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, AFOSRMURI 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

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

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

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

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 efforts- review & discussions summarized in:

• Colket, M., et al., “Development of an Experimental Database and Kinetic Models for Surrogate Jet Fuels”, AIAA Paper 2007-0770, January 2007

• Farrell, J. T., et al., "Development of an Experimental Database and Chemical Kinetic Models for Surrogate Diesel Fuels", SAE Paper 2007-01-0201, April 2007

• Pitz, W. J., et al., "Development of an Experimental Database and Chemical Kinetic Models for Surrogate Gasoline Fuels", SAE Paper 2007-01-0175, April 2007

• CFD4C: Hohmann, Uslu, MTU Aero Engines (2001-2003)• n-Heptane/Iso-Octane/Toluene Surrogate Mixtures for Emulating Gasoline

– “A Surrogate Mixture Study: Partially Reduced “Skeletal” and Semi-Empirical Kinetic Models for Gasoline” (2000-2002) GM Contract Number TCS07695 (Princeton University)

– “Fuel Chemistry Models for Simulating Gasoline Kinetics in Internal Combustion Engine Applications” (2002-2005) Honda Research Agreement 1504286 (Princeton University)

Real Fuel Chemical Component Characteristics

Boiling point range, F

Hydrocarbon Class Distribution in Jet-A (wt.%)

Naphthalenes2%

Alkylbenzenes18%

n-Paraffins28%

Cycloparaffins20%

Misc.2%ND

1%

i-Paraffins29%

Paper: AIAA-2007-770

How “Variable” are Real Jet Fuel Properties?

Fraction of delivered JP-8 fuels (in 2005) with specified aromatic concentration

Paper: AIAA-2007-770

While an “average” jet fuel can be envisioned, there are large variations from the average.

Table 2. Composition results for 55 “world survey” fuels9.* World survey

average, vol % Composite Jet A blend

paraffins (n- + i-) 58.78 55.2 Monocycloparaffins 10.89 17.2

Dicycloparaffins 9.25 7.8 Tricycloparaffins 1.08 0.6

alkyl benzenes 13.36 12.7 indans+tetralins 4.9 4.9

Naphthalene 0.13 <0.2 substituted naphthalenes 1.55 1.3

http://www.desc.dla.mil/DCM/Files/2005PQISreport.pdfPetroleum Quality Information System

JP-8 Properties (2005)

Petroleum Quality Information System

JP-8 Properties (2005)

Petroleum Quality Information System

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

Paraffins Iso-paraffins Cycloparaffins Aromatics Naphthalenes

Fuel Component Selection Limited understanding

Detailed Model B

Detailed Model C

Detailed Model D

Detailed Model A

Thermodynamic/Transport/Reaction-Rate Parameter Determination

Experimental Data• Ignition (RCM,ST) • Speciation (FR, ST) • Flames (HP/HT)

burning rate ignition extinction diffusion

• Soot characteristics (HPDC)

Minimization / Optimization / Validation

Greater understanding

Kinetic Coupling

Density Ignition criteriaViscosity C/H Ratio

Heat Release Rate Heat Capacity

Flame Temperature Sooting Character

etc …

Surrogate Composition Formulation(emulation of physical/chemical properties)

JetFuels

SURROGATE FUEL

Validation

SingleComponents

Single Componentsand

Mixtures

Comparison

REDUCED MECHANISMSFor specific applications

II

III

I

VI

V

IV

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

Building Surrogate Models for Aircraft Fuels

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?

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]

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

Surrogate Component ConstraintsComponents 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

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

Kinetically-Limited Processes of Concern (List remains in flux, presently guided by Surrogate Working Group Discussions)

Kinetically-limited concern Application

Generic Experiment/ characteristic

Heat release rates allFlow reactors, stirred reactors lean lmt rich lmt 350 900 0.3 35

Combustion dynamics all ht rlse rates, turbulent lean lmt rich lmt 350 1100 0.3 35

Fuel type effect all sensitivity to all above lean lmt rich lmtNOx (RL) Aeroengine C/H ratio of fuel 450 900 4 35

Flame stability AugmentorExtinction SR for premixed and non-premixed laminar lean lmt rich lmt 350 1100 0.3 6

Soot/Particulate Matter (formation) Aeroengine

PAH, C2H2 formation, H-atoms 1.5 3 600 900 10 35

Flame propagation, structure all laminar flame speed lean lmt rich lmt 350 1100 0.3 35

phi Tinlet (K) P3 (atm)

SWG; Paper: AIAA-2007-770

Validation Experiments• Princeton University (PU)

– Variable Pressure Flow Reactor (VPFR) Experiments 2-12 atm, 550-950 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, 10-50 atm, 600-1100 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, 600-950 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, 10-40 atm, 800-2500 K

Choosing Surrogate Fuel Components

Paraffins Iso-paraffins Cycloparaffins Aromatics Naphthalenes

Fuel Component Selection Limited understanding Greater understanding 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

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

Auto-ignition Delays of Alkylbenzenes in an RCM1. toluene; no ntc2. 1,3,5-TMB; no ntc3. p-xylene; no ntc4. m-xylene; no ntc5. o-xylene; ntc6. 1,2,3-TMB; ntc7. ethyltoluene; ntc8. 1,2,4-TMB; mild ntc?9. n-propylbenzene; ntc10. ethylbenzene; ntc11. n-butylbenzene, ntc.

From Roubaud et al (2000)

• 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.

Examples of Surrogate Compositionsfu

el m

ass

fract

ion,

Yfu

el [

- ]

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

a2 [s-1]0 50 100 150 200 250 300 350 400 450 500

mod. Aachen Surr. Drexel Surr. 2 JP-8 Jet A Utah Surr. Aachen Surr. Surrogate C Surrogate E Surrogate D

tem

pera

ture

at i

gniti

on, T

ign

[K]

1180

1200

1220

1240

1260

1280

1300

strain rate, a2 [1/s]200 300 400 500 600 700 800 900

Yfuel = 0.4 (const.)

Surrogate mod. Aachen Surrogate Aachen JP-8 Surrogate C Surrogate Drexel 2 Surrogate Utah Surrogate D

Surrogate Compositions

Surrogate C: 60% n-dodecane, 20% methylcyclohexane, 20% o-xylene H/C = 1.92Surrogate D: 50% n-decane, 25% butylcyclohexane, 25% butylbenzene H/C = 1.92Surrogate E: 34% n-decane, 33% butylcyclohexane, 33% butylbenzene H/C = 1.84Aachen Surrogate: 80% n-decane, 20% trimethylbenzene, H/C = 1.99Modified Aachen Surrogate: 80% n-dodecane, 20% trimethylbenzene, H/C = 1.97Drexel Surrogate 2: 43% n-dodecane, 27% iso-cetane, 15% methylcyclohexane, 15% 1- methylnaphthalene, H/C = 1.87Utah Surrogate: 30% n-dodecane, 20% tetradecane, 10% iso-cetane, 20% methylcyclohexane, 15% o-xylene, 5% tetraline,

H/C = 1.93Taken from Colket et al. (2006); Data contributed by Hummer and Seshadri

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)

Paraffins Iso-paraffins Cycloparaffins Aromatics Naphthalenes

Fuel Component Selection Limited understanding

Detailed Model B

Detailed Model C

Detailed Model D

Detailed Model A

Thermodynamic/Transport/Reaction-Rate Parameter Determination

Minimization / Optimization / Validation

Greater understanding

Kinetic Coupling

Project Milestones

Surrogate Model Development ProceduresDetailed Model B

Detailed Model C

Detailed Model D

Detailed Model A

Experimental Data• Ignition (RCM,ST) • Speciation (FR, ST) • Flames (HP/HT)

burning rate ignition extinction diffusion

• Soot characteristics (HPDC)

Minimization / Optimization / Validation

Kinetic Coupling

Density Ignition criteriaViscosity C/H Ratio

Heat Release Rate Heat Capacity

Flame Temperature Sooting Character

etc …

Surrogate Composition Formulation (emulation of physical/chemical properties)

Jet Fuels

SURROGATE FUEL

Validation

SingleComponents

Single Componentsand

Mixtures

Comparison

REDUCED MECHANISMSFor specific applications

II

III

VI

V

IV

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)