Khayyer, Abbas and Shimizu, Yuma and Lee, Chun Hean and Gil, Antonio and Gotoh, Hitoshi and Bonet, Javier (2024) An improved updated Lagrangian SPH method for structural modelling. Computational Particle Mechanics, 11. pp. 1055-1086. ISSN 2196-4378
AI Summary:
This paper presents a set of novel refined schemes to enhance the accuracy and stability of the updated Lagrangian SPH ULSPH for structural modelling.AI Topics:
This paper presents a set of novel refined schemes to enhance the accuracy and stability of the updated Lagrangian SPH (ULSPH) for structural modelling. The original ULSPH structure model was first proposed by Gray et al. (Comput Methods Appl Mech Eng 190:6641–6662, 2001) and has been utilised for a wide range of structural analyses including metal, soil, rubber, ice, etc., although the model often faces several drawbacks including unphysical numerical damping, high-frequency noise in reproduced stress fields, presence of several artificial terms requiring ad hoc tunings and numerical instability in the presence of tensile stresses. In these regards, this study presents a set of enhanced schemes corresponding to (1) consistency correction on discretisation schemes for differential operators, (2) a numerical diffusive term incorporated in the continuity or the density rate equation, (3) tuning-free stabilising term based on Riemann solution and (4) careful control/switch of stress divergence differential operator model under tensile stresses. Qualitative/quantitative validations are conducted through several well-known benchmark tests.
Title | An improved updated Lagrangian SPH method for structural modelling |
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Creators | Khayyer, Abbas and Shimizu, Yuma and Lee, Chun Hean and Gil, Antonio and Gotoh, Hitoshi and Bonet, Javier |
Identification Number | 10.1007/s40571-023-00673-z |
Date | June 2024 |
Divisions | College of Science and Engineering > School of Engineering > Infrastructure and Environment |
Publisher | Springer |
Additional Information | This study was supported by JSPS (Japan Society for the Promotion of Science) KAKENHI Grants Numbers JP21H01433, JP18K04368, JP21K14250 and JP22H01599. Antonio Gil and Chun Hean Lee would like to acknowledge the financial support received through the project Marie Sklodowska-Curie ITN-EJD ProTechTion, funded by the European Union Horizon 2020 research and innovation programme with Grant Number 764636. |
URI | https://pub.demo35.eprints-hosting.org/id/eprint/249 |
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Item Type | Article |
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Depositing User | Unnamed user with email ejo1f20@soton.ac.uk |
Date Deposited | 11 Jun 2025 16:36 |
Revision | 19 |
Last Modified | 12 Jun 2025 10:39 |
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