An improved updated Lagrangian SPH method for structural modelling

Khayyer, A., Shimizu, Y., Lee, C. H. , Gil, A., Gotoh, H. and Bonet, J. (2023) An improved updated Lagrangian SPH method for structural modelling. Computational Particle Mechanics, (doi: 10.1007/s40571-023-00673-z) (Early Online Publication)

Abstract

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.

• Item Type: Articles
• 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.
• Keywords: Smoothed particle hydrodynamics, structure model, updated Lagrangian SPH, δSPH, tensile instability, accuracy, consistency.
• Status: Early Online Publication
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Lee, Dr Chun Hean
• Authors: Khayyer, A., Shimizu, Y., Lee, C. H., Gil, A., Gotoh, H., and Bonet, J.
• College/School: College of Science and Engineering > School of Engineering > Infrastructure and Environment
• Journal Name: Computational Particle Mechanics
• Publisher: Springer
• ISSN: 2196-4378
• Published Online: 27 November 2023
• Copyright Holders: Copyright © The Author(s) under exclusive licence to OWZ 2023
• First Published: First published in Computational Particle Mechanics 2023
• Publisher Policy: Reproduced in accordance with the publisher copyright policy