A new dynamic adaptive chemistry reduction method

Xiao Long Gou, Zheng Chen, Wen Ting Sun, Yi Guang Ju

Research output: Contribution to journalArticle

Abstract

A dynamic adaptive chemistry(DAC) is developed based on the path flux analysis(PFA) model reduction approach to increase drastically the computation efficiency of combustion modeling with large, detailed kinetic mechanism. This new method is applied to the simulation of homogeneous ignition and unsteady flame propagation of n-decane/air mixtures. The comparison between results predicted by dynamic adaptive chemistry and those by detailed chemistry shows that this method can accurately reproduce the species time histories and ignition delay times. Compared to the detailed mechanism, there are much smaller numbers of active species and reactions with DAC method. The effects of the mechanism size and criteria of model reduction in path flux analysis are investigated. Results show that the computation efficiency of DAC increases with the size of chemical kinetic mechanisms. This scheme can be used for direct numerical simulations and large eddy simulations with detailed chemical mechanisms to improve the computation efficiency.

Original languageEnglish (US)
Pages (from-to)514-518
Number of pages5
JournalNeiranji Xuebao/Transactions of CSICE (Chinese Society for Internal Combustion Engines)
Volume28
Issue number6
StatePublished - Nov 1 2010

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering

Keywords

  • Detailed chemistry
  • Dynamic adaptive chemistry reduction
  • N-decane

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