Numerical wave basin using incompressible smoothed particle hydrodynamics (ISPH) on a single GPU with vertical cylinder test cases

Chow, Alex D., Rogers, Benedict D., Lind, Steven J. and Stansby, Peter K. 2019. Numerical wave basin using incompressible smoothed particle hydrodynamics (ISPH) on a single GPU with vertical cylinder test cases. Computers and Fluids 179 , pp. 543-562. 10.1016/j.compfluid.2018.11.022

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Abstract

This paper presents the development of a numerical wave basin for violent hydrodynamics of free-surface waves interacting with vertical cylindrical structures using the incompressible smoothed particle hydrodynamics (ISPH) method accelerated with a graphics processing unit (GPU). ISPH has been implemented on a single GPU based on the open-source DualSPHysics software and using the ViennaCL linear algebra library for solving the pressure Poisson equation. Extensions to the code are presented for a numerical wave basin including development of the solid boundary condition, based on a mirror image particle and moving least squares interpolation approach, for improved accuracy at the free and solid surface interfaces during wave-structure impact. This is applied to focused waves, including breaking for which SPH is well suited, interacting with a cylindrical column to compare with experimental data. Convergence is demonstrated within the limit of 5 million particles for a single GPU. Acceptable agreement with experiment is achieved for force measurements, and variation of free-surface elevation around the column is shown to be significant particularly in larger waves with a correspondingly large force contribution from hydrostatic pressure. While breaking does not have a marked effect on total force, associated high particle velocities amplify local pressures considerably on the column near the water surface. The computer runtime is similar to that for volume-of-fluid and particle-in-cell solvers running on 8 and 80 processors respectively.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	Elsevier
ISSN:	0045-7930
Date of Acceptance:	21 November 2018
Last Modified:	07 Jun 2024 14:00
URI:	https://orca.cardiff.ac.uk/id/eprint/169415

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