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

Authors:
A. Batou;C. Soize;M. Corus
Affiliations:
Université Paris-Est, Laboratoire Modélisation et Simulation Multi Echelle, MSME UMR 8208 CNRS, 5 bd Descartes, 77454 Marne-la-Vallee, France;Université Paris-Est, Laboratoire Modélisation et Simulation Multi Echelle, MSME UMR 8208 CNRS, 5 bd Descartes, 77454 Marne-la-Vallee, France;LaMSID, CNRS-EDF, UMR 2832, 1 avenue du général De Gaulle, 92140 Clamart, France
Venue:
Computers and Structures
Year:
2011

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Abstract

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.