A material point/finite volume method for coupled shallow water flows and large dynamic deformations in seabeds

Zheng, Xiangcou; Seaid, Mohammed; Pisanò, Federico; Hicks, Michael A.; Vardon, Philip J.; Huvaj, Nejan; Osman, Ashraf S.

Abstract

A hybrid material point/finite volume method for the numerical simulation of shallow water waves caused by large dynamic deformations in the bathymetry is presented. The proposed model consists of coupling the nonlinear shallow water equations for the water flow and a dynamic elastoplastic system for the seabed deformation. As a constitutive law, we consider a linear elastic-non-associative plastic model with the Drucker-Prager yield criterion allowing for large deformations under undrained cases. The transfer conditions between these models are achieved by using forces sampled from the hydraulic pressure and the friction terms along the interface between the seabed soil and shallow water. A detailed description regarding the coupled algorithm for the hybrid material point/finite volume method is presented. Several numerical examples are investigated to demonstrate the performance of the finite volume method for simulations of shallow water flow and the material point method for capturing the large deformation process of the solid phase. We also present numerical simulations of an undrained clay column collapse that induced shallow water waves and a dam-break problem to demonstrate the excellent performance of the proposed hybrid material point/finite volume method.

Citation

Zheng, X., Seaid, M., Pisanò, F., Hicks, M. A., Vardon, P. J., Huvaj, N., & Osman, A. S. (2023). A material point/finite volume method for coupled shallow water flows and large dynamic deformations in seabeds. Computers and Geotechnics, 162(October), Article 105673. https://doi.org/10.1016/j.compgeo.2023.105673

• Journal Article Type: Article
• Acceptance Date: Jul 15, 2023
• Online Publication Date: Aug 1, 2023
• Publication Date: 2023-10
• Deposit Date: Aug 30, 2023
• Publicly Available Date: Aug 30, 2023
• Journal: Computers and Geotechnics
• Print ISSN: 0266-352X
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 162
• Issue: October
• Article Number: 105673
• DOI: https://doi.org/10.1016/j.compgeo.2023.105673
• Keywords: Computer Science Applications; Geotechnical Engineering and Engineering Geology
• Public URL: https://durham-repository.worktribe.com/output/1726543