Uncertainty Quantification in Vibroacoustic Analysis of a Vehicle Body Using Generalized Polynomial Chaos Expansion

It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications. The investigations reveal that the gPC expansion is reliably applicable in industrial models. However, the accuracy of the non-intrusive based gPC method highly depends on the selection of the collocation points. Using the right choice of collocation points, a first order gPC expansion leads to very accurate results compared to sampling based approaches. Consequently, the gPC methodology allows to efficiently predict uncertainties in industrial models, even with a high number of uncertain parameters.