Published, Version of Record (VoR)CC BY V4.0, Open
Abstract
Advances in Computational Integral Equations Article Computational Mathematics and Numerical Analysis Computational Science and Engineering Mathematical and Computational Biology Mathematical Modeling and Industrial Mathematics Mathematics Mathematics and Statistics Visualization
We present two accurate and efficient algorithms for solving the incompressible, irrotational Euler equations with a free surface in two dimensions with background flow over a periodic, multiply connected fluid domain that includes stationary obstacles and variable bottom topography. One approach is formulated in terms of the surface velocity potential while the other evolves the vortex sheet strength. Both methods employ layer potentials in the form of periodized Cauchy integrals to compute the normal velocity of the free surface, are compatible with arbitrary parameterizations of the free surface and boundaries, and allow for circulation around each obstacle, which leads to multiple-valued velocity potentials but single-valued stream functions. We prove that the resulting second-kind Fredholm integral equations are invertible, possibly after a physically motivated finite-rank correction. In an angle-arclength setting, we show how to avoid curve reconstruction errors that are incompatible with spatial periodicity. We use the proposed methods to study gravity-capillary waves generated by flow around several elliptical obstacles above a flat or variable bottom boundary. In each case, the free surface eventually self-intersects in a splash singularity or collides with a boundary. We also show how to evaluate the velocity and pressure with spectral accuracy throughout the fluid, including near the free surface and solid boundaries. To assess the accuracy of the time evolution, we monitor energy conservation and the decay of Fourier modes and compare the numerical results of the two methods to each other. We implement several solvers for the discretized linear systems and compare their performance. The fastest approach employs a graphics processing unit (GPU) to construct the matrices and carry out iterations of the generalized minimal residual method (GMRES).
Numerical algorithms for water waves with background flow over obstacles and topography
Creators
David M. Ambrose - Drexel University
Roberto Camassa - University of North Carolina at Chapel Hill
Jeremy L. Marzuola - University of North Carolina at Chapel Hill
Richard M. McLaughlin - University of North Carolina at Chapel Hill
Quentin Robinson - North Carolina Central University
Jon Wilkening - University of California, Berkeley
Publication Details
Advances in computational mathematics, v 48(4)
Publisher
Springer US
Grant note
DMS-1716560 / national science foundation (https://doi.org/10.13039/100000001)
DE-AC02-05CH11231 / u.s. department of energy (https://doi.org/10.13039/100000015)
ONR N00014-18-1-2490 / office of naval research (https://doi.org/10.13039/100000006)
DMS-1910824 / national science foundation (https://doi.org/10.13039/100000001)
DMS-1909035 / national science foundation (https://doi.org/10.13039/100000001)
DMS-1352353 / national science foundation (https://doi.org/10.13039/100000001)
DMS-1907684 / national science foundation (https://doi.org/10.13039/100000001)
Resource Type
Journal article
Language
English
Academic Unit
Mathematics
Web of Science ID
WOS:000822492300001
Scopus ID
2-s2.0-85133703844
Other Identifier
991019168586904721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool: