Skeletal Reaction Model Generation, Uncertainty Quantification and Minimization: Combustion of Butane

Published

August 20, 2014

Author(s)

Yuxuan Xin, David Sheen, Hai Wang, Chung K. Law

Abstract

Skeletal reaction models for n-butane and iso-butane combustion are derived from the detailed chemistry model of USC Mech II 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 model. In the case of a complete model, the uncertainty must increase with model size, while an incomplete model may display behavior that is impossible to predict.

Citation

Combustion and Flame

Volume

161

Issue

12

Pub Type

Journals

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DOI Link

Keywords

model reduction, model optimization, uncertainty quantification

Citation

Xin, Y. , Sheen, D. , Wang, H. and Law, C. (2014), Skeletal Reaction Model Generation, Uncertainty Quantification and Minimization: Combustion of Butane, Combustion and Flame, [online], https://doi.org/10.1016/j.combustflame.2014.07.0 (Accessed October 10, 2025)