to education in MDO. (4) Liaison - Act as a focal point to coordinate activities and provide a channel of communication with other active AIAA TC's. (5) Conference Support - Act as a control focus of activity and resources of the TC-MDO in support of AIAA sponsored and co-sponsored conferences, symposiums, and shows. (6) Publications - Act as a focal point for generation and distribution of all publications of the TC- MDO. (26 of 41)12/29/ :29:36 PM

351 AIAA Technical Committee (7) Benchmark - Act as a focal point for devising effective and practical test cases for MDO methods. (8) Emerging Methods - Act as a focal point for identifying emerging methods applicable to MDO. (9) Material Optimization - Act as a focal point for coordinating research efforts in the area of optimum design of materials, and their inclusion into the design of complex systems together with the other relevant disciplines. (10) Awards - Act as a focal point for identifying and recognizing significant contributors to MDO. REFERENCES 1. U. Haupt, "Decision-Making and Optimization," NPS-67 Hp 77021A, February R. I. Winner, et al., "The Role of Concurrent Engineering in Weapons System Acquisition," Report R- 338, IDA, Washington, DC, December D. P. Schrage, "The Impact of TQM and Concurrent Engineering on the Aircraft Design Process," Keynote Address Vertical Lift Aircraft Design Conference, San Francisco, CA, Jan 17, Sobieszczanski-Sobieski, J.; Barthelemy, J.-F. M.; and Giles, G. L.: "Aerospace Engineering Design by Systematic Decomposition and Multilevel Optimization," 14-th Congress of the International Council of the Aeronautical Sciences (ICAS), Proceedings of; Toulouse, France, Sept. 1984; also published as NASA TM NASA; Langley Research Center, Hampton, VA, June "Aeronautics Technology, Possibilities for 2000: Report of a Workshop," National Academy Press. Washington, D.C J. L. Hunt and J. G. Martin, "Hypersonic Airbreathing Vehicle Conceptual Design (Focus on Aero- Space Plane)," Recent Experiences in Multidiscipiinary Analysis and Optimization, Hampton, VA, September 28-30, "The Future of Military R&D: Towards a Flexible Acquisition Strategy," Institute for Defense Analysis (IDA), July "Goals and Priorities For Research In Engineering Design: A Report to the Design Research Community," The American Society of Mechanical Engineers (ASME), New York, NY, July E. Tse and W.E. Cralley, "Management of Risk and Uncertainty in Product Development Processes," IDA Paper P-2153, June (27 of 41)12/29/ :29:36 PM

352 AIAA Technical Committee 10. J. E. Rogan and W. E. Cralley, "Meta Design," IDA, Paper P-2152, Jan R. E. Fulton and J. I. Craig, "Information Framework Technology For Integrated Design/ Engineering Systems," Results of NSF and Georgia Lnstitute of Technology Workshop, Callaway Gardens, GA, March 13-15, First Draft, "Requirements For Concurrent Engineering Infonnation Architecture," CALS/ISG/CE Framework Subtask Group, June 11, "High Performance Computing Networking For Science - Background Paper," Congress of the United States, Office of Technology Assessment, September R. G. Voigt: "Requirements For Multidisciplinary Design of Aerospace Vehicles on High Performance Computers," NASA Contractor Report , September Schmit, L. A.: "Structural design by Systematic Synthesis," Proc. of the Second National Congress on Electronic Computation, Structures Division ASCE, Pittsburgh. PA, Sept pp Ashley, H.: "On Making Things the Best - Aeronautical Uses of Optimization," AIAA J. of Aircraft, Vol 19, No 1. Jan. 1982, pp Siddall, J. N.: "Frontiers of Optimal Design," ASME J. of Mechanical Design, Oct Betts, J. T.: "Frontiers in Engineering Optimization," ASME J. of Mechanisms, Transmissions. and Automation in Design; June Eschenauer, H., Koski, J.. and Osyczka, A. (Editors): "Multicriteria Design Optimization," Springer Verlag, Sobieszczanski-Sobieski, J.; Barthelemy, J.-F. M.; and Riley, K. M.: "Sensitivity of Optimum Solutions to Problem Parameters," AIAA Paper R, and AIAA J, Vol 20, No 9, September 1982, pp Barthelemy, J.-F. M.: Sobieszczanski-Sobieski, J.: "Extrapolations of Optimum Designs Based on Sensitivity Derivatives," AIAA J., Vol 21, No 5, May 1983, pp Aviation Week and Space Technology, June 18, 1990, pp Adam Smith: "The Wealth of Nations," Sobiesznanski-Sobieski, J.: "A Linear Decomposition Method for Large Optimization Problems - (28 of 41)12/29/ :29:36 PM

353 AIAA Technical Committee Blueprint for Development," NASA TM 83248, February Barthelemy, J. F.; and Sobieszczanski-Sobieski. J.: "Optimum Sensitivity Derivatives of Objective Functions in Nonlinear Programing," AIAA J, Vol 22, No 6, June 1983, pp Sobieszczanski-Sobieski. J.; James, B. B.; and Dovi, A. R.: "Structural Optimization by Multilevel Decomposition," AIAA J., Vol 23, No 11, November 1985, pp Wrenn, G. A.; and Dovi. A. R.: "Multilevel Decomposition Approach to the Preliminary Sizing of a Transport Aircraft Wing," AIAA Journal of Aircraft, Vol 25, No 7, July 1988, pp Barthelemy, J. F.: "Engineering Design Applications of Heuristic Multilevel Optimization Methods," Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization; Hampton, VA, September 28-30, 1988, Proceedings to be published as NASA CP - No Sobieszczanski-Sobieski, J.: "On the Sensitivity of Complex, Internally Coupled Systems," AIAA/ ASME/ASCE/AHS 29th Structures, Structural Dynamics and Materials Conference, Williamsburg, VA., April 1988; AIAA Paper No CP and AIAA J.. Vol 28, No 1, Jan. 1990, also published as NASA TM , January Sobieszczanski-Sobieski, J.: "Sensitivity Analysis of Complex Coupled Systems Extended to Second and Higher-Order Derivatives," AIAA J.. Vol 28, No 4, Apr. 1990, also published as NASA TM , April Sobieszczanski-Sobieski, J.: "Sensitivity Analysis and Multidisciplinary Optimization for Aircraft Design: Recent Advances and Results," Int'l Council for Aeronautical Sc., Proceedings of 16th Congress, Jerusalem. Aug.- Sept. 1988; Vol 2, pp Abi, F.F.; Ide. H.; Shankar, V. J.; and Sobieszczanski-Sobieski, J.: "Optimization for Nonlinear Aeroelastic Tailoring Criteria," Int'l Council for Aeronautical Sc., Proceedings of 16th Congress. Jerusalem, Aug.-Sept ; Vol 2. pp Proceedings of the Symposium on Sensitivity Analysis in Engineering, NASA Langley Research Center, Hampton, VA, Sept. 1986; Adelman, H. M.; and Haftka, R.T. - editors. NASA CP-2457, Adelman. H. A; and Haftka, R. T.: "Sensitivity Analysis of Discrete Structural Systems," AIAA J., Vol 24, No 5, May 1986, pp Yates, E. C.: "Aerodynamic Sensitivities from Subsonic, Sonic, and Supersonic Unsteady, Nonplanar Lifting-Surface Theory," NASA TM , September (29 of 41)12/29/ :29:36 PM

354 AIAA Technical Committee 36. Rogers, J. L.: "A Knowledge-Based Tool for Multilevel Decomposition of a Complex Design Problem," NASA TP 2903, CALS Technical Rep 002: "Application of Concurrent Engineering to Mechanical Systems Design," Final Report of RM Mechanical Design Study, June 16, Schmit, L. A.: "Structural Synthesis - Its Genesis and Development," AIAA J., Vol. 19, No 10, 1981, pp Betts, J. T.; and Huffman, W. P.: "The Application of Sparse Nonlinear Programming to Trajectory Optimization," AIAA Paper , Aug. 1990, Proceedings AIAA Guidance Navigation and Control Conference. 40. Fiacco, A.: "An Introduction to Sensitivity and Stability Analysis in Nonlinear Programming," 1983, Academic Press. 41. Hallman, W. P.: "Sensitivity Analysis for Trajectory Optimization Problems," AIAA Paper , Jan APPENDIX I SURVEY OF THE INDUSTRY MDO PRACTICES In the summer of 1990, the AIAA Technical Committee for Multidisciplinary Design Optimization conducted an industry survey on the use of the MDO technology. The survey was taken to their companies in the U.S.A. and in Europe by the TC members who used their company contacts to answer the survey questions. Thus the answers received were representative of the company rather than individual opinions. The first part of this appendix defines the survey purpose and background. A Summary of the results is given in the second part. Survey Definition Purpose The survey purpose is to determine the ways and means the aerospace industry uses to resolve trade-offs that arise in design process of aerospace vehicles, with emphasis on the trade-offs that involve two or more engineering disciplines. Background The following examples illustrate the notion of a trade-off. By increasing the aspect ratio of a transport wing, the drag-due-to-lift is reduced thus improving range for a given payload. However, a higher aspect ratio wing, in general, will weight more tending to decrease range. The net effect of (30 of 41)12/29/ :29:36 PM

355 AIAA Technical Committee change in aspect ratio on range may then be positive or negative, depending on the strength of the drag and weight influences. The kill probability of an air-to-air missile may be increased by making the missile more agile, or making the fighter that launches the missile more agile, or both. There is a cost associated with adding agility to the missile and another cost of adding agility to the fighter. In what proportions should one allocate a fixed total budget to the missile development and to the fighter development to get a missile/ fighter system of the maximal kill probability? The pointing accuracy of a large antenna dish attached to a spacecraft constructed as a large, activelycontrolled structure, may be improved by making the structure more rigid, or by adding more capability to the control system. There are weight penalties, and cost penalties for both alternatives. What is the "best" mix of added structural rigidity and added capability of active-control system to achieve the required pointing accuracy? As the examples illustrate, the trade-off arise at high-level (system level) as well as more detailed level, in all classes of vehicles. For proper resolution they involve numerical information and judgment. Regarding numerical information, there is a body of mathematical methods such as: disciplinary and system analyses, sensitivity analysis (to compute derivatives of the dependent variables with respect to independent variables by analytical, quasi-analytical, or finite difference techniques), parametric studies, and formal optimization. On the judgment side, the approaches range from unstructured decision making to highly organized and disciplined procedures for generation, evaluation, and recording of the judgmental decisions. It is not clear, however, where the center of gravity lies between the extremes of the all mathematical and all judgmental ways of resolving the trade-offs, and what are the most often used techniques in both categories. It is also not clear whether things are as they should be with regard to the above, or whether they should be changed. It is important to know the industry opinion on this issue for effective planning and development of the pertinent methodology and engineering education. This survey should shed some light on the issue. Format The survey subject is really too complex to boil down to a simple, check-a-box, questionnaire. Therefore, a free format essay is preferred (please, include identification of your company, your position, and give an example of a product to which the issues raised in this survey would, typically, apply). The minimum length for a meaningful answer is probably less than one single-spaced page. To facilitate the evaluation, the maximum length should not exceed 3 pages. However, a questionnaire format is also available, if time for a free-format answer cannot be found. Summary of the Survey Results: Questions and Answers. Most of the survey returns came in the Questionnaire Format but several were in an all free-format (31 of 41)12/29/ :29:36 PM

356 AIAA Technical Committee narrative. The survey Questionnaire Format questions are reproduced in full. Most questions called for a numerical answer. The numerals following each question represent averages of the survey return. The answers were also illustrated by placing the averages on the numerical axis. Since there is no uniform definition of design stages, the answers were classified as pertaining to early and late phases of design and marked by E and L, respectively. The averages include also the information extracted judgmentally from the free narrative results. Questions 4 and 6 in the Questionnaire called for free-format answers and are followed by paraphrased extracts from these answers and from those returns that came in an all-freeformat narrative. 1. Assuming a scale from -5 (all mathematical) to +5 (all judgmental), place on the scale the center of gravity of the ways by which the design trade-offs are being resolved, for each design stage. Notes: 1) results are reported for early/late design stages, 2) "system" means a complete vehicle. -1.1/ -2.2 (early/late) Mathematical......Judgmental L...E In the judgmental decision making, where is the center of gravity between the extremes of very formal organizational procedures (-5) and unstructured process (+5). Use a format as in answer / -2.2 Mathematical......Judgmental L...E For the numerically generated information, please, evaluate how much does your organization rely on the following mathematical tools, using a scale from 0 (not used) to +5 (used very often, regarded as essential). Analysis Disciplinary analysis 4.2/ (32 of 41)12/29/ :29:36 PM

357 AIAA Technical Committee...EL System sensitivity by parametric study: 3.0/ E..L... System sensitivity by finite differences: 2.8/ L...E... System sensitivity by analytical/semi-analytical method: 3.0/ L...E... Optimization Parametric study/disciplines: 4.0/ L.E... Parametric study/system: 4.2/ L/E... Formal numerical optimization/disciplines: 3.0/ LE... (33 of 41)12/29/ :29:36 PM

358 AIAA Technical Committee Formal numerical optimization/system: 3.0/ L...E If formal, numerical optimization is used, name a few techniques, e.g., nonlinear programming (NLP), linear programming (LP), optimality criteria, and names of a few optimization programs (Early/H for inhouse developed, A for acquired from outside). NLP, LP, Fully Stressed Design, Optimality Criteria (FASTOP), Design of experiments (DOE), Mix of in-house and acquired, Most of NLP at early stages, little in Aerodynamics, OC and FSD at later states in Structures. Formal optimization of the configuration in early stages, after that structural optimization with the configuration frozen. 5. For each design stage indicate whether the present system adequately identifies the best design options and configurations, accounting for complex interactions among the system parts and governing disciplines. Use scale from 0 (very inadequate) +5 (completely adequate). 2.9/ E.L Finally, indicate whether you are satisfied with status quo or would like to see a change. Formal optimization applied to configuration (system) very early, then configuration frozen, optimization limited to structures and control. The above confirms the paradox: In the design process, "the knowledge increases with time, the freedom to act on that knowledge decreases with time". Present ways adequate to design good vehicles, not adequate "to prevent problems from occurring late in the design cycle which require costly and sometimes futile efforts to correct". After the configuration is frozen, problems arising in a particular discipline are expected to be solved by a fix limited to that discipline (e.g., flutter fixed by stiffening of the wing structure or by balance masses). Organizational structure and culture must change to bring about an effective MDO into the design process. (34 of 41)12/29/ :29:36 PM

359 AIAA Technical Committee The best place for MDO is in the middle of the design process when enough hard information is available but before too many variables get frozen and before the problem size mushrooms. Better infrastructure is essential: faster, bigger computers, visualization, data bases. Lack of the system sensitivity information hampers the design process. "Higher order" disciplines (e.g., aeroelasticity) are particularly limited by the above. High priority should go to a complete automation of the routine engineering tasks, including AI methods. MDO should be used at ALL stages of design Mathematical models of different degree of refinement should be used in a coordinated manner throughout the design process. Doing work faster = the MDO advantage. Need a better handle on the multiple minima problems and more visibility into the optimization process to gain confidence in the results. MDO has a potential as a crucial component in the Concurrent Engineering. The best way to introduce MDO is by incremental changes. Trajectory optimization is a good example of an application where optimization is used because no other means would do. APPENDIX II AIAA Technical Committee Multidisciplinary Design Optimization (MDO) Membership Roster NAME ORGANIZATION (35 of 41)12/29/ :29:36 PM

360 AIAA Technical Committee Dr. Jaroslaw Sobieski, Chairman NASA Langley Research Center, MS 246 Hampton, VA Engineering Computing Systems Technology MD Mr. Jan Aase General Electric 1000 Western Ave. Lynn, MA Rockwell International Dr. Frank Abdi P.O. Box N. Douglas St. #GB15 El Segundo, CA McDonnell Douglas Research Laboratories Dr. Ramesh K. Agarwal Dept. 222/B.110 P.O. Box 516; MC St. Louis, MO The Aerospace Corporation Dr. Todd J. Beltracchi P.O. Box Los Angeles, CA NASA Lewis Research Center Dr. Laszlo Berke Brookpark Rd. Cleveland, OH (36 of 41)12/29/ :29:36 PM

361 AIAA Technical Committee Mr. Christopher Borland Boeing Commercial Airplane Group P.O. Box 3707; MS 7H-94 Seattle, WA College of Engineering Dr. Kyung K. Choi The University of Iowa Iowa City, IA General Dynamics Fort Worth Div. Mr. Robert D. Consoli Dept P.O. Box 748 MZ 2872 Ft. Worth, TX Boeing Comp. Services Dr. Evin Cramer P.O. Box 24346, M/S 7L-21 Seattle, WA Douglas Aircraft Co. Mr. Alan J. Dodd McDonnell Douglas Co Lakewood B., M/S Long Beach, CA Aerospace Engineering Dept. Prof. George S. Dulikravich 233 Hammond Bldg. The Pennsylvania State University University Park, PA (37 of 41)12/29/ :29:36 PM

362 AIAA Technical Committee Mr. George C. Greene Fluid Mechanics Div., MS 163 NASA Langley Research Center Hampton, VA Engineering Sc. and Mechanics Dept. Dr. Zafer Gurdal Virginia Polytechnic Institute Blacksburg, VA Dept. of Mechanical Engineering Aeronautical Eng. and Mechanics Dr. Prabhat Hajela 5020 Jonsson Eng. Ctr. Rensselaer Polytechnic Institute Troy, NY The Aerospace Corporation Dr. Wayne Hallman P.O. Box Los Angeles, CA Boeing Aerospace Dr. K. Scott Hunziker P. O. Box 3999, M/S Seattle, WA MacNeal Schwendler Co. Dr. Erwin H. Johnson 815 Colorado Blvd. Los Angeles, CA (38 of 41)12/29/ :29:36 PM

363 AIAA Technical Committee Dr. Ilan Kroo Dept. of Aeronautics and Astronautics Stanford University Stanford, CA General Dynamics Fort Worth Div. Mr. Michael Love P. O. Box 748, MZ 2824 Ft. Worth, TX NASA Lewis Research Center, MS AAC-1 Dr. John K. Lytle Brookpark Rd. Cleveland, OH Grumman Aircraft Systems Div. Mr. Philip Mason MS B43/35 Bethpage, NY System Analysis Br. Dr. Hirokazu Miura NASA Ames Research Center, MS Moffett Field, CA Northrop Aircraft Div. Mr. Douglas Neill Dept. 3854/82, 1 Northrop Ave. Hawthorne, CA McDonnell Aircraft Co. Mr. Larry G. Niedling P. O. Box 516, M/C St. Louis, MO (39 of 41)12/29/ :29:36 PM

364 AIAA Technical Committee Ms. Beth Paul General Dynamics Ft. Worth Div. P. O. Box 748, MZ 2208 Ft. Worth, TX Lockheed Aeronautical Systems Co. Dr. Nick Radovcich Dept , Bldg. 63GE, Plant A-1 P. O. Box 551 Burbank, CA Douglas Aircraft Co. Mr. Bruce A. Rommel McDonnell-Douglas Corp. M/S Long Beach, CA Rockwell Int'l. Science Center\ Dr. Vijaya Shankar P. O. Box 1085 Camino del Rios Thousand Oaks, CA School of Aerospace Engineering Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, TA MBB Ottobrunn Mr. Otto Sensburg P. O. Box Munich 80 Germany (40 of 41)12/29/ :29:36 PM

365 AIAA Technical Committee Rockwell International Corp. North American Aerospace Oper. 011 GC02 Mr. J. Tulinius P. O. Bhox N. Douglas St. El Segundo, CA VMA Engineering Dr. Gary Vanderplaats 5960 Mandarin Ave., Suite F Goleta, CA Air Force Wright Research & Dev. Center Dr. Vipperla Venkayya FIBR Wright-Patterson AFB, OH University of Texas at Arlington Dr. B. P. Wang P. O. Box Arlington, TX McDonnell-Douglas Missile Co. Mr. John W. Hayn P. O. Box 516, M/C St. Louis, MO (41 of 41)12/29/ :29:36 PM

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388 What is MDO? What is MDO? Some popular definitions for Multidisciplinary Design Optimization (MDO): A methodology for the design of complex engineering systems and subsystems that coherently exploits the synergism of mutually interacting phenomena. Optimal design of complex engineering systems which requires analysis that accounts for interactions amongst the disciplines (or parts of the system) and which seeks to synergistically exploit these interactions. "How to decide what to change, and to what extent to change it, when everything influences everything else." For a more detailed description, refer to the Current State of the Art On Multidisciplinary Design Optimization (MDO) white paper. Back to MDO TC Home Page Last Updated: March 12, 2001 Anthony A. Giunta, aagiunt@sandia.gov 12:29:56 PM

389 Functions performed by the MDO TC What functions are performed by the MDO TC? The AIAA MDO TC sponsors a variety of activities to further the development, application, and teaching of MDO technology: Service Conferences supported by the MDO TC Short Courses supported by the MDO TC White Papers and Publications prepared by the MDO TC Awards to recognize outstanding contributions in the field of MDO. Assessment and recommendation of improvements in the teaching of MDO technology. Technical Provision of a MDO test problem suite for the benchmarking of optimization methods in the aerospace community. Exchange and dissemination of MDO application information within the aerospace community. For more information, see the MDO TC Operations Manual and AIAA Technical Activities. Back to MDO TC Home Page Last Updated: March 12, 2001 Anthony A. Giunta, aagiunt@sandia.gov 12:29:56 PM

390 1.0 INTRODUCTION AIAA MULTIDISCIPLINARY DESIGN OPTIMIZATION TECHNICAL COMMITTEE OPERATING PLAN June 1998 TABLE OF CONTENTS 1. INTRODUCTION 2. PURPOSE AND ORGANIZATION 3. SUBCOMMITTEE FUNCTIONS 3.1 Communications Subcommittees Education Internet Liaison Publications White Paper 3.2 Technical Subcommittees Applications Benchmarking Conference support MA&O Symposium Support 3.3 Planning Awards Charter Membership 4. ACTIVITIES AND SCHEDULES 4.1 Committee operation and membership 4.2 TC Chair Selection Process 4.3 Officer Responsibilities 4.4 Subcommittee activities and schedules Education Internet Liaison (1 of 18)12/29/ :29:58 PM

391 1.0 INTRODUCTION Publications White Paper Applications Benchmarking Conference support MA&O Symposium Support Awards Charter Membership 5. APPENDICES 5.1 Latest 3 year plan 5.2 Sample Liason Report 5.3 AIAA Short Course Review Procedure 5.4 TC Operations/Calander Even Years 5.5 TC Operations/Calander Odd Years 5.6 Plan for Electing New General Chair for Multidisciplinary Analysis and Optimization Symposium 1.0 INTRODUCTION This manual describes the activities of the AIAA Multidisciplinary Design Optimization Technical Committee in support of the broad AIAA objective of advancing the state of technology for a wide range of aerospace systems. The purpose of this manual is to describe the overall schedule and activities of the committee in order to maintain continuity of committee functions as members change from year to year. This is therefore a working document which should be reviewed yearly and updated as required to accurately reflect committee activities. 2.0 PURPOSE AND ORGANIZATION CHARTER: "To provide an AIAA forum for those active in development, application, and teaching of a formal design methodology based on the integration of disciplinary analyses and sensitivity analyses, optimization, and artificial intelligence, applicable at all stages of the multidisciplinary design of aerospace systems". The key mission of the technical committee as outlined in the charter is "to provide an AIAA forum..." for members of the technical community active in the study of formal design methodology based on an efficient integration of analysis and optimization methods. Such a forum currently exists in the form of technical meetings and publications of the AIAA, and can be further enhanced by input from the technical committee. In particular, the committee must ensure that the subject of these meetings and (2 of 18)12/29/ :29:58 PM

392 1.0 INTRODUCTION publications include all scientific disciplines involved in creating an effective multidisciplinary design optimization environment. To achieve this broad mission, the technical committee is organized around a number of subcommittees with narrower, more specific charters. Some of the subcommittees are standing committees to handle the ongoing business of the technical committee and others have finite lifetimes consistent with the nature of their activities. It is the expressed intent of the technical committee that the subcommittees be active, solicit committee member involvement, and conduct the primary business of the technical committee. 3. SUBCOMMITTEES/FUNCTIONS 3.1 Communications Subcommittees Education: To assess and make recommendations for improvement on all issues related to the teaching of multidisciplinary design optimization methods in both the university and the industry R&D environment and to develop a program for fostering a greater overall awareness of multidisciplinary design methods. Internet: To facilitate timely communications among TC members using the Internet for electronic messages and postings. This entails managing the TC World Wide Web site, administering TC electronic mailing lists, and archiving TC operational reports and data. Liaison: To coordinate activities and provide a channel of communication with other technical committees and outside organizations which contribute to advancing the state of technology in the design of aerospace systems. Publications: To compile and edit information for the yearly "highlights" article, and to distribute an updated committee operating manual and roster each year. White Paper:The white paper subcommittee is charged with initiating all MDO TC white paper efforts. The subcommittee reviews current white paper activities at the first of each year to determine if any new initiatives are needed during the coming year. 3.2 Technical Subcommitees Applications: To provide for an exchange of information related to the application of MDO methods at a level that can be explicitly measured in vehicle mission performance, weight, or cost. Also serves as a forum for industry to relate real world needs to government and academia. Benchmarking: To develop a set of test cases (formulations and solutions) for optimization in several MDO/Aerospace disciplines and in MDO itself, to be offered to the aerospace community as a means to measure performance of optimization methods. (3 of 18)12/29/ :29:58 PM

393 1.0 INTRODUCTION Conference support: To provide support to AIAA sponsored and co-sponsored conferences which include sessions or papers related to MDO. MA&O Symposium Support: To provide planning and support to MA&O symposiums which are cosponsored by AIAA and run by the MDO TC. 3.3 Planning Subcommitees The planning subcommittee has the task of insuring the long-range continuity of the MDO TC, including developing plans for the membership transition to continue a balanced mixture of disciplines and organizations, and to stimulate and coordinate planning in the subcommittees. The planning subcommittees are responsible for choosing new TC members from among the applicants. The planning subcommittee also has responsibility for keeping the Operations Manual up to date. Finally, this subcommittee is in charge of determining when the White Paper subcommittee should be reformed in order to generate a state of the art version. Awards: To act as a focal point in the recognition of outstanding contributions in the area of multidisciplinary design optimization. Charter: This subcommittee reviews current charter activities at the first of each year to determine if any new initiatives are needed during the coming year. It is anticipated that the charter will be updated on an annual basis. Membership: This subcommittee is charged with maintaining the current membership roster. The committee will issue a call for MDO TC member applications in late August of each year. This committee along with the current chair will review member applications and make recommendations to the full TC at the January TC meeting. 4.0 ACTIVITIES AND SCHEDULES 4.1 Committee membership and operation: The TC has a nominal membership limit of 35 members. Membership is for one year (May 1 to April 30) annually renewable for three years contingent on active participation in the TC and continued membership in the AIAA. These requirements may be relaxed under unusual circumstances; for example, to insure that membership terms are staggered for a new TC or to insure continuity of leadership or other specific duties. Nominations for committee members are requested in the early fall and may be submitted by any AIAA member (including self nomination). Non-AIAA members may be nominated but must join immediately after accepting membership on the TC. The TC chairman with the help of the Planning Subcommittee makes the membership selection and notifies new members in the early spring. The TC seeks to maintain a membership which reflects: a broad background in the (4 of 18)12/29/ :29:58 PM

394 1.0 INTRODUCTION technologies which contribute to multidisciplinary design optimization, a cross section of industry, government, and academic interests, a resonable geographic distribution, and a balance of technical and management skills. The TC chairman plays a vital role in the life of the committee. The TC chairman is responsible for running the biennial election process to ensure a smooth transition of leadership on the technical committee. Note that, while the TC chair is required to have been a member for one full year by the time the elections are conducted, the vice-chairs do not have to have prior TC experience; they must be full members, however. There is no limit as to how many times one may hold a particular position and, should your term on the TC expire during you tenure, it should normally be extended to enable you to fulfill your responsibility. Candidates should contact the current TC Chair to clearly identify the position they are running for. In addition, the candidates need to provide a write-up (~1-2 pages) describing their vision for the TC and what they intend to accomplish in their new position. These write-ups will be posted on the web for the membership to peruse, prior to voting. While any TC member may nominate another candidate, the TC would request that the nominee be contacted prior to nomination in order to assure their availability and willingness to run for office. The voting will be conducted electronically by the TC Chair, and the TC will need a quorum of the voting members (associate members are non-voting members) before validating the elections. TC members should give serious consideration to running for these positions. 4.2 TC Chair Selection Process The terms for the new Chair and Vice Chair/Technical, Vice Chair/Communications run for two years begining in May and ending in April. The curent term for new officers will run from May 1998 to April The election process should be completed prior to the Fall MDO TC meeting in the year preceeding the transition. This will enable the new office to overlap with the current one for 3 consecutive meetings. Note that the position of secretary is appointed rather than elected. Here is the timetable for election of new officers (1997): Call for nominations 1 July 1997 Nominations/background material due 30 July 1997 Background material posted on the Web by 3 August 1997 Electronic votes due 2 September 1997 Please consult the web page ( for responsibilities and conditions of eligibility (under Operations Information/TC Operations Slides). 4.3 Officer Responsibilities (5 of 18)12/29/ :29:58 PM

395 1.0 INTRODUCTION TC Chair Elected for 2 years from members who have at least one year of experience with the TC, in odd years, between spring and fall meeting, comes into office on May 1, even years. Attend all TC meetings Run planning committee Interface with TAC and AIAA Run elections for chair and vice-chairs Select subcommittee chairs from recommendations of vice-chairs, odd years Select subcommittee membership on recommendation of vice-chairs, review every year between Fall and Reno meeting, or when appropriate Present subcommittee reports for planning committee if chair absent TC Vice-Chairs Elected for 2 years, in odd years, between spring and fall meeting, comes into office on May 1, even years. Attend all TC meetings Coordinate Technical and Communications committees Lead subcommittees in reviewing their charters Stand-in for chair if absent Recommend subcommittee memberships Recommend subcommittee chairs Present subcommittee reports at meeting if subcommittee chair absent TC Subcommittee Chairs Appointed for 1 years by TC chair, every year by SDM meeting prior to entering service at Fall meeting, upon recommendation from vice-chair. Attend two out of three of all TC meetings, must have substitute fo the other meetings. Define, update subcommittee charter. Provide subcommittee information to webmaster. Run subcommittee business between meetings. Draft and present subcommittee written reports, submit to secretary. Recommend subcommittee membership to vice-chair. Recommend subcommittee chair upon leaving position. Secretary (6 of 18)12/29/ :29:58 PM

396 1.0 INTRODUCTION Appointed by the chair for two years, in even years, by SDM meeting prior to entering service at Fall meeting. Collect subcommittee reports, submit to webmaster within 30 days of meeting Deliver minutes of meeting to webmaster within 30 days of meeting Membership Selected yearly at Reno meeting by membership subcommittee Membership begins on May 1 of year selected Membership is renewable annually, typically for up to 3 years Membership may be renewed annually, beyond 3 years, at chair's discretion, if member has taken on a responsibility that extends beyond his/her tenure. Each member must participate actively in the activities of at least one subcommittee for continued membership 4.4 Subcommittee activities and schedules Subcommittee activities and schedules as they are currently available are included in this version of the manual. Others will be added as they are generated in the normal review and update process of this manual. Education: The activities of this subcommittee are of an ongoing nature. The subcommittee must develop a plan for both increasing the general awareness of the potential advantages of a formal design methodology and for coordinating the delivery of educational programs in the general area of multidisciplinary design optimization. In order to achieve these goals: The subcommittee plans to continue assisting in the development of requirements for various AIAA sponsored design competitions to encourage use of formal optimization tools at the senior undergraduate level. It has initiated contact with the AIAA Education committee to provide input for ABET requirements for design in the undergraduate aerospace curriculum and is currently soliciting specialized course topics in multidisciplinary design from MDO TC members. A sequence of courses related to multidisciplinary analysis and optimization are being offered. These can be attached to AIAA or ASME meetings, arranged at central sites, or delivered at specific industry/ R&D facilities. Informational articles can be written or solicited. These articles should be targeted at an audience without formal education in optimization and be published in Aerospace America. The same material can also be organized in a general informational lecture, suited for AIAA sectional or regional meetings. (7 of 18)12/29/ :29:58 PM

397 1.0 INTRODUCTION Develop a general informational database that includes the preparation of audio visual material in the subject area, and possible publication by AIAA. The subcommittee must play a key role in promoting the teaching of formal optimization techniques in engineering curricula. This must go beyond instruction of a traditional optimization course, and must focus to some degree on the integration of analysis and design. Considering the already stretched requirements of most undergraduate programs, this may be no easy task. The most likely place for incorporating such material is in capstone design courses at the senior level. Input and suggestions from the AIAA to the ABET accreditation board must be effectively used for this purpose. The education subcommittee can serve as a catalyst to encourage the inclusion of formal design optimization in undergraduate curricula by seeding and providing AIAA/Industry sponsorship to projects/papers/contests directly related to the application of optimization methods. A possible approach to this could be along the lines of the current AIAA design competitions. The subcommittee can also adopt an active role in reviewing the available literature and educational material in the subject area. Publications of reviews on new material as well as suggestions to major publishing houses on needs in specific areas can provide a very useful service to the technical community. Internet: This subcommittee provides three primary services to the MDO TC. First, the internet subcommittee maintains the TC World Wide Web site. This involves the following operations: maintaining accurate committee and subcommittee membership information, white papers, conference and short course information, an operations manual, a FAQ list, and related site information. posting of TC meeting location and agenda, meeting minutes, subcommittee reports, and current action items. updating the site to reflect advances in web technology and software. Second, the internet subcommittee administers electronic mailing lists for the TC in order to centralize management of the TC distribution. This involves the following operations: maintaining software (e.g., Majordomo) for list serving. maintaining accurate list subscriptions by updating member addresses and trouble-shooting problems. informing TC members of list purpose and proper usage. creating additional lists as required to accomplish further automation of TC operations. Third, the internet subcommittee archives both Web site postings and mailing list traffic in order to provide a browsable reference on past and present TC issues. This involves the following operations: (8 of 18)12/29/ :29:58 PM

398 1.0 INTRODUCTION maintaining software (e.g., LWGate) for mailing list archival. maintaining menus of past and present postings on the TC Web pages. Liaison: This subcommittee works closely with the TC chair to coordinate the activities of the MDO TC with those of the other AIAA TCs or other organizations. The subcommittee chair is appointed by the TC chair and is primarily responsible for assigning liasons to other TC meetings and collecting and reporting significant activities. These liasons communicate with the other TC's via their TC chair or liason chair or by attending their meetings when possible. The liason the communicates MDO related activities back to the MDO TC via the Liaison Chair. This communication is in the format of the MDO TC Liaison Report; found in the Appendix of this manual. Liaison assignments can be found in the subcommittee membership list. Currently representatives are assigned to the Aircraft Design TC, the Applied Aero TC, the Structures TC, the Structural Dynamics TC, the CAD/CAM TC, the Guidance and Control TC, Public Policy TC, the Thermophysics TC, and to ASME and PMEC. Publications: This subcommittee distributes the roster and operating manual to new members at the first meeting of the year or as soon after as practical. It compiles and edits information for the yearly "highlights" article at the end of each year and reviews the operating manual for possible update. White Paper: The committee will periodically generate and review a white paper expressing the collected views of the technical committee and describing the state-of-the-art in integrated multidisciplinary design analysis and optimiztion. Applications : This subcommittee provides for the exchange and dissemination of information related to the application of MDO methods at a level that can be explicitly measured in vehicle mission performance, sized weight, and/or cost. Emphasis will be placed on current and planned activities to integrate MDO methods in the standard design pro-active of aerospace systems. The methods themselves, as well as design experiences, overall benefits, and impediments to formal MDO methods, will be subjects to be considered by the subcommittee. The subcommittee will also serve as a forum for industry participants to relate the "real world" needs associated with MDO to the academic and government members of the MDO TC. Specific activities include: Promote presentation and publication of experiences with and plans for the application and utilization of MDO methods into the vehicle synthesis/design environment arrange invited speakers at conferences and MDO Technical Committee meetings arrange special sessions at conferences encourage publication of journal articles Identify and disseminate information pertaining to the benefits of formal MDO methods to overall vehicle performance, size, range, and/or cost Assess and report the MDO needs of advanced (conceptual/preliminary) vehicle design or synthesis organizations Define multidisciplinary metrics and figures of merit Examine issues related to overall vehicle synthesis that MDO can influence. E.g. shorten design (9 of 18)12/29/ :29:58 PM

399 1.0 INTRODUCTION cycle, improve product, reduce development cost, reduce manpower required for design, capture human experience, etc. Benchmarking: This subcommittee is to develop a set of test cases (formulations and solutions) for optimization in several MDO/Aerospace disciplines and in MDO itself, to be offered to the aerospace community as a means to measure performance of optimization methods. Also, available and future capabilities in multidisciplinary design optimization are to be compared benchmarked according to a standard set of problems and performance measures. Conference support: The MDO TC has had an evolving presence at conferences over the past several years. The current focus is on the SDM (various locations, April), Aircraft Engineering, Technology, and Operations (various locations, August), Aerospace Sciences (Reno, January), and MA&O (various locations, September bi-annually) conferences but this is expanding. Note that support of the MA&O Symposium is handled by the MA&O Conference Support subcommittee. The activities include participating in conference planning, organizing and chairing sessions, writing calls for papers, and paper review to ensure that meetings reflect the appropriate involvement of the scientific disciplines which contribute to multidisciplinary design optimization. The schedule for session organization and paper review for these conferences is keyed to the conference date. MA&O Symposium Support: The MDO TC has primary control and responsibility of the MA&O Symposium which is held in even years during September at various locations. The subcommittee is responsible for planning, organizing, writing the call for papers, and choosing chairing sessions, and paper review. Papers are chosen to ensure that symposium reflects involvement multidisciplinary analysis, design, and optimization. The schedule for the call for papers, paper review, and session organization is keyed to the conference date. Awards: At the beginning of each year, the Awards subcommittee will survey the new members of the MDO TC and advocate the promotion of deserving members to Senior Member, Associate Fellow, and Fellow status. Members who are upgraded shall be recognized during the appropriate TC meeting. The requirements for upgrades are found below in brief and in detail at the AIAA Membership Upgrades: Senior Members - Persons who have demonstrated a successful professional practice in the arts, sciences, or technology of aeronautics for the equivalent of at least eight years, or the applicant shall have at least eight years of continuous professional membership. Applications are reviewed by the Membership Committee on a monthly basis. Senior Members receive a certificate and lapel pin. (10 of 18)12/29/ :29:58 PM

400 1.0 INTRODUCTION Associate Fellows - Persons who have accomplished or been in charge of important engineering or scientific work, or who have done original work of outstanding merit, or who have otherwise made outstanding contributions to the arts, sciences or technology of aeronautics or astronautics. Nominees must be Senior Members with at least 12 years of professional experience (four years of post-graduate studies may be included, if applicable). Three AIAA member references with the standing of the Associate Fellow, Fellow or Honorary Fellow are required. Nomination forms are due by April 15; references are due by May 15. Newly elected Associate Fellows receive a certificate and lapel pin. A list of newly elected Associate Fellows is published every January in Aerospace America. Fellows - Persons of distinction in aeronautics or astronautics, and shall have made notable valuable contributions to the arts, sciences, or technology thereof. Nominees must be of Associate Fellow status. Five references are required. Nomination forms are due by June 15; references are due by July 15. Newly elected Fellows receive a certificate and lapel pin and are honored at the Honors Night Banquet, in conjunction with the Global Air & Space Conference. During the Reno (January) and SDM (April) names are collected for who the TC should nominate for the rank of fellow. During the SDM (April) meeting the TC votes on who, if anyone, the awards committee should nominate for the rank of fellow. During the year the subcommittee will contribute to the selection of award recipients for existing AIAA awards based on established schedules and AIAA calls for participation. This includes the SDM award and the new AIAA award in the area of multidisciplinary optimization which is given bi-annually at the MA&O symposium. All of the awards procedures can be found in the AIAA Honors and Awards Manual. The Multidisciplinary Design Optimization Award was established by this TC. The chairman of the awards subcommittee should remind the TC members during the fall meeting to submit nominations to AIAA for this award. The selection of the recipient of this award is made by this subcommittee as follows: 1. In October of the year proceeding the MA&O conference the call for nominations is published in Aerospace America. A copy of the call for nominations, as well as the nomination form, are mailed to each TC chairman. 2. The nominations must be submitted to AIAA headquarters by mid January (January 12 in 1996). 3. The nominations are passed on to this subcommittee in late January. 4. Members of a selection committee are chosen by this subcommittee using the following AIAA guidelines: The selection committee should be a representative sampling of the professional peer (11 of 18)12/29/ :29:58 PM

401 1.0 INTRODUCTION group(s) in the technical specialty(ies) of concern. They are not required to be current TC members, but must be members of AIAA. At least two members should be members of the TC. Former award winners are often useful and willing to be selection committee members. They may not be able to serve as regular TC members but are often quite willing to undertake this less-time-consuming task. Whenever possible (without violating other important guidelines), the total selection committee membership should be an odd number to eliminate tie votes. 5. The selection committee must determine the award recipient and award citation by the end of February. The information is passed along to the Awards Subcommittee, which in turn, passes it along to AIAA headquarters. 6. The award recipient is notified in mid March. 7. The award is presented at the MA&O conference in mid September. The nomination material for candidates that do not receive the award are kept for two years. These candidates are automatically considered for the next award. More details on the technical awards procedure can be found in the AIAA Honors and Awards Manual. The MDO TC chooses the recipient of the best paper award for the MA&O symposium. AIAA has no set procedure for determining the best paper of a conference. The choice is completely up to the TC sponsoring the conference. Requirements for best paper: 1. Full length papers only. 2. The paper must have been presented at the conference. 3. The paper must be in the printed proceedings. This is so people can go back and read the best paper after it has been announced. The selection committee wants to determine the best paper without having to read through all of the conference papers. The potential best papers were determined to be: The best paper in each session as determined by the session co-chairs The top 15 most highly rated abstracts from the conference paper selection reviews Following is the procedure in use to determine the recipient of the best paper award. This procedure may be modified in the future. There will be about 50 papers in consideration for the best paper and 5 (12 of 18)12/29/ :29:58 PM

402 1.0 INTRODUCTION reviewers. STEP 1: Break the papers into 5 groups of about 10 and have each reviewer review 2 groups. This way each paper is reviewed by two reviewers. Each reviewer will choose the 5 best papers out of the about 20 reviewed. STEP 2: There will be up to 25 papers after STEP 1. These will be broken into 5 groups of 5 and each reviewer will again review two groups. No reviewer will review a paper that he reviewed in STEP 1. This way each paper is reviewed by four reviewers. Each reviewer will choose the 2 best papers out of the up to 10 reviewed. STEP 3: There will be up to 10 papers after STEP 2. Each reviewer will review all of the papers and rank them The papers will be assigned points based on their rank, i.e. 1 for the best, 2 for the second best, etc. The points for each paper for each review will be added up. The three papers with the lowest point total will go to STEP 4. STEP 4: The reviewers will decide which of the 3 papers from STEP 3 should receive the best paper award. As soon as the best paper is chosen, the authors should be notified by mail that they will be receiving an award at the next MA&O conference. The selection should be made by the SDM conference following the MA&O symposium. Also, the authors of the 10 papers selected in Step 2 will be notified by mail that their papers were finalists in the best paper award selection procedure. Draft policy for MDO TC Support of Fellow Nomination 1. The MDO TC will endorse a maximum of one nomination for AIAA Fellow Status each year. 2. The endorsement will take the form of a letter signed by the TC chair and logistical support provided by the Honors and Awards subcommittee. 3. Each year at the Reno meeting the TC will initiate the process of at most one candidate to receive its nomination. Names and bios will be solicited after the Reno meeting, and an electronic vote to select a nominee will be completed within two months. 4. Each suggested candidate will have a nominator who is responsible for writing the nomination letter and obtaining commitments from five references. 5. Candidates for the TC's endorsement must have made significant contributions to the field of MDO. Charter: This subcommittee reviews current charter activities at the first of each year to determine if any (13 of 18)12/29/ :29:58 PM

403 1.0 INTRODUCTION new initiatives are needed during the coming year. It is anticipated that the charter will be updated on an annual basis. Membership: This subcommittee is charged with maintaining the current membership roster. The committee will issue a call for MDO TC member applications in late August of each year. This committee along with the current chair will review member applications and make recommendations to the full TC at the January TC meeting. 5.0 APPENDICES 5.1 Latest 3 year plan (to be added when available) 5.2 Sample Liaison Report Submitted by: TC: TC Chairperson: Contact for TC meeting minutes: Their Liaison to MDO TC: Last TC meeting date: Last TC meeting location: Last TC meeting attendance: Items of interest to MDO TC: 5.3 AIAA Short Course Review Procedure MDO TC Liaison Report Proposals for AIAA Short Courses which seek support or sponsorship by the AIAA MDO TC should be sent to the AIAA MDO TC Education Subcommittee Chair. Proposals must include a syllabus with identification of the courses MDO content, a list of speakers and their resumes, with emphasis on prior work and teaching experience. This syllabus should include an hourly breakdown of topics where applicable. The education subcommittee chair will arrange for up to three AIAA MDO TC members (14 of 18)12/29/ :29:58 PM

404 1.0 INTRODUCTION (not necessarily education subcommittee members) to review the Short Course proposal. Reviewers will provide a brief assessment of the short course proposal and will recommend that the AIAA MDO TC accept or decline sponsorship of the short course. Reviewers will be asked to pay particular attention to the MDO content of any short course proposal. In order that a short course be sponsored by the AIAA MDO TC there must be some significant content which addresses issues pertinent to MDO. For example; numerical optimization, system decomposition and synthesis, multidisciplinary design methodologies and strategies, etc.. Once these reviews are completed they will be distributed to the Education Subcommittee Members via electronic mail. The Education Subcommittee will vote as a committee (via ) to accept or decline sponsorship of the short course. The Education Subcommittee's recommendation will be passed onto MDO-TC chair and executive committee. It is expected that proposals submitted via this procedure will be acted on and that the person submitting the proposal will be notified of acceptance or declination within two months from the date of submission. The Education Subcommittee Chair may elect to return the initial reviews to the person submitting the proposal for revision of the short course proposal prior to forwarding the reviews to the Education Subcommittee. Any revisions would need to be reviewed prior to moving the proposal forward to the chair and executive committee. After the short course is held, AIAA will return reviews to the MDO-TC and Education Subcommitee for review 5.4 TC Operations/Calander Even Years January winter meeting, ASM/Reno select new members begin Fellow program annual report due group director new roster due AIAA February select subcommittee chairs select SDM representative (follow. year) March April spring meeting, SDM begin selection of next MA&O team May membership year begins fellow nomination(s) due (15 of 18)12/29/ :29:58 PM

405 1.0 INTRODUCTION June fellow recommendation(s) due July August September fall meeting/ma&o conference (all-day) new office first meeting MDO award ceremony select subcommittee membership begin best MDO paper selection October November December select ASM representative (follow. year) 5.5 TC Operations/Calander Odd Years January winter meeting, ASM/Reno select new members begin Fellow program annual report due group director new roster due AIAA February select subcommittee chairs select SDM representative (follow. year) March April spring meeting, SDM May membership year begins fellow nomination(s) due (16 of 18)12/29/ :29:58 PM

406 1.0 INTRODUCTION June fellow recommendation(s) due July begin office election process August September fall meeting/location tbd announce new office new office first meeting select subcommittee membership October November December select ASM representative (follow. year) 5.6 Plan for Electing New General Chair for Multidisciplinary Analysis and Optimization Symposium Process for Identifying New General Chair: In August or September of the year preceding the biennial Multidisciplinary Analysis and Optimization Symposium, the TC Chair will make an announcement that the TC will be accepting nominations from individuals who wish to serve as General Chair for the next (three years out) MAO Symposium (this announcement should be made to all present and past members of the TC, as well as to ISSMO members). Past and present TC Members can nominate themselves or be nominated by others. However, if the nomination is not a self-nomination, there must be an assurance that the individual being nominated wants to serve in this capacity. Nominations must be written nominations which outline the resources that the individual can commit to the task and any experience/background which might make him/her appropriate for handling the outlined responsibilities below. The nominee can also comment on what procedure he/she would use to identify a Technical Chair. Prior to the fall TC meeting, the TC membership will review nominations. At the fall TC meeting a vote of the TC will elect the next General Chair for the MA&O Conference (three years out). The next (17 of 18)12/29/ :29:58 PM

407 1.0 INTRODUCTION General Chair is encouraged to select a Technical Chair before the ASM meeting in Reno. The election three years prior to the MA&O conference will provide the Technical Chair with greater flexibility in coordinating the site selection process with AIAA and the TC. The new chairs can be introduced during the banquet at the MA&O Symposium the following September. A briefing meeting of the new chairs and present chairs will then take place at the MA&O Symposium. Responsibilities of General Chair: One of the first responsibilities of the General Chair will be to choose an appropriate Technical Chair for the conference. The General Chair works with AIAA to identify the conference site (this typically entails traveling to at least one and perhaps more potential sites, funding for which must come from the General Chair or his company), plans all 'extra-curricular' activities (e.g. banquets, dinners, etc.) and makes arrangements for plenary and banquet speakers. Other responsibilities would be worked out with the Technical Chair and often includes such things as preparing or assisting in preparing the Call for Papers and any other literature associated with the conference, and assisting with the organization of the sessions (which would again involve travel if the Technical Chair is geographically located elsewhere). Responsibilities of Technical Chair: The Technical Chair interfaces with AIAA and the General Chair on all technical matters pertaining to the conference. This includes preparing literature mailings (i.e. Call for Papers, etc.), receiving all abstracts, arranging for review of abstracts, determining acceptance or rejection of abstracts (often with assistance from the General Chair and/or Organizing Committee), organizing special panel or technical sessions, etc. The last two conferences have used Superchairs who are responsible for arranging abstract reviews within topic areas. The Technical Chair is responsible for identifying and interfacing with Superchairs, if this organizational structure is used. If used, volunteers for Superchair duty will be accepted at the MDO TC meetings in the year prior to abstract submission. Back to MDO TC Home Page Last Updated: 13 December 2001 Tony Giunta, aagiunt@sandia.gov (18 of 18)12/29/ :29:58 PM

408 MDO TC Subcommittee Membership MDO TC Subcommittee Membership The AIAA MDO TC has two types of subcommittees: those which support AIAA services and activities (such as conferences and awards), and those which address particular technical topics of interest to TC members and the MDO community at large. TC members are invited (new members especially) to review the enclosed subcommittee descriptions and contact the subcommittee Chairman to volunteer for service on any particular subcommittee. Subcommittees meet at the discretion of their Chairs, who report any activity at the regular TC meetings. Each Chairman should also review the subcommittee membership for completeness and correctness, and notify the TC Chair with changes of subcommittee membership. Also, if you feel that any area of important potential TC activity is not adequately covered by the existing subcommittee structure, please feel free to propose new subcommittees to the TC Chairman (of course, you will probably be asked to head the new subcommittee!). Applications Awards Education Publications Subcommittees Applications Purpose: To provide for an exchange and dissemination of information related to the application of MDO methods at a level that can be explicitly measured in vehicle mission performance, weight, or cost. Also serves as a forum for industry to relate real world needs to government and academia. Chair: Tim Purcell timothy.w.purcell@boeing.com Members: Stephen Batill batill@nd.edu (1 of 4)12/29/ :29:59 PM

409 MDO TC Subcommittee Membership Elias Bounajem Evin Cramer Guru Guruswamy Ram Krishnamachari Achille Messac Vassili Toropov Brett Wujek Awards Purpose: To act as a focal point for recognition of outstanding contributions in the field of multidisciplinary optimization. The Awards Subcommittee was instrumental in establishing the biennial MDO Award, and on an ongoing basis is principal in the selection of candidates for this award, nominations and selection for other AIAA awards such as the SDM, and in nomination of AIAA Associate Fellows for upgrade to Fellow membership status. Chair: Lt. Col. Robert Canfield Robert.Canfield@afit.edu Members: Max Blair maxwell.blair@afrl.af.mil Srinivas Kodiyalam skodiyal@sgi.com Achille Messac messac@rpi.edu Somanath Nagendra snagendra@att.net Hans Schweiger johannes.schweiger@m.dasa.de Afzal Suleman suleman@uvic.ca Karen Wilcox kwillcox@mit.edu Scott Zink scott.zink@lmco.com AIAA Information: AIAA Honors and Awards Manual. Education Purpose: To coordinate activities related to education in multidisciplinary design optimization, both within AIAA and related activities outside of AIAA. These activities include coordinating and (2 of 4)12/29/ :29:59 PM

410 MDO TC Subcommittee Membership sponsoring Short Courses, soliciting or writing informational articles about MDO activities for the education community, promoting teaching of formal optimization and MDO techniques in engineering curricula, supporting AIAA sponsorship of student projects and competitions, reviewing the available literature and educational material, etc. Chair: Kemper Lewis Members: Kurt Anderson Oktay Baysal Wei Chen Bernie Grossman Zafer Gurdal Doug Smith Afzal Suleman Publications Purpose: Oversee publication activities of the MDO TC. These have included a White Paper (published as an AIAA Report), Newsletter (now maintained at this Web site), and the annual Aerospace America Highlights article. Chair: Fred Striz striz@ou.edu Members: Vladimir Balabanov vladimir@vrand.com Dan DeLaurentis dan.delaurentis@aerospace.gatech.edu Tony Giunta aagiunt@sandia.gov Narendra S. Khot narendra.khot@wpafb.af.mil James Reuther jreuther@mail.arc.nasa.gov Ravindra V. Tappeta tappeta@crd.ge.com Last Updated: 16 January (3 of 4)12/29/ :29:59 PM

411 MDO TC Subcommittee Membership Anthony A. Giunta, (4 of 4)12/29/ :29:59 PM

412 How to join the AIAA MDO TC How to join the AIAA Multidisciplinary Design Optimization Technical Committee You may nominate yourself or someone else for membership on a technical committee. For each nominee you must submit a nomination form along with a resume or biographical data. If you nominate someone for more than one committee, list each technical committee (TC) on one form. If you are invited to be on more than on TC, you must select one committee for membership, (as you can only be on one TC at a time). If you are appointed to a TC and you are not a member of AIAA, you must join AIAA within one year of your appointment. If you are not appointed, your nomination will automatically be considered for the following year. TC membership is for one year, with two additional years possible. Committee members are automatically considered for a second and third year of membership and do not have to submit new forms. Deadline for receipt of nominations is November 1. Download the nomination form from the AIAA Web Site and then mail it to AIAA Technical Committee Nominations, 1801 Alexander Bell Drive, Reston, VA 20191, or FAX it to 703/ For more information, see Nomination Requirements and Nomination Form Instructions. Back to MDO TC Home Page Last Updated: 17 October 2002 Anthony A. Giunta, aagiunt@sandia.gov 12:30:00 PM

413 Operations Slides Operations Slides (1 of 7)12/29/ :30:02 PM