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Statistical riemann problems and a composition law for errors in numerical solutions of shock physics problems

  • James Glimm
  • , John W. Grove
  • , Yonghee Kang
  • , Taewon Lee
  • , Xiaolin Li
  • , David H. Sharp
  • , Yan Yu
  • , Kenny Ye
  • , Ming Zhao
  • Los Alamos National Laboratory
  • Stony Brook University

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

We seek error models for shock physics simulations that are robust and understandable. The purpose of this paper is to formulate and validate a composition law to estimate errors in the solutions of composite problems in terms of the errors from simpler ones. We illustrate this idea in a simple context. This paper employs several simplifying assumptions (restriction to one spatial dimension, use of a simplified (gamma law) equation of state, and consideration of a single numerical method). In separate papers we will address the effect of these assumptions.

Original languageEnglish
Pages (from-to)666-697
Number of pages32
JournalSIAM Journal on Scientific Computing
Volume26
Issue number2
DOIs
StatePublished - 2005

Keywords

  • Composition law
  • Error model
  • Riemann problem
  • Uncertainty quantification

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