Towards a parallel time integration method for nonlinear systems

Paul L.C. van der Valk, Daniel J. Rixen

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

2 Scopus citations

Abstract

Obtaining the forced dynamic response of large nonlinear structural models is in practice computationally expensive. As time integration involves solving a static-like nonlinear problem at each time steps, these simulations could take up to several days to solve. In a lot of cases however, the global nonlinearity of the model could be relatively mild or parts of the model can be assumed to behave linearly and the strong nonlinearities, that require many iterations to solve, are localized in a small number of regions of the model. Normal approaches to solve this more efficiently require one to reduce the linear and/or mildly nonlinear parts of the system. In this paper however, a different approach is taken. Here we decompose the total time integration by separating the iterations required, into iterations on the global (linearized) interface problem and iterations on the (local) substructure level. It will be shown that this approach leads to a method that can be efficiently implemented in a parallel computing environment.

Original languageEnglish
Title of host publicationDynamic Behavior of Materials - Proceedings of the 2013 Annual Conference on Experimental and Applied Mechanics
PublisherSpringer New York LLC
Pages135-145
Number of pages11
ISBN (Print)9783319007700
DOIs
StatePublished - 2014
Event32nd IMAC Conference and Exposition on Structural Dynamics, 2014 - Orlando, FL, United States
Duration: 3 Feb 20146 Feb 2014

Publication series

NameConference Proceedings of the Society for Experimental Mechanics Series
Volume1
ISSN (Print)2191-5644
ISSN (Electronic)2191-5652

Conference

Conference32nd IMAC Conference and Exposition on Structural Dynamics, 2014
Country/TerritoryUnited States
CityOrlando, FL
Period3/02/146/02/14

Keywords

  • Dual assembly
  • Newmark time integration
  • Nonlinear models
  • Parallel computations
  • Simulations

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