Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/116326
DC FieldValueLanguage
dc.contributorDepartment of Civil and Environmental Engineeringen_US
dc.creatorFang, Hen_US
dc.creatorYin, ZYen_US
dc.date.accessioned2025-12-16T03:19:55Z-
dc.date.available2025-12-16T03:19:55Z-
dc.identifier.issn0021-9991en_US
dc.identifier.urihttp://hdl.handle.net/10397/116326-
dc.language.isoenen_US
dc.publisherAcademic Pressen_US
dc.subjectComputational Fluid Dynamicsen_US
dc.subjectLagrangian Formulationen_US
dc.subjectMesh-based Methoden_US
dc.subjectParticle Interpolation Reconstructionen_US
dc.subjectParticle Methoden_US
dc.titleLagrangian hybrid element particle method (LHEPM) for incompressible fluid dynamicsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume541en_US
dc.identifier.doi10.1016/j.jcp.2025.114281en_US
dcterms.abstractTraditional numerical approaches for solving incompressible fluid dynamics problems face notable limitations, including convective instability and interface tracking in Eulerian approaches, severe element distortion in Lagrangian mesh-based methods, and reduced computational accuracy in particle-based approaches. To overcome these challenges, this paper develops a new Lagrangian Hybrid Element Particle Method (LHEPM) that combines two discretization schemes: underlying elements and material particles. The underlying elements, designed without storing historical variables, can be dynamically regenerated during the computation. These elements serve as temporary tools for discretizing physical fields within the computational domain, with their spatial interpolation subsequently reconstructed onto the particles via a kernel function. The proposed framework permits the seamless incorporation of diverse finite element techniques, such as boundary condition enforcement, contact algorithms, and pressure stabilization, without requiring modifications. The effectiveness and performance of LHEPM are validated through its application to several standard fluid problems. Compared to other state-of-the-art methods, the proposed LHEPM avoids the need for complex treatment of convective terms and free-surface tracking typically required in Eulerian mesh-based approaches, such as the finite volume method (FVM); its unique interpolation technique and optimal particle integration enable significantly higher accuracy than particle-based methods like Smoothed Particle Hydrodynamics (SPH); dynamic mesh regeneration further resolves the mesh distortion issues inherent in traditional Lagrangian finite element method (FEM), making the proposed method a precise, efficient, and robust framework for incompressible fluid dynamics simulations.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationJournal of computational physics, 5 Nov. 2025, v. 541, 114281en_US
dcterms.isPartOfJournal of computational physicsen_US
dcterms.issued2025-11-05-
dc.identifier.scopus2-s2.0-105013964370-
dc.identifier.artn114281en_US
dc.description.validate202512 bchyen_US
dc.description.oaNot applicableen_US
dc.identifier.SubFormIDG000477/2025-09-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextFunding text 1: The authors gratefully acknowledge the financial support from the Research Grants Council (RGC) of the Hong Kong Special Administrative Region Government (HKSARG) of China under Grant Nos. 15227923 and 15229223. The authors are also grateful to Prof. Dan Negrut and Dr. Lijing Yang from the University of Wisconsin-Madison for providing the original SPH data used for the comparative analysis in Section 6.2. During the preparation of this work the authors used \u201CChatGPT\u201D in order to improve language. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.; Funding text 2: The authors gratefully acknowledge the financial support from the Research Grants Council (RGC) of the Hong Kong Special Administrative Region Government (HKSARG) of China under Grant Nos. 15227923 and 15229223 . The authors are also grateful to Prof. Dan Negrut and Dr. Lijing Yang from the University of Wisconsin-Madison for providing the original SPH data used for the comparative analysis in Section 6.2.en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2027-11-05en_US
dc.description.oaCategoryGreen (AAM)en_US
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