Pan Ruojian, Ren Junxue, Tang Haibin, Cao Shuai, Li Juan, Zhang Zhe, Zhou Jun, Cao Jinbin
School of Space and Environment, Beihang University, Beijing 100083, China.
School of Astronautics, Beihang University, Beijing 100083, China.
Phys Rev E. 2020 Sep;102(3-1):033311. doi: 10.1103/PhysRevE.102.033311.
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.
粒子模拟（PIC）和蒙特卡罗碰撞（MCC）方法已被广泛用作电推进的模拟方法。然而，中性原子的运动速度比其他粒子慢得多，这可能会导致模拟速度大幅降低。在这项工作中，我们研究了视因子模型与PIC-MCC方法相结合的情况，并提出了一种模拟三维中性原子的方法。通过定期更新中性原子分布，可以显著提高PIC-MCC方法的精度。我们将计算结果与加利福尼亚大学洛杉矶分校（UCLA）微型环形尖点放电实验的固定中性PIC-MCC模型进行了比较。模拟的等离子体分布和电势分布与UCLA实验数据吻合良好。与固定中性模型相比，视因子模型在提高中性原子、等离子体密度和电势分布精度的同时，仅将模拟时间增加了33%，并将放电电流和放电功率的模拟误差从19.8%降低到了9.8%。PIC-MCC模拟的精度得到了提高，但代价是计算时间略有增加。
