Application of the view factor model on the particle-in-cell and Monte Carlo collision code

Ruojian Pan, Junxue Ren, Haibin Tang*, Shuai Cao, Juan Li, Zhe Zhang, Jun Zhou, Jinbin Cao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Particle-in-cell and Monte Carlo collision (PIC-MCC) has been widely adopted as a simulation method for electric propulsion. However, neutral atoms move much more slowly than other species, which can cause a serious reduction in simulation speed. In this work, we investigate the view factor model in combination with the PIC-MCC method and propose a method for simulating three-dimensional neutral atoms. The accuracy of the PIC-MCC method can be significantly improved by updating the neutral distribution periodically. We compare the computational results with the fixed-neutral PIC-MCC model of the miniature ring-cusp discharge experiment at the University of California, Los Angeles (UCLA). The plasma distribution and potential distribution of the simulation match well with the UCLA experimental data. Compared with the fixed-neutral model, the view factor model increases the simulation time by only 33% while it improves the distribution accuracy of neutrals, plasma density, and electric potential, and reduces the simulation errors of discharge current and discharge power from 19.8% to 9.8%. The accuracy of PIC-MCC simulation has been improved at the expense of slightly increasing the computational time.

Original languageEnglish
Article number033311
JournalPhysical Review E
Volume102
Issue number3
DOIs
Publication statusPublished - Sept 2020
Externally publishedYes

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