The Influence of Chemical Mechanisms on PDF Calculations of Nonpremixed Piloted Jet Flames. Renfeng Richard Cao and Stephen B. Pope Sibley School of the Mechanical and Aerospace Engineering Cornell University, Ithaca, NY, 14853 - PowerPoint PPT Presentation
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1 Dfdfdsa The Influence of Chemical Mechanisms on PDF Calculations of Nonpremixed Piloted Jet Flames Renfeng Richard Cao and Stephen B. Pope Renfeng Richard Cao and Stephen B. Pope Sibley School of the Mechanical and Aerospace Sibley School of the Mechanical and Aerospace Engineering Engineering Cornell University, Ithaca, NY, 14853 Cornell University, Ithaca, NY, 14853 This work is supported by Air Force Office of Scientific Research under This work is supported by Air Force Office of Scientific Research under grant No. F-49620-00-1-0171 and the Department of Energy under Grant grant No. F-49620-00-1-0171 and the Department of Energy under Grant No. DE-FG02-90ER. No. DE-FG02-90ER.
Transcript
11Dfdfdsa
The Influence of Chemical Mechanisms on PDF Calculations
of Nonpremixed Piloted Jet Flames
Renfeng Richard Cao and Stephen B. PopeRenfeng Richard Cao and Stephen B. Pope
Sibley School of the Mechanical and Aerospace EngineeringSibley School of the Mechanical and Aerospace EngineeringCornell University, Ithaca, NY, 14853Cornell University, Ithaca, NY, 14853
This work is supported by Air Force Office of Scientific Research under grant No. F-This work is supported by Air Force Office of Scientific Research under grant No. F-49620-00-1-0171 and the Department of Energy under Grant No. DE-FG02-90ER.49620-00-1-0171 and the Department of Energy under Grant No. DE-FG02-90ER.
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ContentsContents IntroductionIntroduction
About turbulent combustionAbout turbulent combustion Experimental operating conditionsExperimental operating conditions Calculations on piloted jet flamesCalculations on piloted jet flames
Joint PDF methodJoint PDF method Tested mechanismsTested mechanisms Numerical issuesNumerical issues Comparison of different mechanismsComparison of different mechanisms Sensitivity to reaction rates and the mixing model Sensitivity to reaction rates and the mixing model
Turbulent combustion is importantTurbulent combustion is important Research on turbulent combustion is difficultResearch on turbulent combustion is difficult Simplified view of chemistry has been used for many Simplified view of chemistry has been used for many
years, which often show unacceptable limitations, such years, which often show unacceptable limitations, such as the prediction of pollutant emissions or of stability as the prediction of pollutant emissions or of stability limitslimits
With the rapid increase of computer power and the With the rapid increase of computer power and the development of efficient algorithms, turbulent development of efficient algorithms, turbulent combustion simulations with detailed chemistry have combustion simulations with detailed chemistry have become more and more feasible in recent years. become more and more feasible in recent years.
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Why piloted jet flamesWhy piloted jet flames
Starner S.H. and R.W. Bilger, 1985Starner S.H. and R.W. Bilger, 1985 Masri A.R., Bilger R.W. and Dibble R.W., 1988Masri A.R., Bilger R.W. and Dibble R.W., 1988 Masri A.R., Dibble R.W. and Barlow R.S., 1996Masri A.R., Dibble R.W. and Barlow R.S., 1996 Barlow, R.S., and J.H. Frank, 1998Barlow, R.S., and J.H. Frank, 1998 A.N. Karpetis and R.S. Barlow, 2002A.N. Karpetis and R.S. Barlow, 2002
•Creating strong turbulence-chemistry interactions in a stable flame with relatively simple fluid mechanics and turbulence structure
•Demonstration of local extinction and reignition in these flames
The current workThe current work Six detailed and reduced mechanisms: Six detailed and reduced mechanisms: GRI3.0 (53 species, 325 GRI3.0 (53 species, 325
reactions), GRI2.11, ARM2, S5G211, Skeletal, Smookereactions), GRI2.11, ARM2, S5G211, Skeletal, Smooke Tested flame: Tested flame: Flame FFlame F (and D and E) (and D and E) AutoignitionAutoignition Laminar opposed-flow diffusion flame (OPPDIF)Laminar opposed-flow diffusion flame (OPPDIF)
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Joint PDF methodJoint PDF method TURBULENT COMBUSTION MODEL
Joint velocity-turbulent frequency-composition PDF methodJoint velocity-turbulent frequency-composition PDF method Software: HYB2D
Developed by Muradoglu, Caughey, Pope, Liu and CaoDeveloped by Muradoglu, Caughey, Pope, Liu and Cao MIXING MODEL
Implemented using the experimental dataImplemented using the experimental data Numerical accuracyNumerical accuracy
Statistical identical results of parallel and serial Statistical identical results of parallel and serial calculationscalculations
Numerical parameters that affect the accuracy of Numerical parameters that affect the accuracy of the resultsthe results
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Convergence with respect to the ISAT error Convergence with respect to the ISAT error tolerancetolerance
ISAT error tolerance is set to 2ISAT error tolerance is set to 2××1010–5–5
Less than 2% error for the test caseLess than 2% error for the test case
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Numerical AccuracyNumerical Accuracy Statistical identical results of parallel and serial Statistical identical results of parallel and serial
calculationscalculations ISAT (In Situ Adaptive Tabulation) error ISAT (In Situ Adaptive Tabulation) error
tolerance (2tolerance (2××1010–5–5)) The number of cells in the domain ( 96 by 96 )The number of cells in the domain ( 96 by 96 ) The number of particles per cell (100)The number of particles per cell (100) The coefficients of the numerical viscosity (The coefficients of the numerical viscosity (22=0.25 =0.25
, , 44=2.0=2.0 ) ) The coefficients of time averaging (>2000 particle The coefficients of time averaging (>2000 particle
time steps with time averaging factor >600)time steps with time averaging factor >600)
•Generally, < 2% error for mean major species, < 5% error in the minor species
•Significant statistical fluctuations can be observed in conditional rms’s downstream (which is not important for the current work).
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Results and discussionsResults and discussions IntroductionIntroduction
Experimental operating conditionsExperimental operating conditions Calculations on piloted jet flamesCalculations on piloted jet flames
Joint PDF methodJoint PDF method Tested mechanismsTested mechanisms Calculation domain and boundary conditionsCalculation domain and boundary conditions Numerical parametersNumerical parameters
Results and discussionResults and discussion Calculation of the velocity field and mixture fractionCalculation of the velocity field and mixture fraction Comparison of different mechanismsComparison of different mechanisms
(1) Joint PDF calculations(1) Joint PDF calculations(2) Autoignition test(2) Autoignition test(3) OPPDIF(3) OPPDIF
Sensitivity to the chemical reaction ratesSensitivity to the chemical reaction rates Sensitivity to the mixing model constant CSensitivity to the mixing model constant Cφφ
ConclusionsConclusions
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Velocity field
Blue circles: measurements
[Schneider et al.]; Red lines, PDF
calculations using the GRI3.0 and the EMST mixing model with Cφ=1.5
The calculated velocity The calculated velocity profiles agree with the profiles agree with the experimental data experimental data reasonably wellreasonably well
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Mixture fraction
Blue circles: measurements [Barlow et al.];
Lines, PDF calculations using the GRI3.0 and the EMST mixing model
Red lines: Cφ=1.5
Green lines: Cφ=2.0
Increasing Increasing CCφ φ doesdoes not not
always result in always result in decreasing of rms mixture decreasing of rms mixture fraction at all locationsfraction at all locations
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Effect of pilot temperature and comparison with previous calculations (z/D=15)
z/D=15: most significant local extinction; Very sensitive to Tp
Red solid:
HYB2D Tp=1880 K
Blue dash:
PDF2DV Tp=1880K
Green dash dotted:
PDF2DV Tp=1860 K
Black dots: measured
HYB2D Tp=1880 K
PDF2DV Tp=1860 K
PDF2DV Tp=1880K
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Comparison of mechanisms with z/D=15Comparison of mechanisms with z/D=15
Smooke: extinguishedS5G211: highest conditional mean
S5G211
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Comparison of mechanisms with autoignition and Comparison of mechanisms with autoignition and flame F (Cflame F (Cφφ=1.5) calculations=1.5) calculations
S5G211: shortest IDT Smooke: longest IDT
S5G211: highest conditional mean T Smooke: extinguished
Flame FFlame FAutoignitionAutoignition
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Comparison of mechanisms with autoignition and Comparison of mechanisms with autoignition and flame F (Cflame F (Cφφ=2.0) calculations=2.0) calculations
S5G211: shortest IDT Smooke: longest IDT
Flame FFlame FAutoignitionAutoignition
S5G211: highest conditional meanSmooke: lowest conditional mean
Sensitivity to the mixing model constant Sensitivity to the mixing model constant CCφφ
C=1.2 C=1.5
C=2.0 C=3.0
•More sensitive to the change when the calculations close to global extinction
Skeletal
ARM2
S5G211
GRI2.11
GRI3.0
Smooke
z/D=15z/D=15
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Maximal temperature against CMaximal temperature against C at at
z/D=15z/D=15
Skeletal
ARM2
S5G211
GRI2.11
GRI3.0
ARM2
S5G211
Skeletal
GRI2.11
GRI3.0 Smooke
Smooke
•Similar tendency for all mechanisms (horizontally shifted)•More sensitive to the change when the calculations close to global extinction
Measured
Measured
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Conclusions (1/2)Conclusions (1/2) The performance of six detailed and reduced mechanisms
has been investigated using the joint PDF calculations of flame F
The large number of numerically-accurate PDF calculations reported here demonstrates that this PDF/ISAT methodology can be effectively applied to turbulent flames using chemical mechanisms with of order 50 species.
For different mechanisms, longer IDTs, smaller extinction strain rate (in OPPDIF), lower conditional mean temperature (in flame F)
Sensitivities of these calculations to the reaction rates and the mixing model constant Cφ has been studied. Generally, the closer to the global extinction, the more sensitive to theses parameters.
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Conclusions (2/2)Conclusions (2/2)
The GRI and ARM mechanisms (GRI2.11, GRI3.0 and ARM2) yield comparable results in agreement with experimental data (except for NO)
As previously observed, GRI3.0 overpredicts NO by a factor of 2
The 5-step mechanism under-predicts local extinction substantially
The Smooke mechanism has longer IDT and over-predicts local extinction
The skeletal mechanism is generally good but it over-predicts CO
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Thanks and questionsThanks and questions
Thank you for your attention!Thank you for your attention!
Open for questions or commentsOpen for questions or comments
