Model validation via uncertainty propagation using response surface models

Lusine Baghdasaryan*, Wei Chen, Thaweepat Buranathiti, Jian Cao

*Corresponding author for this work

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


Model validation has become a primary means to evaluate accuracy and reliability of computational simulations in engineering design. Mathematical models enable engineers to establish what the most likely response of a system is. However, despite the enormous power of computational models, uncertainty is inevitable in all model-based engineering design problems, due to the variation in the physical system itself, or lack of knowledge, and the use of assumptions by model builders. Therefore, realistic mathematical models should contemplate uncertainties. Due to the uncertainties, the assessment of the validity of a modeling approach must be conducted based on stochastic measurements to provide designers with the confidence of using a model. In this paper, a generic model validation methodology via uncertainty propagation is presented. The approach reduces the number of physical testing at each design setting to one by shifting the evaluation effort to uncertainty propagation of the computational model. Response surface methodology is used to create metamodels as less costly approximations of simulation models for uncertainty propagation. The methodology is illustrated with the examination of the validity of a finite-element analysis model for predicting springback angles in a sample flanging process.

Original languageEnglish (US)
Title of host publicationProceedings of the ASME Design Engineering Technical Conference
PublisherAmerican Society of Mechanical Engineers
Number of pages12
ISBN (Electronic)0791836223
StatePublished - 2002
Event28th Design Automation Conference - Montreal, Que., Canada
Duration: Sep 29 2002Oct 2 2002

Publication series

NameProceedings of the ASME Design Engineering Technical Conference


Other28th Design Automation Conference
CityMontreal, Que.


  • Model validation
  • Response surface models
  • Sheet metal flanging
  • Uncertainty propagation

ASJC Scopus subject areas

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


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