Identification of stochastic loads applied to a non-linear dynamical system using an uncertain computational model and experimental responses

Anas Batou (1) , Christian Soize (1)

1 MSME - Laboratoire de Modélisation et Simulation Multi Echelle

The paper is devoted to the identification of stochastic loads applied to a non-linear dynamical system for which experimental dynamical responses are available. The identification of the stochastic load is performed using a simplified computational non-linear dynamical model containing both model uncertainties and data uncertainties. Uncertainties are taken into account in the context of the probability theory. The stochastic load which has to be identified is modelled by a stationary non-Gaussian stochastic process for which the matrix-valued spectral density function is uncertain and is then modelled by a matrix-valued random function. The parameters to be identified are the mean value of the random matrix-valued spectral density function and its dispersion parameter. The identification problem is formulated as two optimization problems using the computational stochastic model and experimental responses. A validation of the theory proposed is presented in the context of tubes bundles in Pressurized Water Reactors.

Mots clés: Uncertainty quantification; Nonlinear stochastic dynamics; Random loads; Statistical inverse problem; Stochastic structural dynamics; Stochastic dynamics; Nonparametric probabilistic approach; Model uncertainties; Modeling errors; Random matrix; Structural dynamics; Nonlinear vibrations; Random vibrations; Random excitation

Domaines: Sciences de l'ingénieur [physics]; Probabilités [math.PR]; Statistiques [math.ST]

Anas Batou, Christian Soize. Identification of stochastic loads applied to a non-linear dynamical system using an uncertain computational model and experimental responses. Computational Mechanics, 2009, 43 (4), pp.559-571. ⟨10.1007/s00466-008-0330-y⟩. ⟨hal-00684461⟩