Simultaneous Bayesian Calibration and Engineering Design With an Application to a Vibration Isolation System

Carl Ehrett, D. Andrew Brown, Christopher Kitchens, Xinyue Xu, Roland Platz, Sez Atamturktur

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Calibration of computer models and the use of those design models are two activities traditionally carried out separately. This paper generalizes existing Bayesian inverse analysis approaches for computer model calibration to present a methodology combining calibration and design in a unified Bayesian framework. This provides a computationally efficient means to undertake both tasks while quantifying all relevant sources of uncertainty. Specifically, compared with the traditional approach of design using parameter estimates from previously completed model calibration, this generalized framework inherently includes uncertainty from the calibration process in the design procedure. We demonstrate our approach to the design of a vibration isolation system. We also demonstrate how, when adaptive sampling of the phenomenon of interest is possible, the proposed framework may select new sampling locations using both available real observations and the computer model. This is especially useful when a misspecified model fails to reflect that the calibration parameter is functionally dependent upon the design inputs to be optimized.

Original languageEnglish (US)
Article number011007-1
JournalJournal of Verification, Validation and Uncertainty Quantification
Volume6
Issue number1
DOIs
StatePublished - Mar 2021

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Computer Science Applications
  • Computational Theory and Mathematics

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