A dynamic data-driven application simulation framework for contaminant transport problems

C. C. Douglas*, Yalchin Efendiev

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

We describe, devise, and augment dynamic data-driven application simulations (DDDAS). DDDAS offers interesting computational and mathematically unsolved problems, such as, how do you analyze, compute, and predict the solution of a generalized PDE when you do not know either where or what the boundary conditions are at any given moment in the simulation in advance? A summary of DDDAS features and why this is a intellectually stimulating new field are included in the paper. We apply the DDDAS methodology to some examples from a contaminant transport problem. We demonstrate that the multiscale interpolation and backward in time error monitoring are useful to long running simulations.

Original languageEnglish (US)
Pages (from-to)1633-1646
Number of pages14
JournalComputers and Mathematics with Applications
Volume51
Issue number11
DOIs
StatePublished - Jun 1 2006

Keywords

  • Automatic model changing
  • CFD
  • DDDAS
  • Multiscale methods
  • Remote supercomputing
  • steering

ASJC Scopus subject areas

  • Modeling and Simulation
  • Computational Theory and Mathematics
  • Computational Mathematics

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