High-Resolution Global Point Mascon Models for the Moon

No AccessEngineering NotesHigh-Resolution Global Point Mascon Models for the MoonSean McArdle and Ryan P. RussellSean McArdle https://orcid.org/0000-0001-8849-4778The University of Texas at Austin, Austin, Texas 78712*Graduate Student, Aerospace Engineering, 2617 Wichita Street; .Search for more papers by this author and Ryan P. Russell https://orcid.org/0000-0001-7672-0408The University of Texas at Austin, Austin, Texas 78712†Professor, Aerospace Engineering, 2617 Wichita Street; .Search for more papers by this authorPublished Online:27 Feb 2023https://doi.org/10.2514/1.G006921SectionsRead Now ToolsAdd to favoritesDownload citationTrack citations ShareShare onFacebookTwitterLinked InRedditEmail About References [1] McArdle S. and Russell R. P., “Global Point Mascon Models for the Moon,” AAS/AIAA Astrodynamics Specialists Conference, AAS Paper 20-666, Univelt, Inc., San Diego, CA, 2020, pp. 1–19. 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TopicsApplied MathematicsAvionics ComputersComputer GraphicsComputing and InformaticsComputing, Information, and CommunicationEarth SciencesGeneral PhysicsGeophysicsMathematical AnalysisPlanetary Science and ExplorationPlanetsSolar System MoonsSpace Science and Technology KeywordsSolar System MoonsMathematical AnalysisGraphics Processing UnitCentral Processing UnitHigh Performance ComputingPlanetsShell StructuresNear Rectilinear Halo OrbitApplication Programming InterfaceGeochemistryAcknowledgmentsThe authors would like to thank the University of Texas at Austin for its support through the Thrust 2000 Fellowship and the Texas Space Grant Consortium for its support through its graduate fellowship. The authors would also like to thank Shane Robinson and David Dannemiller for their discussions and insightful suggestions. This material is based upon work supported by NASA under award No. 80NSSC18M0121. The authors acknowledge the Texas Advanced Computing Center at The University of Texas at Austin for providing high-performance computing resources that have contributed to the results reported within this paper (http://www.tacc.utexas.edu).PDF Received26 April 2022Accepted29 January 2023Published online27 February 2023