Stochastic reduced-order model for dynamical structures having a high modal density in the low-frequency range

A. Arnoux (1, 2) , Anas Batou (1) , Christian Soize (1) , L. Gagliardini (2)

1 MSME - Laboratoire de Modélisation et Simulation Multi Echelle
2 PSA Peugeot Citroen

This paper is devoted to the construction of stochastic reduced-order computational model for dynamical structures having a high modal density in the low-frequency range. The structure considered 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. A new approach has recently been proposed for constructing a reduced-order computational dynamical model adapted to the low-frequency range. The proposed method requires to decompose the domain of the structure into subdomains. Such a decomposition is carried out using the Fast Marching Method. An adapted generalized eigenvalue problem is constructed using such a decomposition and allows an adapted vector basis to be computed. This basis is then used to construct the reduced-order computational model. The methodology is applied on a complex computational model of an automotive vehicle.

Mots clés: uncertainty quantification; Rreduced-order model; structural dynamics; high modal density; low-frequency range

Domaines: Mécanique [physics.med-ph]; Probabilités [math.PR]; Vibrations [physics.class-ph]

A. Arnoux, Anas Batou, Christian Soize, L. Gagliardini. Stochastic reduced-order model for dynamical structures having a high modal density in the low-frequency range. Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2012), Vienna University of Technology, Sep 2012, Vienna, Austria. pp.1-2. ⟨hal-00734163⟩