4.7 Article

A residual-based artificial viscosity finite difference method for scalar conservation laws

期刊

JOURNAL OF COMPUTATIONAL PHYSICS
卷 430, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcp.2020.110100

关键词

High-order finite difference methods; Conservation laws; Shock-capturing; Artificial viscosity; Residual-based error estimator; SBP-SAT

资金

  1. Uppsala University

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This paper presents an accurate, stable, and robust shock-capturing finite difference method for solving scalar non-linear conservation laws. The method utilizes high-order accurate upwind finite difference operators, residual-based error estimators for shock detection, and first-order viscosity in regions with strong discontinuities. The method also includes additional damping of spurious oscillations from high-order dissipation, showing stability for skew-symmetric discretizations. Accuracy and robustness are demonstrated through solving benchmark problems with convex and non-convex fluxes in 2D.
In this paper, we present an accurate, stable and robust shock-capturing finite difference method for solving scalar non-linear conservation laws. The spatial discretization uses high-order accurate upwind summation-by-parts finite difference operators combined with weakly imposed boundary conditions via simultaneous-approximation-terms. The method is an extension of the residual-based artificial viscosity methods developed in the finite- and spectral element communities to the finite difference setting. The three main ingredients of the proposed method are: (i) shock detection provided by a residual-based error estimator; (ii) first-order viscosity applied in regions with strong discontinuities; (iii) additional dampening of spurious oscillations provided by high-order dissipation from the upwind finite difference operators. The method is shown to be stable for skew-symmetric discretizations of the advective flux. Accuracy and robustness are shown by solving several benchmark problems in 2D for convex and non-convex fluxes. (C) 2020 The Author(s). Published by Elsevier Inc.

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