Well-balanced adaptive compact approximate Taylor methods for systems of balance laws
H. Carrillo, E. Macca, C. Pares, G. Russo

TL;DR
This paper extends adaptive compact approximate Taylor (ACAT) methods to systems of balance laws, ensuring high-order accuracy and well-balanced properties, and demonstrates their effectiveness on various complex systems including Euler equations with gravity.
Contribution
It introduces a novel extension of ACAT methods to balance laws, incorporating well-balanced features and demonstrating their application to diverse systems.
Findings
Methods achieve high-order accuracy in numerical tests.
Well-balanced property preserves stationary solutions.
Effective for complex systems like Euler equations with gravity.
Abstract
Compact Approximate Taylor (CAT) methods for systems of conservation laws were introduced by Carrillo and Pares in 2019. These methods, based on a strategy that allows one to extend high-order Lax-Wendroff methods to nonlinear systems without using the Cauchy-Kovalevskaya procedure, have arbitrary even order of accuracy 2p and use (2p + 1)-point stencils, where p is an arbitrary positive integer. More recently in 2021 Carrillo, Macca, Pares, Russo and Zorio introduced a strategy to get rid of the spurious oscillations close to discontinuities produced by CAT methods. This strategy led to the so-called Adaptive CAT (ACAT) methods, in which the order of accuracy, and thus the width of the stencils, is adapted to the local smoothness of the solution. The goal of this paper is to extend CAT and ACAT methods to systems of balance laws. To do this, the source term is written as the derivative…
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Taxonomy
TopicsNumerical methods for differential equations · Advanced Numerical Methods in Computational Mathematics · Model Reduction and Neural Networks
