A Nonparametric Bootstrap Approach to Variable-size Local-domain Design Optimization and Computer Model Validation

Paper #:
  • 2012-01-0226

Published:
  • 2012-04-16
DOI:
  • 10.4271/2012-01-0226
Citation:
Drignei, D., Mourelatos, Z., Pandey, V., and Kokkolaras, M., "A Nonparametric Bootstrap Approach to Variable-size Local-domain Design Optimization and Computer Model Validation," SAE Int. J. Mater. Manf. 5(1):143-149, 2012, doi:10.4271/2012-01-0226.
Pages:
7
Abstract:
Design optimization often relies on computational models, which are subjected to a validation process to ensure their accuracy. Because validation of computer models in the entire design space can be costly, a recent approach was proposed where design optimization and model validation were concurrently performed using a sequential approach with both fixed and variable-size local domains. The variable-size approach used parametric distributions such as Gaussian to quantify the variability in test data and model predictions, and a maximum likelihood estimation to calibrate the prediction model. Also, a parametric bootstrap method was used to size each local domain. In this article, we generalize the variable-size approach, by not assuming any distribution such as Gaussian. A nonparametric bootstrap methodology is instead used to size the local domains. We expect its generality to be useful in applications where distributional assumptions are difficult to verify, or not met at all. A heat conduction problem illustrates the proposed methodology.
Access
Now
SAE MOBILUS Subscriber? You may already have access.
Buy
Select
Price
List
Download
$27.00
Mail
$27.00
Members save up to 40% off list price.
Share
HTML for Linking to Page
Page URL

Related Items

Training / Education
2015-03-31
Training / Education
1997-05-29
Training / Education
2015-04-02
Technical Paper / Journal Article
2010-10-25
Training / Education
2017-12-07
Training / Education
2017-06-15
Training / Education
1997-05-29