A semi-Lagrangian finite difference WENO scheme for scalar nonlinear conservation laws

被引:22
|
作者
Huang, Chieh-Sen [1 ]
Arbogast, Todd [2 ]
Hung, Chen-Hui [3 ]
机构
[1] Natl Sun Yat Sen Univ, Dept Appl Math, Kaohsiung 804, Taiwan
[2] Univ Texas Austin, Inst Computat Engn & Sci, 201 EAST 24th St,Stop C0200, Austin, TX 78712 USA
[3] Air Force Acad, Dept Math & Phys Sci, Sisou 1,Jieshou W Rd, Kaohsiung 82047, Taiwan
基金
美国国家科学基金会;
关键词
Hyperbolic; Semi-Lagrangian; WENO reconstruction; Eulerian-Lagrangian; Traceline; Locally frozen; EFFICIENT IMPLEMENTATION; ADVECTION; EQUATION;
D O I
10.1016/j.jcp.2016.06.027
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
For a nonlinear scalar conservation law in one-space dimension, we develop a locally conservative semi-Lagrangian finite difference scheme based on weighted essentially non-oscillatory reconstructions (SL-WENO). This scheme has the advantages of both WENO and semi-Lagrangian schemes. It is a locally mass conservative finite difference scheme, it is formally high-order accurate in space, it has small time truncation error, and it is essentially non-oscillatory. The scheme is nearly free of a CFL time step stability restriction for linear problems, and it has a relaxed CFL condition for nonlinear problems. The scheme can be considered as an extension of the SL-WENO scheme of Qiu and Shu (2011) [2] developed for linear problems. The new scheme is based on a standard sliding average formulation with the flux function defined using WENO reconstructions of (semi-Lagrangian) characteristic tracings of grid points. To handle nonlinear problems, we use an approximate, locally frozen trace velocity and a flux correction step. A special two-stage WENO reconstruction procedure is developed that is biased to the upstream direction. A Strang splitting algorithm is used for higher-dimensional problems. Numerical results are provided to illustrate the performance of the scheme and verify its formal accuracy. Included are applications to the Vlasov-Poisson and guiding-center models of plasma flow. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:559 / 585
页数:27
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