Monte Carlo simulation of polydisperse particle deposition and coagulation dynamics in enclosed chambers

Hongmei Liu, Wei Jiang, Wenming Liu, Xuedong Liu, Shuyuan Liu, Tat Leung Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)


A novel Monte Carlo method is proposed to improve the computational accuracy and efficiency of Monte Carlo methods in examining the polydisperse micro- and nano-particle dynamics including deposition and coagulation processes in enclosed or vacuum chambers. In the original differentially weighted Monte Carlo (DWMC) method, the coagulation and deposition events are both treated by stochastic approaches. In the present study, the deposition event is solved by a deterministic method where a proportion of the deposited real particles inside a simulated particle is determined by a probability related to the deposition kernel. Furthermore, the operator splitting method is adopted to couple the stochastic and deterministic processes. This method is verified against both analytical solutions and experimental results for particle deposition and coagulation dynamics. The particle size distributions are obtained and the results exhibit excellent accordance with the corresponding analytical solutions and experimental results. Compared with the original DWMC method, the simulation results show that the proposed Monte Carlo method can obtain very favorable improvement in both computational accuracy and efficiency.

Original languageEnglish
Article number109952
Publication statusPublished - Feb 2021


  • Coagulation
  • Deposition
  • Monte Carlo simulation
  • Paper ash particles
  • Particle size distribution
  • Sodium chloride aerosols

ASJC Scopus subject areas

  • Instrumentation
  • Condensed Matter Physics
  • Surfaces, Coatings and Films


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