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

Journal Article · · Numerical Methods for Partial Differential Equations
DOI:https://doi.org/10.1002/num.22480· OSTI ID:1592036
 [1];  [2]
  1. Univ. of Colorado, Boulder, CO (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Univ. of Colorado, Boulder, CO (United States)
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 L2 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 L2-coercive. Nevertheless, the L2 convergence properties of the method are discussed. Convergence can be obtained either by an explicit regularization of the functional, that provides control of the L2 norm, or by properly choosing the finite element spaces, providing implicit control of the L2 norm. Numerical results for the inviscid Burgers equation with discontinuous source terms are shown, demonstrating the L2 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. Finally, 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).
Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC52-07NA27344; NA0002376
OSTI ID:
1592036
Alternate ID(s):
OSTI ID: 1632979
Report Number(s):
LLNL-JRNL--756408; 943871
Journal Information:
Numerical Methods for Partial Differential Equations, Journal Name: Numerical Methods for Partial Differential Equations Journal Issue: 6 Vol. 36; ISSN 0749-159X
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English

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