Diffusion coefficient reduction through species bundling

Tianfeng Lu, Chung K. Law

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

A systematic approach was developed for reducing the size as well as the computational cost in the evaluation of diffusion coefficients for mechanisms with mixture-averaged diffusivities by bundling species with similar diffusivities into groups. The systematic reduction was formulated as an integer programming problem and solved efficiently with a greedy algorithm. Reduction error was controlled by a user-specified threshold value, and the algorithm was fully automated. The method was then applied to a 20-species reduced mechanism for ethylene and a 188-species skeletal mechanism for n-heptane. Nine bundled species groups were identified for ethylene, while reduced models with 19, 9, and 3 diffusive species groups were developed for n-heptane in ascending order of reduction errors. Validations of the reduced diffusion models obtained with about 10% reduction error in premixed and nonpremixed flames show good agreement with the detailed model, and the worst case reduction error is close to the user-specified level of 10%. Significant reduction in CPU time was observed in the evaluation of the diffusion terms, while the overall time saving is simulation-dependent due to the existence of other terms, such as the chemical source term, that are not affected by the reduction in the diffusion term.

Original languageEnglish (US)
Pages (from-to)117-126
Number of pages10
JournalCombustion and Flame
Volume148
Issue number3
DOIs
StatePublished - Feb 2007

All Science Journal Classification (ASJC) codes

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

Keywords

  • Diffusion coefficient reduction
  • Mechanism reduction
  • Species bundling

Fingerprint Dive into the research topics of 'Diffusion coefficient reduction through species bundling'. Together they form a unique fingerprint.

Cite this