Title: Statistical validation of simulation models

Authors: Ramesh Rebba, Shuping Huang, Yongming Liu, Sankaran Mahadevan

Addresses: Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, USA. ' Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, USA. ' Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, USA. ' Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, USA

Abstract: This paper investigates various statistical methodologies for validating simulation models in automotive design. Validation metrics to compare model prediction with experimental observation, when there is uncertainty in both, are developed. Two types of metrics based on Bayesian analysis and principal components analysis are proposed. The validation results are also compared with those obtained from classical hypothesis testing. A fatigue life prediction model for composite materials and a residual stress prediction model for a spot-welded joint are validated, using the proposed methodology.

Keywords: Bayesian statistics; fatigue life prediction; hypothesis testing; PCA; principal component analysis; model validation; simulation; automotive design; vehicle design; uncertainty; composite materials; residual stress prediction; spot welding.

DOI: 10.1504/IJMPT.2006.008280

International Journal of Materials and Product Technology, 2006 Vol.25 No.1/2/3, pp.164 - 181

Published online: 28 Nov 2005 *

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