In this article, an analytical formulation of the response of the coupled acoustic–structural system were performed. The reliability-based design optimization (RBDO) aims to find the best compromise between cost and safety. We present here an extension of the Hybrid Method and the Optimum Safety Factor method in case of coupled acoustic-structural problems. The Robust Hybrid Method (RHM) is then applied in order to overcome the difficulties of the other methods. Numerical examples showed the effectiveness and efficiency of the RHM on acoustic–structural systems. Results showed that the optimal solution obtained by the RHM is more reliable than the other methods.

Design optimization for cementless hip prosthesis signifies one of the key topics of research to improve its performances. However, majority of the studies have not considered the presence of uncertainties while it has been shown that a deterministic optimization leads to an unreliable design. In this paper, a multi-objective reliability-based design optimization (MORBDO) procedure is proposed for cementless hip prosthesis design. The proposed methodology consists in combining the finite element simulation (FES), surrogating techniques and optimization procedure. The constructed meta-models are validated and compared using different measures such as error predictions and cross-validation (CV). The results show that the constrained non-dominated sorting genetic algorithm (C-NSGA-II) coupled with the hybrid method (HM) was capable to generate well-distributed reliable Pareto solutions.

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.

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...

In this article, structural analysis is performed on the disk due to the brake pad actuating load. Thermal analysis is addressed on the disk to observe the maximum temperature rise after the braking operation. A reliability-based design optimization using Kriging meta-model is performed to determine the optimal reliable design. Kriging meta-model provides a more accurate approximation of the original model with 50 LHS points. The objective is to minimize the brake disk volume, whereas the constraints are to minimize its stress and temperature. The optimal design gives a minimum volume with a weight reduction of 32.67% compared to the initial model.