Enhanced gas-surface scattering modeling for VLEO satellites in DSMC simulations

Enhanced gas-surface scattering modeling for VLEO satellites in DSMC simulations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Enhanced gas-surface scattering modeling for VLEO satellites in DSMC simulations Miklas Schütte, Stefanos Fasoulas, Marcel Pfeiffer This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6225632/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Jun, 2025 Read the published version in CEAS Space Journal → Version 1 posted 9 You are reading this latest preprint version Abstract The Direct Simulation Monte Carlo (DSMC) method is a crucial tool for calculating the aerodynamicsof satellites in Very Low Earth Orbit (VLEO). However, DSMC simulations fall short in providinghigh-precision gas-surface scattering models. Implementing such model could vastly enhance missionplanning and fuel requirement calculations, ultimately extending operational lifetimes and reducingcosts. Moreover, the ability to utilize aerodynamic lift for altitude and orbit control reduces the needfor thrusters and fuel. Existing scattering models in DSMC can only capture the full complexity of theinteractions between gas and surface to a limited extent. Molecular dynamics (MD) simulations areexcellent for accurately modeling these interactions on a microscopic scale and provide detailed insightsinto the physical processes involved. However, due to computational limitations, it is not possible tosimulate the entire scale of a satellite with MD. We present an advanced modeling technique that is ableto use reflected velocity data points from MD simulations, to create a scattering kernel. This kernel,which represents a conditional probability density function, can be integrated into DSMC simulations,significantly enhancing their accuracy. VLEO DSMC databased gas-surface scattering machine learning Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Jun, 2025 Read the published version in CEAS Space Journal → Version 1 posted Editorial decision: Revision requested 30 Apr, 2025 Reviews received at journal 21 Apr, 2025 Reviews received at journal 03 Apr, 2025 Reviewers agreed at journal 26 Mar, 2025 Reviewers agreed at journal 26 Mar, 2025 Reviewers invited by journal 24 Mar, 2025 Editor assigned by journal 15 Mar, 2025 Submission checks completed at journal 14 Mar, 2025 First submitted to journal 14 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6225632","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":434265497,"identity":"4479d729-0038-4bf6-bb4c-92d583c5c54d","order_by":0,"name":"Miklas Schütte","email":"data:image/png;base64,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","orcid":"","institution":"University of Stuttgart","correspondingAuthor":true,"prefix":"","firstName":"Miklas","middleName":"","lastName":"Schütte","suffix":""},{"id":434265499,"identity":"483e2de2-f9b0-4e46-903f-408712da7901","order_by":1,"name":"Stefanos Fasoulas","email":"","orcid":"","institution":"University of Stuttgart","correspondingAuthor":false,"prefix":"","firstName":"Stefanos","middleName":"","lastName":"Fasoulas","suffix":""},{"id":434265501,"identity":"ba6e1e21-1514-4c27-bfde-bbf04c408d5d","order_by":2,"name":"Marcel Pfeiffer","email":"","orcid":"","institution":"University of Stuttgart","correspondingAuthor":false,"prefix":"","firstName":"Marcel","middleName":"","lastName":"Pfeiffer","suffix":""}],"badges":[],"createdAt":"2025-03-14 11:09:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6225632/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6225632/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12567-025-00629-4","type":"published","date":"2025-06-13T15:57:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84726548,"identity":"9e81f578-1645-4b1d-8c1c-29fa41dbb055","added_by":"auto","created_at":"2025-06-16 16:06:51","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":899959,"visible":true,"origin":"","legend":"","description":"","filename":"EnhancedgassurfacescatteringmodelingforVLEOsatellitesinDSMCsimulations.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6225632/v1_covered_35dfb49b-38af-463d-9946-cc16166a9bb0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Enhanced gas-surface scattering modeling for VLEO satellites in DSMC simulations","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"ceas-space-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ceas","sideBox":"Learn more about [CEAS Space Journal](http://link.springer.com/journal/12567)","snPcode":"12567","submissionUrl":"https://submission.nature.com/new-submission/12567/3","title":"CEAS Space Journal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"VLEO, DSMC, databased gas-surface scattering, machine learning","lastPublishedDoi":"10.21203/rs.3.rs-6225632/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6225632/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The Direct Simulation Monte Carlo (DSMC) method is a crucial tool for calculating the aerodynamicsof satellites in Very Low Earth Orbit (VLEO). 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