A least-squares finite element method based on the Helmholtz decomposition for hyperbolic balance laws

被引:2
|
作者
Kalchev, Delyan Z. [1 ,2 ]
Manteuffel, Thomas A. [1 ]
机构
[1] Univ Colorado, Dept Appl Math, 526 UCB, Boulder, CO 80309 USA
[2] Lawrence Livermore Natl Lab, Ctr Appl Sci Comp, Livermore, CA 94550 USA
关键词
Burgers equation; conservation laws; finite element methods; Helmholtz decomposition; hyperbolic balance laws; least-squares methods; negative-norm methods; space-time discretization; weak solutions; REFINEMENT; ENTROPY; SUPG;
D O I
10.1002/num.22480
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, a least-squares finite element method for scalar nonlinear hyperbolic balance laws is proposed and studied. The approach is based on a formulation that utilizes an appropriate Helmholtz decomposition of the flux vector and is related to the standard notion of a weak solution. This relationship, together with a corresponding connection to negative-norm least-squares, is described in detail. As a consequence, an important numerical conservation theorem is obtained, similar to the famous Lax-Wendroff theorem. The numerical conservation properties of the method in this paper do not fall precisely in the framework introduced by Lax and Wendroff, but they are similar in spirit as they guarantee that when L-2 convergence holds, the resulting approximations approach a weak solution to the hyperbolic problem. The least-squares functional is continuous and coercive in an H-1-type norm, but not L-2-coercive. Nevertheless, the L-2 convergence properties of the method are discussed. Convergence can be obtained either by an explicit regularization of the functional, that provides control of the L-2 norm, or by properly choosing the finite element spaces, providing implicit control of the L-2 norm. Numerical results for the inviscid Burgers equation with discontinuous source terms are shown, demonstrating the L-2 convergence of the obtained approximations to the physically admissible solution. The numerical method utilizes a least-squares functional, minimized on finite element spaces, and a Gauss-Newton technique with nested iteration. We believe that the linear systems encountered with this formulation are amenable to multigrid techniques and combining the method with adaptive mesh refinement would make this approach an efficient tool for solving balance laws (this is the focus of a future study).
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页码:1418 / 1445
页数:28
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