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

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.

Automated summary

A novel Monte Carlo method is proposed to improve the computational accuracy and efficiency by using a deterministic method for deposition events and adopting the operator splitting method to couple stochastic and deterministic processes. The method is verified against analytical solutions and experimental results, showing significant improvement in both computational accuracy and efficiency compared to the original DWMC method.