Generalized summation by parts operators: Second derivative and time-marching methods

David C. Del Rey Fernández*, Pieter D. Boom, David W. Zingg

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    This paper describes extensions of the generalized summation-by-parts (GSBP) framework to the approximation of the second derivative with a variable coefficient and to time integration. GSBP operators for the second derivative lead to more efficient discretizations, relative to the classical finite-difference SBP approach, as they can require fewer nodes for a given order of accuracy. Similarly, for time integration, time-marching methods based on GSBP operators can be more efficient than those based on classical SBP operators, as they minimize the number of solution points which must be solved simultaneously. Furthermore, we demonstrate the link between GSBP operators and Runge-Kutta time-marching methods.

    Original languageEnglish
    Title of host publicationSpectral and High Order Methods for Partial Differential Equations, ICOSAHOM 2014, Selected papers from the ICOSAHOM
    EditorsRobert M. Kirby, Martin Berzins, Jan S. Hesthaven
    PublisherSpringer Nature
    Pages207-215
    Number of pages9
    ISBN (Print)9783319197999
    DOIs
    Publication statusPublished - 1 Jan 2015
    Event10th International Conference on Spectral and High-Order Methods, ICOSAHOM 2014 - Salt Lake City, United States
    Duration: 23 Jun 201427 Jun 2014

    Publication series

    NameLecture Notes in Computational Science and Engineering
    Volume106
    ISSN (Print)1439-7358

    Conference

    Conference10th International Conference on Spectral and High-Order Methods, ICOSAHOM 2014
    Country/TerritoryUnited States
    CitySalt Lake City
    Period23/06/1427/06/14

    Fingerprint

    Dive into the research topics of 'Generalized summation by parts operators: Second derivative and time-marching methods'. Together they form a unique fingerprint.

    Cite this