Tensor-Product Split-Simplex Summation-By-Parts Operators

Fuente: arXiv
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Main Authors: Worku, Zelalem Arega, Hicken, Jason E., Zingg, David W.
Format: Preprint
Published: 2024
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author Worku, Zelalem Arega
Hicken, Jason E.
Zingg, David W.
author_facet Worku, Zelalem Arega
Hicken, Jason E.
Zingg, David W.
contents We present an approach to construct efficient sparse summation-by-parts (SBP) operators on triangles and tetrahedra with a tensor-product structure. The operators are constructed by splitting the simplices into quadrilateral or hexahedral subdomains, mapping tensor-product SBP operators onto the subdomains, and assembling back using a continuous-Galerkin-type procedure. These tensor-product split-simplex operators do not have repeated degrees of freedom at the interior interfaces between the split subdomains. Furthermore, they satisfy the SBP property by construction, leading to stable discretizations. The accuracy and sparsity of the operators substantially enhance the efficiency of SBP discretizations on simplicial meshes. The sparsity is particularly important for entropy-stable discretizations based on two-point flux functions, as it reduces the number of two-point flux computations. We demonstrate through numerical experiments that the operators exhibit efficiency surpassing that of the existing dense multidimensional SBP operators by more than an order of magnitude in many cases. This superiority is evident in both accuracy per degree of freedom and computational time required to achieve a specified error threshold.
format Preprint
id arxiv_https___arxiv_org_abs_2408_10494
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Tensor-Product Split-Simplex Summation-By-Parts Operators
Worku, Zelalem Arega
Hicken, Jason E.
Zingg, David W.
Numerical Analysis
We present an approach to construct efficient sparse summation-by-parts (SBP) operators on triangles and tetrahedra with a tensor-product structure. The operators are constructed by splitting the simplices into quadrilateral or hexahedral subdomains, mapping tensor-product SBP operators onto the subdomains, and assembling back using a continuous-Galerkin-type procedure. These tensor-product split-simplex operators do not have repeated degrees of freedom at the interior interfaces between the split subdomains. Furthermore, they satisfy the SBP property by construction, leading to stable discretizations. The accuracy and sparsity of the operators substantially enhance the efficiency of SBP discretizations on simplicial meshes. The sparsity is particularly important for entropy-stable discretizations based on two-point flux functions, as it reduces the number of two-point flux computations. We demonstrate through numerical experiments that the operators exhibit efficiency surpassing that of the existing dense multidimensional SBP operators by more than an order of magnitude in many cases. This superiority is evident in both accuracy per degree of freedom and computational time required to achieve a specified error threshold.
title Tensor-Product Split-Simplex Summation-By-Parts Operators
topic Numerical Analysis
url https://arxiv.org/abs/2408.10494