A variable high-order shock-capturing finite difference method with GP-WENO

Abstract

We present a new finite difference shock-capturing scheme for hyperbolic equations on static uniform grids. The method provides selectable high-order accuracy by employing a kernel-based Gaussian Process (GP) data prediction method which is an extension of the GP high-order method originally introduced in a finite volume framework by the same authors. The method interpolates Riemann states to high order, replacing the conventional polynomial interpolations with polynomial-free GP-based interpolations. For shocks and discontinuities, this GP interpolation scheme uses a nonlinear shock handling strategy similar to Weighted Essentially Non-oscillatory (WENO), with a novelty consisting in the fact that nonlinear smoothness indicators are formulated in terms of the Gaussian likelihood of the local stencil data, replacing the conventional $L_2$-type smoothness indicators of the original WENO method. We demonstrate that these GP-based smoothness indicators play a key role in the new algorithm, providing significant improvements in delivering high -- and selectable -- order accuracy in smooth flows, while successfully delivering non-oscillatory solution behavior in discontinuous flows.

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• An Application of Gaussian Process Modeling for High-order Accurate Adaptive Mesh Refinement Prolongation
• A Simulation Study of Ultra-Relativistic Jets -- I. A New Code for Relativistic Hydrodynamics
• Superconvergent Non-Polynomial Approximations