Stochastic reduced-order model for an automotive vehicle in presence of numerous local elastic modes in the low-frequency range

Abstract : This paper is devoted to the construction of a stochastic reduced-order model for dynamical structures having a high modal density in the low-frequency range, such as an automotive vehicle. This type of structure is characterized by the fact that it exhibits, in the low-frequency range, not only the classical global elastic modes but also numerous local elastic modes which cannot easily be separated from the global elastic modes. An approach has recently been proposed for constructing a reduced-order computational dynamical model adapted to the low-frequency range. First, the domain of the structure is decomposed into subdomains. Then an adapted generalized eigenvalue problem is constructed using such a decomposition and allows an adapted vector basis of the global displacements space to be computed. This basis is then used to construct the reduced-order model. Model uncertainties induced by modeling errors in the computational model are taken into account using the nonparametric probabilistic approach. The methodology is applied to an automotive vehicle.