Chemical kinetic model reduction through species-targeted global sensitivity analysis (STGSA)

Shengqiang Lin, Ming Xie, Jiaxing Wang, Wenkai Liang, Chung K. Law, Weixing Zhou, Bin Yang

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


The uncertainty of the rate coefficients of elementary reactions in detailed chemical kinetic mechanisms can affect the predicted species concentrations and global properties. The size of reduced mechanisms generated by reduction methods, such as directed relation graph (DRG), can also be greatly affected by the uncertainties in the rate coefficients, because these methods eliminate species by comparing contributions of the production rates of important species from other species. In order to obtain the optimum reduced mechanism in the uncertainty domain of reaction rate parameters, the species-targeted global sensitivity analysis (STGSA) method is proposed to measure the importance of species in kinetic mechanisms and to simplify them by considering the input uncertainties. The demonstrations are performed for the ethylene oxidation mechanism using the USC-Mech II with 111 species and the n-heptane oxidation mechanism using the JetSurf (version 1.0) with 194 species. It is found that STGSA can accurately identify the redundant global species and generate more compact reduced mechanisms compared with the DRG-based methods, resulting in a 33-species reduced mechanism for ethylene oxidation and a 37-species reduced mechanism for n-heptane oxidation. These reduced mechanisms show accurate predictions for the ignition delay times and laminar flame speeds over a wide range of operating conditions.

Original languageEnglish (US)
Pages (from-to)73-82
Number of pages10
JournalCombustion and Flame
StatePublished - Feb 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • General Chemical Engineering
  • Fuel Technology
  • Energy Engineering and Power Technology
  • General Physics and Astronomy


  • DRG
  • Mechanism reduction
  • Sobol sensitivity indices
  • Uncertainty analysis


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