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

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

Research output: Contribution to journalArticle

24 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)3031-3039
Number of pages9
JournalCombustion and Flame
Volume161
Issue number12
DOIs
StatePublished - Dec 1 2014

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)
  • Fuel Technology
  • Energy Engineering and Power Technology
  • Physics and Astronomy(all)

Keywords

  • Model optimization
  • Model reduction
  • Uncertainty quantification

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