Optimal implicit strong stability preserving Runge-Kutta methods

Strong stability preserving (SSP) time discretizations were developed for use with spatial discretizations of partial differential equations that are strongly stable under forward Euler time integration. SSP methods preserve convex boundedness and contractivity properties satisfied by forward Euler,...

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Main Authors: Ketcheson, D, Macdonald, C, Gottlieb, S
Format: Journal article
Language:English
Published: 2009
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author Ketcheson, D
Macdonald, C
Gottlieb, S
author_facet Ketcheson, D
Macdonald, C
Gottlieb, S
author_sort Ketcheson, D
collection OXFORD
description Strong stability preserving (SSP) time discretizations were developed for use with spatial discretizations of partial differential equations that are strongly stable under forward Euler time integration. SSP methods preserve convex boundedness and contractivity properties satisfied by forward Euler, under a modified timestep restriction. We turn to implicit Runge-Kutta methods to alleviate this timestep restriction, and present implicit SSP Runge-Kutta methods which are optimal in the sense that they preserve convex boundedness properties under the largest timestep possible among all methods with a given number of stages and order of accuracy. We consider methods up to order six (the maximal order of SSP Runge-Kutta methods) and up to eleven stages. The numerically optimal methods found are all diagonally implicit, leading us to conjecture that optimal implicit SSP Runge-Kutta methods are diagonally implicit. These methods allow a larger SSP timestep, compared to explicit methods of the same order and number of stages. Numerical tests verify the order and the SSP property of the methods. © 2008 IMACS.
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spelling oxford-uuid:1d12067a-d9c9-4d86-8cd5-389c4909b4672022-03-26T11:08:49ZOptimal implicit strong stability preserving Runge-Kutta methodsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:1d12067a-d9c9-4d86-8cd5-389c4909b467EnglishSymplectic Elements at Oxford2009Ketcheson, DMacdonald, CGottlieb, SStrong stability preserving (SSP) time discretizations were developed for use with spatial discretizations of partial differential equations that are strongly stable under forward Euler time integration. SSP methods preserve convex boundedness and contractivity properties satisfied by forward Euler, under a modified timestep restriction. We turn to implicit Runge-Kutta methods to alleviate this timestep restriction, and present implicit SSP Runge-Kutta methods which are optimal in the sense that they preserve convex boundedness properties under the largest timestep possible among all methods with a given number of stages and order of accuracy. We consider methods up to order six (the maximal order of SSP Runge-Kutta methods) and up to eleven stages. The numerically optimal methods found are all diagonally implicit, leading us to conjecture that optimal implicit SSP Runge-Kutta methods are diagonally implicit. These methods allow a larger SSP timestep, compared to explicit methods of the same order and number of stages. Numerical tests verify the order and the SSP property of the methods. © 2008 IMACS.
spellingShingle Ketcheson, D
Macdonald, C
Gottlieb, S
Optimal implicit strong stability preserving Runge-Kutta methods
title Optimal implicit strong stability preserving Runge-Kutta methods
title_full Optimal implicit strong stability preserving Runge-Kutta methods
title_fullStr Optimal implicit strong stability preserving Runge-Kutta methods
title_full_unstemmed Optimal implicit strong stability preserving Runge-Kutta methods
title_short Optimal implicit strong stability preserving Runge-Kutta methods
title_sort optimal implicit strong stability preserving runge kutta methods
work_keys_str_mv AT ketchesond optimalimplicitstrongstabilitypreservingrungekuttamethods
AT macdonaldc optimalimplicitstrongstabilitypreservingrungekuttamethods
AT gottliebs optimalimplicitstrongstabilitypreservingrungekuttamethods