Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-27T18:28:08.513Z Has data issue: false hasContentIssue false

A parallel particle-in-cell code for spacecraft charging problems

Published online by Cambridge University Press:  03 June 2020

Kai Zhang
Affiliation:
Department of Mechanical Engineering-Engineering Mechanics, Michigan Technological University, Houghton, MI49931, USA
Shiying Cai
Affiliation:
Department of Mechanical Engineering-Engineering Mechanics, Michigan Technological University, Houghton, MI49931, USA
Chunpei Cai*
Affiliation:
Department of Mechanical Engineering-Engineering Mechanics, Michigan Technological University, Houghton, MI49931, USA
David L. Cooke
Affiliation:
Space Vehicle Directorate, Air Force Research Laboratory, Kirtland Air Force Base, Albuquerque, NM87117, USA
*
Email address for correspondence: [email protected]

Abstract

This paper reports the recent development of a full-scale particle-in-cell (PIC) simulation package highlighting an efficient electro-statics (ES)-PIC implementation for spacecraft charging problems. Numerical simulations are crucial in studying plasma flows because analytical solutions are rare, and experiments are expensive. There are many types of plasma flow that need various numerical methods for efficient and accurate simulations; as such, how to implement and organize those different methods into one comprehensive simulation package is challenging. This work adopted several modern software design patterns and developed a versatile package that includes various PIC schemes. This package has an open architecture, clean interfaces with both serial and parallel simulation capabilities. Two benchmark test cases are included to demonstrate the capabilities of this package. Then two plasma flows around a positively charged probe are simulated, and the results are discussed. The simulation results are consistent with past simulation results, and new insights are obtained. This work can lead to the development and organization of more sophisticated plasma simulation solvers in the future.

Type
Research Article
Copyright
© The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ahrens, J., Geveci, B. & Law, C. 2005 ParaView: An End-User Tool for Large Data Visualization, Visualization Handbook. Elsevier.Google Scholar
Ayachit, U. 2015 The ParaView Guide: A Parallel Visualization Application. Kitware.Google Scholar
Benzi, M. & Tuma, M. 1999 A comparative study of sparse approximate inverse pre-conditioners. Appl. Numer. Maths 30, 305340.CrossRefGoogle Scholar
Bird, G. 1994 Molecular Gas Dynamics and Direct Simulation of Gas Flows. Clarendon Press.Google Scholar
Birdsall, C. & Langdon, A. 1991 Plasma Physics Via Computer Simulation. Taylor & Francis.CrossRefGoogle Scholar
Blahovec, J. D., Bowers, L. & Luginsland, J. 2000 3D ICEPIC simulations of the realistic Klystron oscillator. IEEE Trans. Plasma Sci. 28, 821829.Google Scholar
Boris, J. P.1970 The acceleration calculation from a scalar potential. Tech. Rep. MATT-152. Plasma Physics Laboratory, Princeton University, NJ.Google Scholar
Brieda, L. 2018 Model for steady-state fully kinetic ion beam neutralization studies. IEEE Trans. Plasma Sci. 46 (3), 556562.CrossRefGoogle Scholar
Cai, C. 2017 An improved electron pre-sheath model for TSS-1R current enhancement computation. Aerospace 4, 1.CrossRefGoogle Scholar
Cooke, D. & Katz, I. 1998 TSS-1R electron currents: magnetic limited collection from a heated pre-sheath. Geophy. Res. Lett. 25, 735756.CrossRefGoogle Scholar
Derouilla, J., Beck, A., Perez, F., Vinci, T., Chiaramello, M., Grassi, A., Fle, M., Bouchard, G., Plotnikov, I., Aunai, N. et al. 2017 SMILEI: a collaborative, open-source, multi-purpose particle-in-cell code for plasma simulation. Phys. Plasma 2, 16. arXiv:1702.05128v1.Google Scholar
Gamma, E., Johnson, R. & Vlissides, J. 1995 Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley.Google Scholar
Giacone, R. 2002 Generation of nonlinear plasma wake fields in the colliding laser pulses injection schemes. Bull. Am. Phys. Soc. 47, 282.Google Scholar
Golub, G. H., Charles, F. & Loan, V. 2012 Matrix computations. Comput. Fluids 57, 6775.Google Scholar
Heinrich, J. & Cooke, D. 2013 Dynamics of positive probes in under-dense, strongly magnetized, $E\times B$ drifting plasma: particle-in-cell simulations. Phys. Plasmas 20, 093503.CrossRefGoogle Scholar
Huang, T., Tuma, M., Zhang, Y., Li, L., Shao, W. & Lai, S. 2009 Modified incomplete Cholesky factorization for solving electromagnetic scattering problems. PERB 13, 4158.Google Scholar
Janeski, J., Scales, W. & Hall, C. 2014 Investigation of the current collected by a positively biased satellite with application to electro-dynamic tethers. J. Geophys. Res. 119, 78247840.Google Scholar
Kolotilina, L., Yu, L. & Yeremin, A. 1993 Factorized sparse approximate inverse pre-conditioning. I. Theory. SIAM J. Matrix Anal. A 14, 4558.CrossRefGoogle Scholar
Laframboise, J.1966 Theory of spherical and cylindrical Langmuir probes in a collisionless, Maxwellian plasma at rest. PhD dissertation, University of Toronto, Canada.CrossRefGoogle Scholar
Laframboise, J. & Sonmor, L. 1993 Current collection by probes and electrodes in space magneto-plasmas: a review. J. Geophys. Res.: Space Phys. 98 (A1), 337357.CrossRefGoogle Scholar
Liewer, P. & Decyk, V. 1989 A general concurrent algorithm for plasma particle-in-cell simulation codes. J. Comput. Phys. 85, 302.CrossRefGoogle Scholar
Lippman, S., Lajoie, J. & Moo, B. 2005 C++ Primer. Addison-Wesley Professional.Google Scholar
Liu, H., Cai, C. & Zou, C. 2012 An object-oriented serial implementation of a DSMC simulation package. Comput. Fluids 57, 6775.CrossRefGoogle Scholar
MacNeal, R.1972 The NASTRAN theoretical manual. Tech. Rep. NASA.Google Scholar
Markidis, S., Lapenta, G. & Rizwan-uddin 2010 Multi-scale simulations of plasma with IPIC3D. Math. Comput. Simul. 80, 15091519.CrossRefGoogle Scholar
Nieter, C. & Cary, J. 2004 VORPAL: a versatile plasma simulation code. J. Comput. Phys. 196, 448473.CrossRefGoogle Scholar
Onishi, T.1998 Electron current collection by a positively charged tether using a particle-in-cell method. PhD thesis, Massachusetts Institute of Technology.Google Scholar
Parker, L. & Murphy, B. 1967 Potential buildup on an electron-emitting ionospheric satellite. J. Geophys. Res. 72, 1631.CrossRefGoogle Scholar
Pritchett, P. L. 2000 Particle-in-cell simulations of magnetosphere electrodynamics. IEEE Trans. Plasma Sci. 28 (6), 19761990.CrossRefGoogle Scholar
Singh, N., Leung, W. & Singh, G. 2000 Enhanced current collection by a positively charged spacecraft. J. Geophys. Res. 105 (A9), 2093520947.CrossRefGoogle Scholar
Singh, N. L., Leung, W. & Vashi, B. 1997 Potential structure near a probe in a flowing magneto-plasma and current collection. J. Geophys. Res. 102, 195208.CrossRefGoogle Scholar
Singh, N. L., Vashi, B. & Leung, L. 1994 Threedimensional numerical simulation of current collection by a probe in a magnetized plasma. Geophy. Res. Lett. 21, 833836.CrossRefGoogle Scholar
Verboncoeur, J., Langdon, A. & Gladd, N. 1995 An object-oriented electromagnetic PIC code. Comput. Phys. Commun. 87, 199.CrossRefGoogle Scholar
Wolfheimer, F., Gjonaj, E. & Weiland, T.2006 Parallel particle-in-cell (PIC) codes. Tech. Rep. In Proceedings of ICAP.Google Scholar