A new free surface identification method for 3D MPS method

A new free surface identification method for 3D MPS method | 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 Article A new free surface identification method for 3D MPS method Chong Geng, Wen-hua Wang, Mengyuan Heng, Yu Zhao, Hao Yang, Yi Huang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7287063/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted 16 You are reading this latest preprint version Abstract In the Moving Particle Semi-Implicit (MPS) method, free surface identification in three dimensions has traditionally relied on particle number density. However, this approach often leads to misidentification of surface particles, which in turn compromises the accuracy of pressure field calculations. In this study, an improved formulation for calculating the relative position divergence (RPD) is first proposed to better align with theoretical expectations, and a surface identification criterion for three-dimensional cases is established using a model with internal cavities. Based on this, an improved surface particle identification method is introduced by combining RPD with an estimation of the surface normal vector (RPD + NV). Validation through geometry-based models demonstrates that the proposed approach can accurately capture surface features, including sharp corners, concave and convex regions, and internal cavities. Further verification using a series of MPS simulations, including static water, dam break, and damped oscillation scenarios, confirms that both the improved RPD method and the combined RPD + NV scheme can effectively suppress pressure fluctuations. Moreover, the proposed method significantly reduces false negatives and false positives in surface particle identification, resulting in a smoother and more accurate pressure field. Consequently, the proposed surface identification method is well-suited for three-dimensional MPS simulations. Physical sciences/Engineering Physical sciences/Mathematics and computing Physical sciences/Physics MPS method free surface particles relative position divergence normal vector pressure fluctuation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 17 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 17 Nov, 2025 Reviews received at journal 13 Oct, 2025 Reviews received at journal 10 Oct, 2025 Reviews received at journal 07 Oct, 2025 Reviews received at journal 05 Oct, 2025 Reviewers agreed at journal 03 Sep, 2025 Reviewers agreed at journal 30 Aug, 2025 Reviewers agreed at journal 29 Aug, 2025 Reviewers agreed at journal 29 Aug, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers invited by journal 28 Aug, 2025 Editor assigned by journal 14 Aug, 2025 Submission checks completed at journal 11 Aug, 2025 First submitted to journal 11 Aug, 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. 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particles, relative position divergence, normal vector, pressure fluctuation","lastPublishedDoi":"10.21203/rs.3.rs-7287063/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7287063/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the Moving Particle Semi-Implicit (MPS) method, free surface identification in three dimensions has traditionally relied on particle number density. However, this approach often leads to misidentification of surface particles, which in turn compromises the accuracy of pressure field calculations. In this study, an improved formulation for calculating the relative position divergence (RPD) is first proposed to better align with theoretical expectations, and a surface identification criterion for three-dimensional cases is established using a model with internal cavities. Based on this, an improved surface particle identification method is introduced by combining RPD with an estimation of the surface normal vector (RPD\u0026thinsp;+\u0026thinsp;NV). Validation through geometry-based models demonstrates that the proposed approach can accurately capture surface features, including sharp corners, concave and convex regions, and internal cavities. Further verification using a series of MPS simulations, including static water, dam break, and damped oscillation scenarios, confirms that both the improved RPD method and the combined RPD\u0026thinsp;+\u0026thinsp;NV scheme can effectively suppress pressure fluctuations. Moreover, the proposed method significantly reduces false negatives and false positives in surface particle identification, resulting in a smoother and more accurate pressure field. 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