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SSPTSmethods

swMATH ID: 38981
Software Authors: Grant, Zachary; Gottlieb, Sigal; Seal, David C.
Description: A strong stability preserving analysis for explicit multistage two-derivative time-stepping schemes based on Taylor series conditions. High-order strong stability preserving (SSP) time discretizations are often needed to ensure the nonlinear (and sometimes non-inner-product) strong stability properties of spatial discretizations specially designed for the solution of hyperbolic PDEs. Multi-derivative time-stepping methods have recently been increasingly used for evolving hyperbolic PDEs, and the strong stability properties of these methods are of interest. In our prior work we explored time discretizations that preserve the strong stability properties of spatial discretizations coupled with forward Euler and a second-derivative formulation. However, many spatial discretizations do not satisfy strong stability properties when coupled with this second-derivative formulation, but rather with a more natural Taylor series formulation. In this work we demonstrate sufficient conditions for an explicit two-derivative multistage method to preserve the strong stability properties of spatial discretizations in a forward Euler and Taylor series formulation. We call these strong stability preserving Taylor series (SSP-TS) methods. We also prove that the maximal order of SSP-TS methods is (p=6), and define an optimization procedure that allows us to find such SSP methods. Several types of these methods are presented and their efficiency compared. Finally, these methods are tested on several PDEs to demonstrate the benefit of SSP-TS methods, the need for the SSP property, and the sharpness of the SSP time-step in many cases.
Homepage: https://link.springer.com/article/10.1007%2Fs42967-019-0001-3
Source Code: https://github.com/SSPmethods/SSPTSmethods
Keywords: strong stability preserving; Taylor series; hyperbolic conservation laws; two derivative Runge Kutta
Related Software: GitHub; NLopt; RIEMANN; Gmsh; KIOPS; imexLNL; ImplicitLNLMethods; phipm; Algorithm 919; Expokit; Rk-opt; RODAS; PVM
Cited in: 9 Publications

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