Particle Simulation Model for Self-Field Magnetoplasmadynamic Thruster

Jian Li, Yu Zhang, Jianjun Wu, Yuqiang Cheng and Xinru Du
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Jian Li: College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China
Yu Zhang: College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China
Jianjun Wu: College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China
Yuqiang Cheng: College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China
Xinru Du: College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China

Energies, 2019, vol. 12, issue 8, 1-14

Abstract: In order to clarify the discharge principle of the self-field magnetoplasmadynamic thruster (MPDT), a two-dimensional axisymmetric particle-in-cell/Monte Carlo collision (PIC/MCC) model is proposed. The spatial distribution and the collision characteristics of discharge plasma were calculated using this model. In addition, the influence of the operation parameters on the plasma was analyzed including the voltage and mass flow rate. The effectiveness of the model was verified by comparison to the experimentally induced magnetic field. It was found that the electrons were mainly accelerated by the electric field in the cathode sheath and the electric field shielding effect of plasma was obvious in the bulk plasma region. Due to the pinch effect, the charged particles were constrained near the cathode. The results of the present work implied that the PIC/MCC model provides an approach to investigate the plasma distribution and a kinetic description of particles for the discharge of the self-field MPDT.

Keywords: self-field magnetoplasmadynamic thruster; particle-in-cell; Monte Carlo collision; discharge plasma; particle simulation; sheath (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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