Reduced Chemistry for a Gasoline Surrogate Valid at Engine-Relevant Conditions

Niemeyer, Kyle E.; Sung, Chih-Jen

doi:10.1021/ef5022126

Cited by 31 publications

(45 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The falloff blending factor F i used in Eq. (20) is determined based on one of three representations: the Lindemann [50], Troe [51], and SRI [52] falloff approaches…”

Section: Falloff Reactionsmentioning

confidence: 99%

pyJac: Analytical Jacobian generator for chemical kinetics

Niemeyer

Curtis

Sung

2017

Computer Physics Communications

Self Cite

View full text Add to dashboard Cite

Accurate simulations of combustion phenomena require the use of detailed chemical kinetics in order to capture limit phenomena such as ignition and extinction as well as predict pollutant formation. However, the chemical kinetic models for hydrocarbon fuels of practical interest typically have large numbers of species and reactions and exhibit high levels of mathematical stiffness in the governing differential equations, particularly for larger fuel molecules. In order to integrate the stiff equations governing chemical kinetics, generally reactive-flow simulations rely on implicit algorithms that require frequent Jacobian matrix evaluations. Some in situ and a posteriori computational diagnostics methods also require accurate Jacobian matrices, including computational singular perturbation and chemical explosive mode analysis. Typically, finite differences numerically approximate these, but for larger chemical kinetic models this poses significant computational demands since the number of chemical source term evaluations scales with the square of species count. Furthermore, existing analytical Jacobian tools do not optimize evaluations or support emerging SIMD processors such as GPUs. Here we introduce pyJac, a Python-based open-source program that generates analytical Jacobian matrices for use in chemical kinetics modeling and analysis. In addition to producing the necessary customized source code for evaluating reaction rates (including all modern reaction rate formulations), the chemical source terms, and the Jacobian matrix, pyJac uses an optimized evaluation order to minimize computational and memory operations. As a demonstration, we first establish the correctness of the Jacobian matrices for kinetic models of hydrogen, methane, ethylene, and isopentanol oxidation (number of species ranging 13-360) by showing agreement within 0.001 % of matrices obtained via automatic differentiation. We then demonstrate the performance achievable on CPUs and GPUs using pyJac via matrix evaluation timing comparisons; the routines produced by pyJac outperformed first-order finite differences by 3-7.5 times and the existing analytical Jacobian software TChem by 1.1-2.2 times on a single-threaded basis. It is noted that TChem is not thread-safe, while pyJac is easily parallelized, and hence can greatly outperform TChem on multicore CPUs. The Jacobian matrix generator we describe here will be useful for reducing the cost of integrating chemical source terms with implicit algorithms in particular and algorithms that require an accurate Jacobian matrix in general. Furthermore, the open-source release of the program and Python-based implementation will enable wide * Corresponding author

show abstract

“…The falloff blending factor F i used in Eq. (20) is determined based on one of three representations: the Lindemann [50], Troe [51], and SRI [52] falloff approaches…”

Section: Falloff Reactionsmentioning

confidence: 99%

pyJac: Analytical Jacobian generator for chemical kinetics

Niemeyer

Curtis

Sung

2017

Computer Physics Communications

Self Cite

View full text Add to dashboard Cite

show abstract

“…CSP analysis (Goussis & Lam, ; Lam, ; Lam & Goussis, ; ) was applied to the chemical kinetic system represented by equations to identify candidate species for QSS approximations following the approach outlined by Lu and Law (, ) and Niemeyer and Sung (). To perform the CSP analysis, the reaction rate equations from equations and were first written as a zero‐dimensional (i.e., only time‐dependent) system given by

\frac{normald boldc}{normald t} = boldS false(boldc false) \Rightarrow \frac{normald boldS}{normald t} = boldJ boldS,

where J = ∂ S / ∂ c is the Jacobian matrix.…”

Section: Description Of Numerical Simulationsmentioning

confidence: 99%

“…Using the eigenvalues from equation , the system dynamics were separated into fast and slow subspaces, where the evolution of the modes f in each subspace is given from equation as (Niemeyer & Sung, )

\frac{d}{normald t} ([], \begin{matrix} array {boldf}^{fast} \\ array {boldf}^{slow} \end{matrix}) = ([], \begin{matrix} array Λ^{fast} & array \\ array & array Λ^{slow} \end{matrix}) ([], \begin{matrix} array {boldf}^{fast} \\ array {boldf}^{slow} \end{matrix}) .

…”

Section: Description Of Numerical Simulationsmentioning

confidence: 99%

See 1 more Smart Citation

Effects of Langmuir Turbulence on Upper Ocean Carbonate Chemistry

Smith

Hamlington

Niemeyer

et al. 2018

J Adv Model Earth Syst

View full text Add to dashboard Cite

Effects of wave‐driven Langmuir turbulence on the air‐sea flux of carbon dioxide (CO2) are examined using large eddy simulations featuring actively reacting carbonate chemistry in the ocean mixed layer at small scales. Four strengths of Langmuir turbulence are examined with three types of carbonate chemistry: time‐dependent chemistry, instantaneous equilibrium chemistry, and no reactions. The time‐dependent model is obtained by reducing a detailed eight‐species chemical mechanism using computational singular perturbation analysis, resulting in a quasi steady state approximation for hydrogen ion (H+); that is, fixed pH. The reduced mechanism is then integrated in two half‐time steps before and after the advection solve using a Runge‐Kutta‐Chebyshev scheme that is robust for stiff systems of differential equations. The simulations show that as the strength of Langmuir turbulence increases, CO2 fluxes are enhanced by rapid overturning of the near‐surface layer, which rivals the removal rate of CO2 by time‐dependent reactions. Equilibrium chemistry and nonreactive models are found to bring more and less carbon, respectively, into the ocean as compared to the more realistic time‐dependent model. These results have implications for Earth system models that either neglect Langmuir turbulence or use equilibrium, instead of time‐dependent, chemical mechanisms.

show abstract

“…To compare the engine performance of butanol isomers with that of conventional gasoline, a skeletal mechanism 46 proposed for a gasoline surrogate 63,64 was used in our engine simulation for the same conditions used in the butanol isomer simulations. consumption of n-and isobutanol closest to that of gasoline, although in different orders (n-butanol and isobutanol are consumed first for the Sarathy and Merchant mechanism, respectively).…”

Section: Validation Of Skeletal Mechanismsmentioning

confidence: 99%

Reduced Chemistry for Butanol Isomers at Engine-Relevant Conditions

et al. 2016

Self Cite

View full text Add to dashboard Cite

Butanol has received significant research attention as the second-generation biofuel in the past few years. In the present study, skeletal mechanisms for four butanol isomers were generated from two widely accepted, well-validated detailed chemical kinetic models for the butanol isomers. The detailed models were reduced using a two-stage approach consisting of the directed relation graph with error propagation and sensitivity analysis. During the reduction process, issues encountered with pressure-dependent reactions formulated using the logarithmic pressure interpolation approach were discussed, with recommendations made to avoid ambiguity in its future implementation in mechanism development. The performances of the skeletal mechanisms generated here were compared with those of detailed mechanisms in simulations of autoignition delay times, laminar flame speeds, and perfectly stirred reactor temperature response curves and extinction residence times, over a wide range of pressures, temperatures, 1 arXiv:1706.02043v1 [physics.chem-ph] 7 Jun 2017 and equivalence ratios. Good agreement was observed between the detailed and skeletal mechanisms, demonstrating the adequacy of the resulting reduced chemistry for all the butanol isomers in predicting global combustion phenomena. The skeletal mechanisms also closely predicted the time-histories of fuel mass fractions in homogeneous compression-ignition engine simulations. Finally, the performances of the butanol isomers were compared with that of a gasoline surrogate with an anti-knock index of 87 in a homogeneous compression-ignition engine simulation. The gasoline surrogate consumed faster than any of the butanol isomers, and tert-butanol had the slowest fuel consumption rate; n-butanol and isobutanol came closest to matching the gasoline, but the two literature chemical kinetic models predicted different orderings.

show abstract

Reduced Chemistry for a Gasoline Surrogate Valid at Engine-Relevant Conditions

Cited by 31 publications

References 46 publications

pyJac: Analytical Jacobian generator for chemical kinetics

pyJac: Analytical Jacobian generator for chemical kinetics

Effects of Langmuir Turbulence on Upper Ocean Carbonate Chemistry

Reduced Chemistry for Butanol Isomers at Engine-Relevant Conditions

Contact Info

Product

Resources

About