Numerical algorithms for water waves with background flow over obstacles and topography
Numerical algorithms for water waves with background flow over obstacles and topography
复制标题
具有越过障碍物和地形的背景流的水波的数值算法
DOI:
10.1007/s10444-022-09957-z
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发表时间:
2022
影响因子:
1.7
通讯作者:
Wilkening, Jon
中科院分区:
文献类型:
--
作者:
Ambrose, David M.;Camassa, Roberto;Marzuola, Jeremy L.;McLaughlin, Richard M.;Robinson, Quentin;Wilkening, Jon
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).
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影响因子:
4.1
作者:
Bradley Froehle;P. Persson
通讯作者:
P. Persson
DOI:
--
发表时间:
2010
影响因子:
11.1
作者:
D. Ambrose;J. Wilkening
通讯作者:
J. Wilkening
影响因子:
3.7
作者:
L. Forbes
通讯作者:
L. Forbes
影响因子:
3.7
作者:
R. Moreira;D. Peregrine
通讯作者:
D. Peregrine
影响因子:
3.7
作者:
G. El;R. Grimshaw;N. F. Smyth
通讯作者:
N. F. Smyth