Abstract
Validation of computational models with multiple correlated functional responses requires the consideration of multivariate data correlation and uncertainty, and objective robust metrics. This paper presents a reliability based model validation method together with Probabilistic Principal Component Analysis (PPCA) to address these critical issues. The PPCA is employed to address multivariate correlation and to reduce the dimensionality. The reliability assessment method is used to quantitatively assess the quality of multivariate dynamic systems. In addition, physics-based thresholds are defined and transformed for reliability assessment. A rear seat child restraint dynamic system with multiple functional responses is used to demonstrate this new approach.
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