Application of the Monte Carlo method in modeling dusty gas, dust in plasma, and energetic ions in planetary, magnetospheric, and heliospheric environments.

dc.contributor.authorTenishev, Valeriy
dc.contributor.authorShou, Yinsi
dc.contributor.authorBorovikov, Dmitry
dc.contributor.authorLee, Yuni
dc.contributor.authorFougere, Nicolas
dc.contributor.authorMichael, Adam
dc.contributor.authorCombi, Michael R.
dc.date.accessioned2021-02-08T17:14:54Z
dc.date.available2021-02-08T17:14:54Z
dc.date.issued2021-01-13
dc.description.abstractTypical planetary and planetary satellite exospheres are in non‐equilibrium conditions, which means that a distribution function that describes these environments is far from Maxwellian. It is even more true when considering transportation of energetic ions in planetary magnetospheres, making it necessary to solve the Boltzmann equation in order to capture kinetic effects when modeling evolution of the distribution function describing such environments. Among various numerical methods, the Monte Carlo approach is one of the most used one for solving kinetic equations. That is because of the relative simplicity of implementing and a high degree of flexibility in including new physical processes specific to a particular simulated environment. Adaptive Mesh Particle Simulator (AMPS) was developed as a general‐purpose code for solving the Boltzmann equation in conditions typical for planetary and planetary satellite exospheres. Later, the code was generalized for modeling dusty gas, dust and plasma, and for simulating transportation of solar energetic particles and galactic cosmic rays in planetary magnetospheres. Here we present a brief overview of the design, list the implemented physics models, and outline the modeling capabilities of AMPS. The latter is supported by several examples of prior applications of the code.en_US
dc.description.sponsorshipSupport for this work was provided by grant 80NSSC17K0681 from the NASA Living with a Star Program and by NASA grant 18-DRIVE18 2-0029, Our Heliospheric Shield,80NSSC20K0603. We also acknowledge the supp or t by NASA’s Community Coordinated Modeling Center during the transitining of AMP Stothec enter.
dc.description.urihttps://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2020JA028242en_US
dc.format.extent23 pagesen_US
dc.genrejournal articles postprintsen_US
dc.identifierdoi:10.13016/m2ggph-9s8c
dc.identifier.citationValeriy Tenishev, Yinsi Shou, Dmitry Borovikov, Yuni Lee, Nicolas Fougere, Adam Michael and Michael R. Combi, Application of the Monte Carlo method in modeling dusty gas, dust in plasma, and energetic ions in planetary, magnetospheric, and heliospheric environments, JGR Space Physics, https://doi.org/10.1029/2020JA028242en_US
dc.identifier.urihttps://doi.org/10.1029/2020JA028242
dc.identifier.urihttp://hdl.handle.net/11603/20973
dc.language.isoen_USen_US
dc.publisherAGU Pubicationen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Center for Space Sciences and Technology
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Physics Department
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rights©2018. American Geophysical Union. All Rights Reserved.
dc.rightsAccess to this item will begin on 07/13/21
dc.titleApplication of the Monte Carlo method in modeling dusty gas, dust in plasma, and energetic ions in planetary, magnetospheric, and heliospheric environments.en_US
dc.typeTexten_US

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