High order linearly implicit methods for evolution equations: How to solve an ODE by inverting only linear systems - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2019

High order linearly implicit methods for evolution equations: How to solve an ODE by inverting only linear systems

Résumé

This paper introduces a new class of numerical methods for the time integration of evolution equations set as Cauchy problems of ODEs or PDEs. The systematic design of these methods mixes the Runge-Kutta collocation formalism with collocation techniques, in such a way that the methods are linearly implicit and have high order. The fact that these methods are implicit allows to avoid CFL conditions when the large systems to integrate come from the space discretization of evolution PDEs. Moreover, these methods are expected to be efficient since they only require to solve one linear system of equations at each time step, and efficient techniques from the literature can be used to do so. After the introduction of the methods, we set suitable definitions of consistency and stability for these methods. This allows for a proof that arbitrarily high order linearly implicit methods exist and converge when applied to ODEs. Eventually, we perform numerical experiments on ODEs and PDEs that illustrate our theoretical results for ODEs, and compare our methods with standard methods for several evolution PDEs.
Fichier principal
Vignette du fichier
manuscript.pdf (555.49 Ko) Télécharger le fichier
svglov3.clo (3.72 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02361814 , version 1 (14-11-2019)
hal-02361814 , version 2 (22-10-2020)
hal-02361814 , version 3 (17-11-2021)

Identifiants

Citer

Guillaume Dujardin, Ingrid Lacroix-Violet. High order linearly implicit methods for evolution equations: How to solve an ODE by inverting only linear systems. 2019. ⟨hal-02361814v1⟩
220 Consultations
415 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More