Stochastic reduced order computational model of structures having numerous local elastic modes in low frequency dynamics

Abstract

This paper is devoted to the construction of a stochastic reduced order computational model of structures having numerous local elastic modes in low frequency dynamics. We are particularly interested in automotive vehicles which are made up of stiff parts and flexible components. 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. To solve this difficult problem, an innovative method has recently been proposed for constructing a reduced order computational dynamical model adapted to this particular situation for the low frequency range. Then a new adapted generalized eigenvalue problem is introduced and allows a global vector basis to be constructed for the global displacements space. This method requires to decompose the domain of the structure into sub-domains. Such a decomposition is carried out using the Fast Marching Method. This global vector basis is then used to construct the reduced order computational model. Since there are model uncertainties induced by modeling errors in the computational model, the nonparametric probabilistic approach of uncertainties is used and implemented in the reduced order computational model. The methodology is applied to a complex computational model of an automotive vehicle.