Generalized probabilistic approach of uncertainties in computational dynamics

Christian Soize (1)

1 MSME - Laboratoire de Modélisation et Simulation Multi Echelle

A new generalized probabilistic approach of uncertainties is proposed for computational model in structural linear dynamics and can be extended without difficulty to computational linear vibroacoustics and to computational nonlinear structural dynamics. This method allows the prior probability model of each type of uncertainties (model-parameter uncertainties and modeling errors) to be separately constructed and identified. The modeling errors are not taken into account with the usual output-prediction-error method but with the nonparametric probabilistic approach of modeling errors recently introduced and based on the use of the random matrix theory. The theory, an identification procedure and a numerical validation are presented.

Mots clés: uncertainty quantification; parametric probabilistic approach; nonparametric probabilistic approach; system-parameter uncertainties; model uncertainties; modeling errors; random matrix; computational dynamics

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

Christian Soize. Generalized probabilistic approach of uncertainties in computational dynamics. (Opening Keynote Lecture) First International Symposium IMPACT 2010 on "Dynamic of Systems, Materials and Structures", Mar 2010, Djerba, Tunisia. pp.1-13. ⟨hal-00692830⟩