Improving identifiability in model calibration using multiple responses

Paul D. Arendt, Wei Chen*, Daniel Apley

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

The use of complex computer simulations to design, improve, optimize, or simply to better understand complex systems in many fields of science and engineering is now ubiquitous. However, simulation models are never a perfect representation of physical reality. Two general sources of uncertainty that account for the differences between simulations and experiments are parameter uncertainty and model uncertainty. The former derives from unknown model parameters, while the latter is caused by underlying missing physics, numerical approximations, and other inaccuracies of the computer simulation that exist even if all of the parameters are known. To obtain knowledge of these two sources of uncertainty, data from computer simulations (usually abundant) and data from physical experiments (typically more limited) are often combined using statistical methods. Statistical adjustment of the computer simulation model to account for the two sources of uncertainty is referred to as calibration. We argue that calibration as it is typically implemented, using only a single response variable, is challenging in that it is often extremely difficult to distinguish between the effects of parameter and model uncertainty. However, many different responses (distinct responses and/or the same response measured at different spatial and temporal locations) are automatically calculated in simulations. As multiple responses generally share a mutual dependence on the unknown parameters, they provide valuable information that can improve identifiability of parameter and model uncertainty in calibration, if they are also measured experimentally. In this paper, we explore the use of multiple responses for calibration.

Original languageEnglish (US)
Title of host publicationASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2011
Pages1213-1222
Number of pages10
EditionPARTS A AND B
DOIs
StatePublished - Dec 1 2011
EventASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2011 - Washington, DC, United States
Duration: Aug 28 2011Aug 31 2011

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
NumberPARTS A AND B
Volume5

Other

OtherASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2011
CountryUnited States
CityWashington, DC
Period8/28/118/31/11

ASJC Scopus subject areas

  • Modeling and Simulation
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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    Arendt, P. D., Chen, W., & Apley, D. (2011). Improving identifiability in model calibration using multiple responses. In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2011 (PARTS A AND B ed., pp. 1213-1222). (Proceedings of the ASME Design Engineering Technical Conference; Vol. 5, No. PARTS A AND B). https://doi.org/10.1115/DETC2011-48623