Random uncertainties modeling in dynamical systems

Christian Soize (1)

1 LaM - Laboratoire de Mécanique

In the introduction of this paper, we summarize the usual parametric probabilistic models for random uncertainties modeling in dynamic systems and we introduce a new nonparametric probabilistic approach. In a first part, a random matrix theory, recently developed by the author, is introduced allowing the nonparametric probabilistic approach to be constructed. This theory is compared with the usual GOE from the random matrix theory. In a second part of the paper, we present applications of this new theory for linear structural vibrations with dynamical substructuring techniques and for nonlinear transient elastodynamics.

Mots clés: uncertainty quantification; nonparametric probabilistic method; modeling errors; model uncertainties; random matrix; structural dynamics; reduced order model; ROM; uncertain computational model

Domaines: Probabilités [math.PR]; Vibrations [physics.class-ph]; Vibrations [physics.class-ph]

Christian Soize. Random uncertainties modeling in dynamical systems. Fourth International Conference on Structural Dynamics organized by the European Association for Structural Dynamics, Sep 2002, Munich, Germany. pp.13-24 (Plenary Lecture). ⟨hal-00687846⟩