Skeletal reaction model generation, uncertainty quantification and minimization: Combustion of butane

被引:39
作者
Xin, Yuxuan [1 ]
Sheen, David A. [2 ]
Wang, Hai [3 ]
Law, Chung K. [1 ]
机构
[1] Princeton Univ, Dept Mech & Aerosp Engn, Princeton, NJ 08544 USA
[2] NIST, Div Chem Sci, Gaithersburg, MD 20899 USA
[3] Stanford Univ, Dept Mech Engn, Stanford, CA 94305 USA
关键词
Model reduction; Model optimization; Uncertainty quantification; CHEMICAL KINETIC MECHANISMS; REDUCED REACTION-MECHANISMS; DIRECTED RELATION GRAPH; SENSITIVITY-ANALYSIS; ARRHENIUS PARAMETERS; METHANE OXIDATION; REDUCTION; OPTIMIZATION; SYSTEMS; FLAME;
D O I
10.1016/j.combustflame.2014.07.018
中图分类号
O414.1 [热力学];
学科分类号
摘要
Skeletal reaction models for n-butane and iso-butane combustion are derived from a detailed chemistry model through directed relation graph (DRG) and DRG-aided sensitivity analysis (DRGASA) methods. It is shown that the accuracy of the reduced models can be improved by optimization through the method of uncertainty minimization by polynomial chaos expansion (MUM-PCE). The dependence of model uncertainty on the model size is also investigated by exploring skeletal models containing different number of species. It is shown that the dependence of model uncertainty is subject to the completeness of the model. In principle, for a specific simulation the uncertainty of a complete model, which includes all reactions important to its prediction, is convergent with respect to the model size, while the uncertainty calculated with an incomplete model may display unpredictable correlation with the model size. (C) 2014 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
引用
收藏
页码:3031 / 3039
页数:9
相关论文
共 62 条
[1]   Optimally-reduced kinetic models: reaction elimination in large-scale kinetic mechanisms [J].
Bhattacharjee, B ;
Schwer, DA ;
Barton, PI ;
Green, WH .
COMBUSTION AND FLAME, 2003, 135 (03) :191-208
[2]   VODE - A VARIABLE-COEFFICIENT ODE SOLVER [J].
BROWN, PN ;
BYRNE, GD ;
HINDMARSH, AC .
SIAM JOURNAL ON SCIENTIFIC AND STATISTICAL COMPUTING, 1989, 10 (05) :1038-1051
[4]   Global Sensitivity Analysis of Chemical-Kinetic Reaction Mechanisms: Construction and Deconstruction of the Probability Density Function [J].
Davis, Michael J. ;
Skodje, Rex T. ;
Tomlin, Alison S. .
JOURNAL OF PHYSICAL CHEMISTRY A, 2011, 115 (09) :1556-1578
[5]   A new approach to response surface development for detailed gas-phase and surface reaction kinetic model optimization [J].
Davis, SG ;
Mhadeshwar, AB ;
Vlachos, DG ;
Wang, H .
INTERNATIONAL JOURNAL OF CHEMICAL KINETICS, 2004, 36 (02) :94-106
[6]   SYSTEMATIC OPTIMIZATION OF A DETAILED KINETIC-MODEL USING A METHANE IGNITION EXAMPLE [J].
FRENKLACH, M .
COMBUSTION AND FLAME, 1984, 58 (01) :69-72
[7]   OPTIMIZATION AND ANALYSIS OF LARGE CHEMICAL KINETIC MECHANISMS USING THE SOLUTION MAPPING METHOD - COMBUSTION OF METHANE [J].
FRENKLACH, M ;
WANG, H ;
RABINOWITZ, MJ .
PROGRESS IN ENERGY AND COMBUSTION SCIENCE, 1992, 18 (01) :47-73
[8]  
Frenklach M., 1991, Numerical Approaches to Combustion Modeling, P129
[9]   Uncertainty propagation in the derivation of phenomenological rate coefficients from theory: A case study of n-propyl radical oxidation [J].
Goldsmith, C. Franklin ;
Tomlin, Alison S. ;
Klippenstein, Stephen J. .
PROCEEDINGS OF THE COMBUSTION INSTITUTE, 2013, 34 :177-185
[10]  
Kee R., 1986, PREMIX AFORTRAN PROG