Testing Weighted Splitting Schemes on a One-Column Transport-Chemistry Model

Mike Botchev, István Faragó, Ágnes Havasi

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

In many transport-chemistry models, a huge system of ODE's of the advection-diffusion-reaction type has to be integrated in time. Typically, this is done with the help of operator splitting. Rosenbrock schemes combined with approximate matrix factorization (ROS-AMF) are an alternative to operator splitting which does not suffer from splitting errors. However, implementation of ROS-AMF schemes often requires serious changes in the code. In this paper we test another classical second order splitting introduced by Strang in 1963, which, unlike the popular Strang splitting, seemed to be forgotten and rediscovered recently (partially due to its intrinsic parallellism). This splitting, called symmetrically weighted sequential (SWS) splitting, is simple and straightforward to apply, independent of the order of the operators and has an operator-level parallelism. In the experiments, the SWS scheme compares favorably to the Strang splitting, but is less accurate than ROS-AMF.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsIvan Lirkov, Svetozar Margenov, Jerzy Waśniewski, Plamen Yalamov
PublisherSpringer Verlag
Pages295-302
Number of pages8
ISBN (Print)3540210903, 9783540210900
DOIs
Publication statusPublished - Jan 1 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2907
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Botchev, M., Faragó, I., & Havasi, Á. (2004). Testing Weighted Splitting Schemes on a One-Column Transport-Chemistry Model. In I. Lirkov, S. Margenov, J. Waśniewski, & P. Yalamov (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 295-302). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2907). Springer Verlag. https://doi.org/10.1007/978-3-540-24588-9_33