Lagrangian particle tracking with new weighted fraction Monte Carlo method for studying the soot particle size distributions in premixed flames

Xiao Jiang, Tat Leung Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Purpose: The purpose of this paper is to study the soot formation and evolution by using this newly developed Lagrangian particle tracking with weighted fraction Monte Carlo (LPT-WFMC) method. Design/methodology/approach: The weighted soot particles are used in this MC framework and is tracked using Lagrangian approach. A detailed soot model based on the LPT-WFMC method is used to study the soot formation and evolution in ethylene laminar premixed flames. Findings: The LPT-WFMC method is validated by both experimental and numerical results of the direct simulation Monte Carlo (DSMC) and Multi-Monte Carlo (MMC) methods. Compared with DSMC and MMC methods, the stochastic error analysis shows this new LPT-WFMC method could further extend the particle size distributions (PSDs) and improve the accuracy for predicting soot PSDs at larger particle size regime. Originality/value: Compared with conventional weighted particle schemes, the weight distributions in LPT-WFMC method are adjustable by adopting different fraction functions. As a result, the number of numerical soot particles in each size interval could be also adjustable. The stochastic error of PSDs in larger particle size regime can also be minimized by increasing the number of numerical soot particles at larger size interval.

Original languageEnglish
Pages (from-to)1961-1998
Number of pages38
JournalInternational Journal of Numerical Methods for Heat and Fluid Flow
Volume32
Issue number6
DOIs
Publication statusPublished - 16 May 2022

Keywords

  • Detailed soot model
  • Lagrangian particle tracking
  • Particle size distribution
  • Stochastic error analysis
  • Weighted fraction Monte-Carlo method

ASJC Scopus subject areas

  • Mechanical Engineering
  • Computer Science Applications
  • Applied Mathematics
  • Energy(all)
  • Chemical Engineering(all)
  • Environmental Science(all)

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