This paper consists of evaluating the performance of a vibro-acoustic model in the presence of uncertainties in the geometric and material parameters of the model using Monte Carlo simulations (MCS). The purpose of using a meta-model is to reduce the computational cost of finite element simulations. Uncertainty analysis requires a large sample of MCS to predict the effect of uncertain parameters on the system response. So, if this study is done through the finite element method (FEM), then the computational cost will be very important. Furthermore, for that, we use meta-models to be able to conduct an efficient uncertainty analysis more quickly. In the present contribution, the approximated meta-model is verified and validated using error measures and cross-validation (CV). Then, the uncertainty analysis is performed by Monte Carlo simulations using the computed Kriging meta-model. The developed methodology has been applied in two vibro-acoustic models. In these two models, the covariance of uncertainty of geometric and physical (elasticity and density) parameters are equal to 2% and 5% respectively. The obtained results prove that the suggested methodology of uncertainty propagation based on the Kriging meta-model can be considered as a very efficient and sufficiently accurate approach for the quantification of uncertainties in acoustic-structural systems.

In Part II of the overview of structural reliability analysis methods, the category of sampling methods is reviewed. The basic Monte Carlo simulation is the foundation for sampling methods of (...)

Our work presents an overview of structural reliability analysis, which plays important roles in structural design. In Part I of the overview, the so-called local reliability methods are (...)

This work aims at increasing the performance prediction for acoustic propagation systems that will operate in the presence of the inevitable parameters uncertainty. In the present contribution, the finite element method is applied to solve an acoustic problem described by the Helmholz equation...