A resource allocation framework for experiment-based validation of numerical models

S. Atamturktur, J. Hegenderfer, B. Williams, M. Egeberg, R. A. Lebensohn, C. Unal

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

In experiment-based validation, uncertainties and systematic biases in model predictions are reduced by either increasing the amount of experimental evidence available for model calibration-thereby mitigating prediction uncertainty-or increasing the rigor in the definition of physics and/or engineering principles-thereby mitigating prediction bias. Hence, decision makers must regularly choose between either allocating resources for experimentation or further code development. The authors propose a decision-making framework to assist in resource allocation strictly from the perspective of predictive maturity and demonstrate the application of this framework on a nontrivial problem of predicting the plastic deformation of polycrystals.

Original languageEnglish (US)
Pages (from-to)641-654
Number of pages14
JournalMechanics of Advanced Materials and Structures
Volume22
Issue number8
DOIs
StatePublished - Aug 3 2015

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Mathematics(all)
  • Materials Science(all)
  • Mechanics of Materials
  • Mechanical Engineering

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