Generation of Comprehensive Surrogate Kinetic Models and Validation Databases for Simulating Large Molecular Weight Hydrocarbon Fuels

Transcription

1 Generation of Comprehensive Surrogate Kinetic Models and Validation Databases for Simulating Large Molecular Weight Hydrocarbon Fuels Principal Investigator: Prof. Frederick L. Dryer Other Co-Investigators and Institutions: Prof. Yiguang Ju Princeton University (PU) Prof. Chih-Jen Sung Case Western Reserve University (CWRU) Prof. Kenneth Brezinsky University of Illinois at Chicago (UIC) Prof. Thomas A. Litzinger Penn State University (PSU) Prof. Robert J. Santoro Penn State University (PSU) Visiting Researchers: Prof. Henry J. Curran (NUI Galway) Princeton University (PU) Technical Management: Dr. Julian Tishkoff, AFOSR MURI Topic: #12:Science-Based Design of Fuel-flexible Chemical Propulsion/Energy Conversion Systems Funding : 3 years: $4.5M; 2 Additional years: $3.0M; Five years (total): $7.5M Initiation Date: July 1, 2007

2 Purpose Generate a base, jet fuel surrogate component model, cross-validated critical experimental data, detailed and reduced kinetic mechanisms, analytical tools and experimental methods to accurately predict the complex gas phase combustion behavior of real fuels using a small (minimal) number of chemical components. Emulate Gas Phase Kinetic/transport properties now Provide evolving models as program progresses Provide foundation for additional refinements in future Further refinement of target predictions Additional kinetic property target inclusions Fuel physical property targets

3 Anticipated Outcome Validated principles to select surrogate components Cross-validated comprehensive experimental database for the selected components and component mixtures Characterization of real fuel kinetic properties in same fundamental venues as those used to characterize surrogates Detailed kinetic models for individual components, and their mixtures, coupled with laminar transport Selection and refinement of combustion target parameters Rules and methods for matching real fuel gas phase combustion properties with surrogate mixture properties Tools to produce low dimensional models for CFD applications

4 Impact on DoD Capabilities Enhanced efficacy in evaluating fuel property effects on existing propulsion system performance and emissions Improved paper design and development for advancing existing and developing new propulsion concepts Assistance in integrating new alternative fuel resources into the aero-propulsion sector

5 Recent Work Impacting Our Program Plan Surrogate Fuels Working Group (2003 present) Initiated following 2003 NIST Workshop to evolve community consensus on how to approach modeling real fuels: model target parameters, surrogate fuel component choices, property, validation venue, data needs : Three cross-collaborative sub-group efforts; Extensive literature/current effortsreview & discussions summarized in: Colket, M., et al., Development of an Experimental Database and Kinetic Models for Surrogate Jet Fuels, AIAA Paper , January 2007 Farrell, J. T., et al., "Development of an Experimental Database and Chemical Kinetic Models for Surrogate Diesel Fuels", SAE Paper , April 2007 Pitz, W. J., et al., "Development of an Experimental Database and Chemical Kinetic Models for Surrogate Gasoline Fuels", SAE Paper , April 2007 CFD4C: Hohmann, Uslu, MTU Aero Engines ( ) n-heptane/iso-octane/toluene Surrogate Mixtures for Emulating Gasoline A Surrogate Mixture Study: Partially Reduced Skeletal and Semi-Empirical Kinetic Models for Gasoline ( ) GM Contract Number TCS07695 (Princeton University) Fuel Chemistry Models for Simulating Gasoline Kinetics in Internal Combustion Engine Applications ( ) Honda Research Agreement (Princeton University)

6 Real Fuel Chemical Component Characteristics Hydrocarbon Class Distribution in Jet-A (wt.%) Cycloparaffins 20% ND 1% Misc. 2% n-paraffins 28% Naphthalenes 2% Alkylbenzenes 18% i-paraffins 29% Boiling point range, F Paper: AIAA

7 How Variable are Real Jet Fuel Properties? Fraction of delivered JP-8 fuels (in 2005) with specified aromatic concentration Petroleum Quality Information System Table 2. Composition results for 55 world survey fuels 9.* World survey average, vol % Composite Jet A blend paraffins (n- + i-) Monocycloparaffins Dicycloparaffins Tricycloparaffins alkyl benzenes indans+tetralins Naphthalene 0.13 <0.2 substituted naphthalenes While an average jet fuel can be envisioned, there are large variations from the average. Paper: AIAA

8 JP-8 Properties (2005) Petroleum Quality Information System

9 JP-8 Properties (2005) Petroleum Quality Information System

10 Are Real Fuels Well Characterized Chemically? ASTM and Mil Fuel Certification procedures for defining real fuels are operations-oriented and do not provide sufficient information on the chemical fuel (component) properties that relate fundamentally to fundamental combustion kinetic and transport behavior. Need to have well characterized jet fuel samples available for cross comparison with each other and against which surrogate mixture behaviors in fundamental experiments can be compared AFRL provision of a fuel archive repository and samples to community is critical to this and other programs

11 Building Surrogate Models for Aircraft Fuels I. Select minimum number of components that will permit emulating chosen real fuel combustion targets. II. Expand experimental validation database for individual components, component mixtures, and real fuels III. Develop minimized/optimized models for chosen targets and operating parameter ranges IV. Define appropriate targets that surrogate mixtures should emulate V. Cross-compare jet fuel and surrogate mixture target behavior VI. Develop/apply methods to produce smaller dimensional representations of minimized/optimized models Fuel Component Selection Greater understanding Limited understanding Paraffins Iso-paraffins Detailed Model A Cycloparaffins Aromatics Naphthalenes Thermodynamic/Transport/Reaction-Rate Parameter Determination Density Ignition criteria Viscosity C/H Ratio Heat Release Rate Heat Capacity Flame Temperature Sooting Character etc V Detailed Model B Detailed Model C Minimization / Optimization / Validation Kinetic Coupling Comparison IV Jet Fuels Surrogate Composition Formulation (emulation of physical/chemical properties) SURROGATE FUEL VI REDUCED MECHANISMS For specific applications Detailed Model D Validation I III Single Components Experimental Data Ignition (RCM,ST) Speciation (FR, ST) Flames (HP/HT) burning rate ignition II extinction diffusion Soot characteristics (HPDC) Single Components and Mixtures

12 Common Surrogate Mixture Approaches Classical technique in Gasoline/Diesel field pick surrogates and mixtures to replicate specific combustion/performance property such as Octane Number, Cetane Number, etc. Reference mixtures have the wrong C/H ratio in comparison to real fuels! Most have not realized what problems this causes in comparing gasoline and surrogate performance in engines More common technique for jet fuels has been picking classes of organic structure and forming compositions of organic structure similar to the real fuel. How many components from each class? Are all classes necessary? And what about modeling both chemical and physical properties simultaneously (e.g., cetane index and fuel distillation characteristics)?? Combined modeling of physical and chemical characteristics typically requires significantly larger numbers of components; kinetic descriptions become unwieldy as numbers of species and reactions become large quickly with increasing components and validation data needed to develop/validate becomes complex. Is distillation character a prime performance issue in propulsion system performance? Can distillation/vaporization models be empirically separated from chemical kinetic models?

13 Some Exemplar Detailed Mixture Models n-heptane, 2445/546 [Curran et al. 1998] n-decane, cyclohexane, toluene, 1463/188 [Cathonnet et al. 1999] n-decane, benzene or toluene or ethylbenzene, 1085/193 [Lindstedt et al. 2000] n-decane, toluene, 440/84 [Patterson et al. 2000] n-decane, propylcyclohexane, n-propylbenzene, 1592/207 [Dagaut et al. 2002] iso-octane, 3600/860 [Curran et al. 2002] n-decane, n-dodecane, methylcyclohexane, 1330/201 [REI 2002] n-decane, n-propylbenzene, 992/180 [CFD4C 2004] n-octane, n-dodecane, n-hexadecane, xylenes, 5032/221 [Cooke et al. 2005] n-decane, n-propylbenzene, n-propylcyclohexane, 1673/209 [Dagaut et al. 2006] n-decane, n-propylcyclohexane, n-propylbenzene, decene, 1400/550 [CSE 2005] n-heptane, iso-octane, toluene (for gasoline), 1221/469 [Chaos et al. 2007]

14 What are the Major Problems? For nearly all of the surrogate components of interest for large carbon number fuel emulation: The experimental validation data bases for components are limited in terms of pressures, temperatures, and venues relevant to propulsion applications Few data for component mixture interactions in comparison to single components Even fewer comparisons of surrogate mixture data with real fuel behavior at equivalence ratios, pressures, and temperatures found in propulsion applications. What rules can be applied to define what mixture components, compositions, should be used and what are the important fundamental kinetic/transport properties needed to emulate real fuel combustion behavior? Minimized detailed kinetic surrogate mixture models will be too large for CFD applications, so methods to yield smaller dimensional models are important to parametric design applications

15 Surrogate Component Constraints Components and mixture properties should: At least one component to represent each hydrocarbon class Range molecular weights within jet fuel class Permit matching mixture overall C/H ratio of real fuel Envelope behavioral kinetic properties of real fuels in homogenous and transport-coupled experiments Have significant databases to develop/validate chemical kinetic/transport models Other priorities Favor components for which some experimental database and/or modeling development is already available Emphasize hierarchical, comprehensive, first principle model development Generate base comprehensive validation database for components/mixtures and real fuels Apply minimization/optimization methods in model development/validation

16 Initial Combustion Kinetic/Transport Targets Match Surrogate Mixture and Real Fuel: First and second stage autoignition behavior in both dilute and higher fuel concentration conditions Heat release rate Major species evolution histories Laminar flame speed Premixed and non-premixed extinction limit Premixed and non-premixed ignition Sooting under more applied fluid dynamic conditions Develop and test rules for matching kinetic behavior of real fuel and surrogate mixture formulation

17 Kinetically-Limited Processes of Concern (List remains in flux, presently guided by Surrogate Working Group Discussions) Kinetically-limited concern Heat release rates all Application Generic Experiment/ characteristic phi Tinlet (K) P3 (atm) Flow reactors, stirred reactors lean lmt rich lmt Combustion dynamics all ht rlse rates, turbulent lean lmt rich lmt Fuel type effect all sensitivity to all above lean lmt rich lmt NOx (RL) Aeroengine C/H ratio of fuel Extinction SR for premixed Flame stability Augmentor and non-premixed laminar lean lmt rich lmt Soot/Particulate PAH, C2H2 formation, H- Matter (formation) Aeroengine atoms Flame propagation, structure all laminar flame speed lean lmt rich lmt SWG; Paper: AIAA

18 Validation Experiments Princeton University (PU) Variable Pressure Flow Reactor (VPFR) Experiments 2-12 atm, K, dilute mixture conditions Premixed Flame (1-30 atm) and Ignition Experiments (1-8 atm), initial T range, (450 K-1400 K), diluent differences Non-Premixed Flame and Ignition Experiments (coordinated with CWRU) Case Western Reserve University (CWRU) Rapid Compression Machine Experiments, atm, K, low dilution Pre-mixed Flame Experiments, (coordinated with Princeton) Non-Premixed Flame Experiments, <1-6 atm Pennsylvania State University (PSU) Autoignition Experiments, (HPFR) 5-30 atm, K, low dilution mixtures Sooting Characteristics (MGTC), <800K inlet to 20 atm University of Illinois, Chicago (UIC) Single Pulse Shock Tube Experiments, ignition delays and stable species evolution, atm, K

19 Choosing Surrogate Fuel Components Fuel Component Selection Greater understanding Limited understanding Paraffins Iso-paraffins Cycloparaffins Aromatics Naphthalenes I Initial Choices in this program: Paraffins n-decane, n-dodecane (any normal paraffin to C16 ) Iso-cetane Cyclo-Alkanes Methylcyclohexane Alkylated Aromatics n-propyl benzene, 1,3,5 tri-methyl benzene Multi-ring Aromatics 1-methyl naphthalene

20 General Kinetic/Transport Concepts Overall net active radical pool defined by production/consumption rates C/H ratio affects radical and hydrogen production rate, fragments diffusion rate, and the location of reaction zone Radical pool of alkanes, cyclo-alkanes typically suppressed by aromatics. Typical pure component radical pools are ordered as: Alkanes>cyclo alkanes> long chain alkyl aromatics> small chain alkyl aromatics Hydrocarbon mixtures exhibit two stage ignition; first stage, ntc and hot ignition behavior are coupled through kinetic properties and first stage heat release Hydrocarbon mixture sooting strongly related to fuel hydrogen content and aromaticity Hydrocarbon mixture transport phenomena effect related to molecular weight as well as fragment thermal stability

21 Auto-ignition Delays of Alkylbenzenes in an RCM 1. toluene; no ntc 2. 1,3,5-TMB; no ntc 3. p-xylene; no ntc 4. m-xylene; no ntc 5. o-xylene; ntc 6. 1,2,3-TMB; ntc 7. ethyltoluene; ntc 8. 1,2,4-TMB; mild ntc? 9. n-propylbenzene; ntc 10. ethylbenzene; ntc 11. n-butylbenzene, ntc. Keep 8-9< Carbon number <14-16, ave.~12 Use alkanes, cycloalkanes in combination to define base net radical level, two stage ignition character, C/H ratio Use at least two aromatics of same molecular weight to adjust two stage autoignition behavior while keeping total aromatic in mixture content constant (aromaticity is sooting and C/H ratio constrained) Small amounts of additional napthalenes to adjust sooting of mixture. From Roubaud et al (2000)

22 Examples of Surrogate Compositions 1300 Y fuel = 0.4 (const.) 1280 fuel mass fraction, Y fuel [ - ] mod. Aachen Surr. Drexel Surr. 2 JP-8 Jet A Utah Surr. Aachen Surr. Surrogate C Surrogate E Surrogate D temperature at ignition, T ign [K] Surrogate mod. Aachen Surrogate Aachen JP-8 Surrogate C Surrogate Drexel 2 Surrogate Utah Surrogate D a 2 [s -1 ] strain rate, a 2 [1/s] Surrogate Compositions Surrogate C: 60% n-dodecane, 20% methylcyclohexane, 20% o-xylene H/C = 1.92 Surrogate D: 50% n-decane, 25% butylcyclohexane, 25% butylbenzene H/C = 1.92 Surrogate E: 34% n-decane, 33% butylcyclohexane, 33% butylbenzene H/C = 1.84 Aachen Surrogate: 80% n-decane, 20% trimethylbenzene, H/C = 1.99 Modified Aachen Surrogate: 80% n-dodecane, 20% trimethylbenzene, H/C = 1.97 Drexel Surrogate 2: 43% n-dodecane, 27% iso-cetane, 15% methylcyclohexane, 15% 1- methylnaphthalene, H/C = 1.87 Utah Surrogate: 30% n-dodecane, 20% tetradecane, 10% iso-cetane, 20% methylcyclohexane, 15% o-xylene, 5% tetraline, H/C = 1.93 Taken from Colket et al. (2006); Data contributed by Hummer and Seshadri

23 Building Surrogate Mixture Models Will require close collaboration among all Use existing hierarchical and computational tools to develop detailed models Use minimization/optimization methods combined with path/elementary and feature sensitivity/csp methodologies to develop component and component-mixture validated detailed models Apply these methods to optimize coupling of individual component models Apply group theory and higher order methods to supply missing thermochemistry and rate data. Close collaborations with other laboratories working on thermochemistry, physical property, elementary kinetic rate formulations, mechanism insights More validation data on components than can be generated by this MURI are important in expanding range of pressure, temperature, and fuel concentration (elementary kinetic experiments) Fuel Component Selection Greater understanding Limited understanding Paraffins Iso-paraffins Cycloparaffins Aromatics Naphthalenes Thermodynamic/Transport/Reaction-Rate Parameter Determination Detailed Model A Detailed Model B Detailed Model C Minimization / Optimization / Validation Kinetic Coupling Detailed Model D

24 Project Milestones

25 Surrogate Model Development Procedures Detailed Model A Detailed Model B Detailed Model C Detailed Model D III Minimization / Optimization / Validation Density Ignition criteria Viscosity C/H Ratio Heat Release Rate Heat Capacity Flame Temperature Sooting Character etc V Kinetic Coupling Comparison IV Jet Fuels Surrogate Composition Formulation (emulation of physical/chemical properties) Single Components Experimental Data Ignition (RCM,ST) Speciation (FR, ST) Flames (HP/HT) burning rate ignition II extinction diffusion Soot characteristics (HPDC) SURROGATE FUEL Single Components and Mixtures VI Validation REDUCED MECHANISMS For specific applications

26 MURI Advisory Committee (present) Tim Edwards, AFRL John Farrell, Exxon-Mobil Catalin Fotache, UTRC Hukam Mongia, GE Aviation Bill Pitz, LLNL Wing Tsang, NIST (Gaithersburg)