ANERS 2011 October Marseille, France

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1 ANERS 2011 October Marseille, France An Integrated Approach for the Multidisciplinary Optimization of Modern Rotorcraft Operations Work done by: Ioannis Goulos, Cranfield University, UK Vassilios Pachidis, Cranfield University, UK Roberto D Ippolito, LMS International, BE Jos Stevens, National Aerospace Laboratory NLR, NE Chrissy Smith, AgustaWestland, UK

2 Presentation contents Introduction Methodology Case study Results Conclusions End of presentation Image courtesy of Turbomeca Platform Hosting Operational & ENvironmental Investigations for Rotorcraft Image courtesy of AgustaWestland 2

3 Introduction Civil rotorcraft activities include [1]: Civil transport Aerial work Medical evacuation Search & rescue Civil protection Offshore transport Law enforcement applications Operations are expected to grow sharply in the future to meet the continuously increasing citizen demands [1] Quadruplicating the values mentioned above Significant contribution to the overall air traffic environmental impact Image courtesy of Airplane-pictures.net Estimated 1,500,000 flight hours annually in Europe Equivalent of 400,000 tons of fuel per year in the European Community only [1] Roberto d Ippolito, Jos Stevens, Vassilios Pachidis, Antonio Berta, Ioannis Goulos, Caterina Rizzi, A Multidisciplinary Simulation Framework for Optimization of Rotorcraft Operations and Environmental Impact, 2 nd International Conference of Engineering Optimization, September 6-9, 2010, Lisbon Portugal 3

4 Introduction Consequences of the progressively increasing rates of fossil fuelbound energy consumption include: Severe environmental impact due to the produced emissions associated with fossil fuel combustion Increasing cost of fossil based fuels Goals set by Advisory Council for Aeronautics Research in Europe (ACARE) to be achieved by 2020 include [2] 50% reduction in carbon dioxide (CO2) emissions 80% reduction in nitrogen oxide (NOx) emissions [2] Advisory Council for Aeronautics Research in Europe home page http// 4

5 Introduction Paths towards the reduction of environmental impact [3] Incorporation of different types of aircraft rotorcraft configurations Deployment of alternative operational rules and procedures seeking of optimal, energy optimized flight paths [3] Clarke, J. P., 2003, "The Role of Advanced Air Traffic Management In Reducing the Impact of Aircraft Noise and Enabling Aviation Growth, Journal of Air Transport Management, 9(3), pp Wide range of research & development activities at national and European levels focus on operational procedures [4] [4] Clean Sky JTI (Joint Technology Initiative) home page 5

6 Methodology Deployed simulation tools EUROPA: Helicopter flight mechanics tool Trim performance during cruise and banking Dynamic response during take-off and landing Validated tool with proven applicability GSP: Engine performance simulation tool Steady state design point and off-design simulation Combustor emissions based on semi-empirical ratio Validated for engine performance and partly validated for emissions HELENA: Noise prediction tool Noise source data: experimental or calculated (CFD) Noise directivity calculation Multi-source asymmetrical interactions 6 Validated with dedicated flight tests Image courtesy of Eurocopter

7 Methodology Platform Hosting Operational & ENvironmental Investigations for Rotorcraft Flight conditions Atmosphere Mission profiles Helicopter data Noise source data H/c position H/c attitude Rotor thrust (Rotor angles) (Power required) optimization iteration Power required Atmosphere GSP Engine data Fuel flow Code linking performed with Noesis Optimus process and simulation integration framework Noise footprint Emissions 7

8 Methodology Problem specification Methodology objectives design outputs Acquisition of optimally designed missions for: Minimized fuel burn CO2 emissions Minimized NOx emissions Effective Perceived Noise Level (EPNL) over any designated populated zone Definition of design variables - constraints Four-dimensional mission variation in terms of: Cruise altitudes Cruise speeds Loitering altitudes (where applicable) Loitering speeds (where applicable) Longitude - latitude variation of mission end-points No constraints implemented at this point 8

9 Methodology Mission design space definition (Mission scenario) Design Of Experiment(DOE) Latin Hypercube Design (LHD) Build Response Surface Models (RSM) Interpolation using Radial Basis Functions Mission Scenario definition Deployed optimization strategy LHD RSM 9

10 Methodology Deployed optimization strategy For each of the design outputs use RSMs for: Single objective global optimization Self-Adaptive Evolution (SAE) Single objective local optimization Non Linear Programming by Quadratic Lagrangian (NLPQL) SAE progress Having found single objective-optimum trajectories: Multi - objective global optimization Boundary Intersection Method Create Pareto fronts for any two design parameters of interest Pareto front examples 10

11 Case study Rotorcraft configuration MBB Bo 105 Crew: 1 or 2 pilots Capacity: 4 Length: m (38 ft 11 in) Rotor diameter: 9.84 m (32 ft 3½ in) Height: 3.00 m (9 ft 10 in) Max take-off weight: 2,500 kg (5,511 lb) Rolls-Royce Allison 250-C20B rated at 313KW Design point air mass flow rate: (kg/s) Compressor design point pressure ratio: 7.2 Design point fuel flow: (kg/s) Design point power turbine rotor speed: (rpm) Image courtesy of Rolls-Royce Image courtesy of Eurocopter 11

12 Case study Mission scenarios definition 1. Law enforcement/police (Long range) 2. Passenger transport/air taxi (Short range) Stockholm, Sweden Three populated zones have been defined for each mission Hanover, Germany 12

13 Case study Baseline mission scenarios 1. Law enforcement / Police 2. Passenger transport / Air taxi Category A take-off maneuver Climb to 1500 ft at 80 knots at 1000 ft/min Cruise at 120 knots at 1500 ft Loiter at 60 knots at 1000 ft Cruise at 120 knots at 1500 ft Descend to 1000 ft at 120 knots at 750 ft/min Helideck landing maneuver Image courtesy of Eurocopter Category A take-off maneuver Climb to 1500 ft at 80 knots at 1000 ft/min Cruise at 120 knots at 1500 ft Descend to 1000 ft at 120 knots at 750 ft/min Helideck landing maneuver Repeat for each leg of the mission ( 3 legs) 13

14 Case study Mission variable range definition 1. Law enforcement / Police 2. Passenger transport / Air taxi Category A take-off maneuver Climb to [ ] ft at 80 knots at 1000 ft/min Cruise at [80-140] knots at [ ] ft Loiter (2X5 circles radius 2 km) at [40-80] knots at [ ] ft Cruise at [80-140] knots at [ ]ft Descend to 1000 ft at 100 knots at 750 ft/min Helideck landing maneuver +4 endpoint latitude variables for leg 1 +5 for leg 2 Image courtesy of Eurocopter Total no of variables Police mission 15 Air taxi mission 14 Category A take-off maneuver Climb to [ ] ft at 80 knots at 1000 ft/min Cruise at [80-140] knots at [ ] ft Descend to 1000 ft at 100 knots at 750 ft/min Helideck landing maneuver Repeat for each leg of the mission ( 3 legs) +4 end point longitude variables per cruise leg for the first 2 legs 14

15 Results 1. Law enforcement/police Long range baseline Fuel flow and equilibrium emissions grams/sec Total mission time: 1 hr 37 min 3 sec Total mission range: km Total fuel burnt: kg CO2 emitted: kg NOx emitted: 1.02 kg EPNL1: db EPNL2: db EPNL3: db Fuel Flow CO2 H2O Time (sec) 15

16 Results 2. Passenger transport / Air taxi Short range baseline grams/sec Fuel flow and equilibrium emissions Fuel Flow CO2 H2O Time (sec) Total mission time: 30 min 40 sec Total mission range: km Total fuel burnt: kg CO2 emitted: kg NOx emitted: 0.32 kg EPNL1: db EPNL2: db EPNL3: db 16

17 Results Latin Hypercube Design of Experiment 1. Law enforcement / Police 2. Passenger transport / Air taxi A total of 600 experiments has been performed for both cases 17

18 Results Latin Hypercube Design of Experiment: Correlation values 1. Law enforcement / Police 2. Passenger transport / Air taxi Strong correlation ( ) between fuel burn and CO2 for both missions allows the deployment of a single optimization to minimize both quantities (fuel burn CO2) Strong correlation between fuel burn - CO2 (0.999) and NOx emissions (0.964) for mission 2 allows the deployment of a single optimization to minimize fuel burn, CO2 and NOx simultaneously 18

19 Results Response Surface Modeling: Interpolated models 1. Law enforcement / Police 2. Passenger transport / Air taxi Multi-quadratic Radial Basis Functions(RBF) have been used for interpolation 19

20 Results Single objective optimization process Convergence check 1. Law enforcement / Police SAE progress NLPQL progress 2. Passenger transport / Air taxi SAE progress NLPQL progress

21 Results Response surface modeling: Quality check Comparison between acquired optimums Simulation/ Relative error % 1. Law enforcement / Police Fuel burn CO2 NOx EPNL1 EPNL2 EPNL3 Fuel Burn Opt NOx Opt EPNL1 Opt Passenger transport / Air taxi Simulation/ Relative error % Fuel burn CO2 NOx EPNL1 EPNL2 EPNL3 Fuel and Emissions Opt EPNL1 Opt

22 Results Single objective optimization results: Trade-off analysis Results from direct simulations (not RSMs) Mission Comparison 1. Law enforcement / Police Fuel Burn % CO2 % NOx % EPNL1 % Fuel-CO2/Baseline NOx/Baseline EPNL1/Baseline NOx/Fuel-CO EPNL1/Fuel-CO Fuel-CO2/NOx EPNL1/NOx Fuel-CO2/EPNL NOx/EPNL Optimizations performed for mission 1 1. Fuel CO2 2. NOx 3. EPNL1 2. Passenger transport / Air taxi Mission Comparison Fuel Burn % CO2 % NOx % EPNL1 % Fuel-Emissions/Baseline EPNL1/Baseline EPNL1/Fuel-Emissions Fuel-Emissions/EPNL Optimizations performed for mission 2 1. Fuel CO2 - NOx 2. EPNL1 22

23 Results Multi-objective optimization Pareto fronts formation 1. Law enforcement / Police 2. Passenger transport / Air taxi EPNL1(db) EPNL1(db) Fuel burn (kg) Fuel burn (kg) Normal-Boundary Intersection Method has been deployed using RSMs 23

24 Results Multi-objective optimization Pareto front derived models EPNL1(db) 1. Law enforcement / Police 2. Passenger transport / Air taxi EPNL1(db) Fuel burn (kg) Fuel burn (kg) Multi-quadratic Radial Basis Functions have been used for interpolation Pareto front models are used to design missions according to requirements 24

25 Results 1. Law enforcement / Police - (EPNL1-Fuel burn) optimized Comparison with baseline mission Cruise 1 at knots at ft Loiter at knots at ft Cruise 2 at knots at ft Total mission time: % Total mission range: +6.15% Total fuel burnt: % CO2 emitted: % NOx emitted: % EPNL1: -9.62% EPNL2: -7.8% EPNL3: -0.37% 25

26 Results 2. Passenger transport / Air taxi (EPNL1 Fuel burn) optimized - Comparison with baseline mission Cruise 1 at knots at ft Cruise 2 at knots at ft Cruise 3 at knots at ft Total mission time: +2.6% Total mission range: +0.39% Total fuel burnt: -5.12% CO2 emitted:-5.12% NOx emitted: % EPNL1: -5.34% EPNL2: +0.48% EPNL3: -0.59% 26

27 Conclusions An integrated approach for the multidisciplinary optimization of modern rotorcraft operations has been presented Optimization for fuel burn, noise and gaseous emissions (CO2, NOx) Quantitative benefits dependent on mission range For a long range mission: Fuel burn CO2 reduction achievable up to 19% NOx reduction achievable up to 27% Compared to a typical sub-optimal baseline For a short range mission: Fuel burn CO2 reduction achievable up to 6.8% NOx reduction achievable up to 14% Image courtesy of Eurocopter Compared to a typical sub-optimal baseline New methodology aiming towards the design of more efficient environmentally friendly missions Applicability to any defined mission and any specified helicopter configuration 27

28 End of presentation Thank you for your attention 28

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