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An artificial viscosity approach to high order entropy stable discontinuous Galerkin methods
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Entropy stable discontinuous Galerkin (DG) methods improve the robustness of high order DG simulations of nonlinear conservation laws. These methods yield a semi-discrete entropy inequality, and rely on an algebraic flux differencing formulation which involves both summation-by-parts (SBP) discretization matrices and entropy conservative two-point finite volume fluxes. However, explicit expressions for such two-point finite volume fluxes may not be available for all systems, or may be computationally expensive to compute. This paper proposes an alternative approach to constructing entropy stable DG methods using an entropy correction artificial viscosity, where the artificial viscosity coefficient is determined based on the local violation of a cell entropy inequality and the local entropy dissipation. The resulting method is a modification of the entropy correction introduced by Abgrall, Offner, and Ranocha (2022) in "Reinterpretation and Extension of Entropy Correction Terms for Residual Distribution and Discontinuous Galerkin Schemes: Application to Structure Preserving Discretization", and recovers the same global semi-discrete entropy inequality that is satisfied by entropy stable flux differencing DG methods. The entropy correction artificial viscosity coefficients are parameter-free and locally computable over each cell, and the resulting artificial viscosity preserves both high order accuracy and a hyperbolic maximum stable time-step size under explicit time-stepping.
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Cited by 2 Pith papers
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Entropy stable finite difference methods via entropy correction artificial viscosity and knapsack limiting
Two finite difference schemes, one using entropy-correction artificial viscosity and one using knapsack limiting, satisfy discrete entropy inequalities; the knapsack variant also provably preserves positivity for the ...
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Entropy Stable Nodal Discontinuous Galerkin Methods via Quadratic Knapsack Limiting
A quadratic knapsack objective for subcell limiting in entropy-stable DG methods is reduced to finite-iteration scalar root-finding and shown to improve temporal regularity and reduce adaptive timestep counts.
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