An integrated stochastic design framework that facilitates practical applications involving time-consuming CAE simulations is described. The probabilistic performance measure that addresses stochastic uncertainties in CAE modeling and simulations is used to support design decision-making. Two enabling metamodeling methods using cross-validated radial basis functions (CVRBF) and a corresponding uniform sampling method are introduced to approximate highly nonlinear CAE model input/output relationships. A vehicle restraint system example is used to demonstrate the effectiveness of the proposed framework and enabling techniques.
An Integrated Stochastic Design Framework Using Cross-Validated Multivariate Metamodeling Methods
Sae Technical Papers
SAE 2003 World Congress & Exhibition ; 2003
2003-03-03
Aufsatz (Konferenz)
Englisch
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