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Predictive Computational Science: Computer Predictions in the Presence of Uncertainty

  • University of Texas at Austin

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

46 Scopus citations

Abstract

Predictive computational science is the scientific discipline concerned with assessing the predictability of mathematical and computational models of physical events in the presence of uncertainties. It embraces the processes of model selection, statistical calibration and validation of models, model verification, and their use in forecasting features of physical events with quantified uncertainty. In this exposition, the conceptual, mathematical, and statistical foundations of predictive computational science are presented together with demonstrative applications to simple problems in structural mechanics.

Original languageEnglish
Title of host publicationEncyclopedia of Computational Mechanics
Publisherwiley
Pages1-26
Number of pages26
ISBN (Electronic)9781119176817
ISBN (Print)9781119003793
DOIs
StatePublished - Jan 1 2017

Keywords

  • Bayesian inference
  • frequentist approach
  • likelihood function
  • model calibration
  • model validation
  • OPAL
  • predictive science
  • quantity of interest

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