Kinetic Particle Simulations of Plasma Charging and Dust Transport Near Uneven Lunar Surface Terrain
Abstract
This paper presents a kinetic particle simulation study of the plasma charging and dust transport near the uneven lunar surface terrain. A fully-kinetic 3-D finite-difference (FD) particle-in-cell (PIC) code is utilized to simulate the plasma interaction with uneven surface terrain. The levitation and transport of charged dust grains under the effect of the local photoelectron sheath will be investigated. The profile of quantities of interests, such as electric potential, electric field, solar wind and photoelectron density, and the concentration of charged dust within the photoelectron sheath will be presented.
Recommended Citation
J. Zhao et al., "Kinetic Particle Simulations of Plasma Charging and Dust Transport Near Uneven Lunar Surface Terrain," Proceedings of the AIAA Science and Technology Forum and Exposition (2022, San Diego, CA), article no. AIAA 2022-1988, American Institute of Aeronautics and Astronautics (AIAA), Jan 2022.
The definitive version is available at https://doi.org/10.2514/6.2022-1988
Meeting Name
AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022
Department(s)
Civil, Architectural and Environmental Engineering
Second Department
Mathematics and Statistics
Third Department
Mechanical and Aerospace Engineering
International Standard Book Number (ISBN)
978-162410631-6
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2022 The Authors, All rights reserved.
Publication Date
07 Jan 2022
Comments
Session: Spacecraft Charging I - Dust, Plasma, and Arc Inception
This work was partially supported by NASA-Missouri Space Grant Consortium through NASA-EPSCoR-Missouri, as well as NSF through grants DMS-2111039 and CBET-2132655. The simulations presented here were performed with computing resources provided by the Center for High Performance Computing Research at Missouri University of Science and Technology through an NSF grant (OAC-1919789).