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Efficient Entropy-Stable Discontinuous Spectral-Element Methods Using Tensor-Product Summation-by-Parts Operators on Triangles and Tetrahedra
Tristan Montoya, David W. Zingg
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We present a new class of efficient and robust discontinuous spectral-element methods of arbitrary order for nonlinear hyperbolic systems of conservation laws on curved triangular and tetrahedral unstructured grids. Such discretizations employ a recently introduced family of sparse tensor-product summation-by-parts (SBP) operators in collapsed coordinates within an entropy-stable modal formulation. The proposed algorithms exploit the structure of such SBP operators alongside that of the Proriol-Koornwinder-Dubiner polynomial basis, and a weight-adjusted approximation is used to efficiently invert the local mass matrix for curvilinear elements. Using such techniques, the number of required entropy-conservative two-point flux evaluations between pairs of quadrature nodes is significantly reduced relative to existing entropy-stable formulations using (non-tensor-product) multidimensional SBP operators, particularly for high polynomial degrees, with an improvement in time complexity from 𝒪(p²ᵈ) to 𝒪(pᵈ⁺¹), where p is the polynomial degree of the approximation and d is the number of spatial dimensions. In numerical experiments involving smooth solutions to the compressible Euler equations, the proposed tensor-product schemes demonstrate similar levels of accuracy for a given mesh and polynomial degree to those using multidimensional SBP operators based on symmetric quadrature rules. Furthermore, both operator families are shown to give rise to entropy-stable methods which exhibit excellent robustness for under-resolved problems. Such results suggest that the algorithmic advantages resulting from the use of tensor-product operators are obtained without compromising accuracy or robustness, enabling the efficient extension of the benefits of entropy stability to higher polynomial degrees than previously considered for triangular and tetrahedral elements.
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