Identification of stochastic loads applied to a nonlinear dynamical system using an uncertain computational model

Christian Soize (1) , Anas Batou (1)

1 MSME - Laboratoire de Modélisation et Simulation Multi Echelle

This paper deals with the identification of stochastic loads applied to a nonlinear dynamical system for which a few experimental responses are available using an uncertain computational model. Uncertainties are induced by the use of a simplified computational model to predict the responses of the real system. A nonparametric probabilistic approach of both parameter uncertainties and model uncertainties is implemented in the simplified computational model in order to take into account uncertainties. The level of uncertainties is identified using the maximum likelihood method. The identified stochastic simplified computational model which is obtained is then used to perform the identification of the stochastic loads applied to the real nonlinear dynamical system. A numerical validation of the complete methodology is presented.

Mots clés: uncertainty quantification; statistical inverse problem; nonlinear structural dynamics; nonlinear vibrations; nonparametric probabilistic method; modeling errors; model uncertainties; nonlinear dynamical systems; random matrix

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

Christian Soize, Anas Batou. Identification of stochastic loads applied to a nonlinear dynamical system using an uncertain computational model. Mathematical Problems in Engineering, 2008, 2008 (), pp.181548-1-16. ⟨10.1155/2008/181548⟩. ⟨hal-00686141⟩