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Robust updating of computational models with uncertainties for dynamical systems

Abstract : A probabilistic modeling of sound-insulation layers is presented in the context of computational vibroacoustics of complex systems. A sound-insulation layer can be either modeled by a full finite element model or by an equivalent acoustic wall impedance . The first one requires a large number of DOF (for instance, several millions for a car model). A simplified mean model of sound-insulation system is constructed using the fuzzy structure theory [3,4] in the context of vibroacoustics. Such an approach allows the number of DOF to be drastically reduced. In a counter part, the introduction of such a simplification introduces model uncertainties which are taken into account using a nonparametric probabilistic approach. An experimental identification of the fuzzy structure parameters (mean modal density, mass participation factor, internal damping and thickness eigenfrequency) is carried out. An application of such an experimental identification is presented for a foam-septum sound-insulation system.
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Contributor : Christian Soize <>
Submitted on : Friday, May 18, 2012 - 2:07:12 PM
Last modification on : Wednesday, February 26, 2020 - 7:06:08 PM


  • HAL Id : hal-00698949, version 1



C. Fernandez, Christian Soize, L. Gagliardini. Robust updating of computational models with uncertainties for dynamical systems. USNCCM IX 2007, Ninth U. S. National Congress on Computational Mechanics, Jul 2007, San Francisco, United States. pp.2. ⟨hal-00698949⟩



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