Experimental identification of an uncertain computational dynamical model representing a family of structures

Anas Batou (1) , Christian Soize (1) , M. Corus (2)

1 MSME - Laboratoire de Modélisation et Simulation Multi Echelle
2 LAMSID - UMR 8193 - Laboratoire de Mécanique des Structures Industrielles Durables

We are interested in constructing an uncertain computational model representing a family of structures and in identifying this model using a small number of experimental measurements of the first eigenfrequencies. The prior probability model of uncertainties is constructed using the generalized probabilistic approach of uncertainties which allows both system-parameters uncertainties and model uncertainties to be taken into account. The parameters of the prior probability model of uncertainties are separately identified for each type of uncertainties, yielding an optimal prior probability model. The optimal prior stochastic computational model allows a robust analysis for the family of structures to be carried out.

Mots clés: Uncertainty quantification; Structural dynamics; Stochastic inverse problem; Chaos representations; Maximum entropy; Random matrix; Random fields; Vibrations

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

Anas Batou, Christian Soize, M. Corus. Experimental identification of an uncertain computational dynamical model representing a family of structures. Computers & Structures, 2011, 89 (13-14), pp.1440-1448. ⟨10.1016/j.compstruc.2011.03.004⟩. ⟨hal-00684292⟩