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Multilevel model reduction for uncertainty quantification in computational structural dynamics

Abstract : For some complex dynamical structures exhibiting several structural scales, numerous local displacements can be intertwined with the usual global displacements, inducing an overlap of the low-, medium-, and high-frequency vibration regimes (LF, MF, HF). Hence the introduction of a multilevel reduced-order model (ROM), based on three reduced-order bases (ROBs) that are constituted of either LF-, MF-, or HF-type displacements. These ROBs are obtained using a filtering method based on global shape functions for the kinetic energy. First, thanks to the filtering of local displacements, the dimension of the multilevel ROM is reduced compared to classical modal analysis. Second, implementing the nonparametric probabilistic approach in the multilevel ROM allows each type of displacements to be affected by a particular level of uncertainties. The method is applied to a car, for which the multilevel stochastic ROM is identified with respect to experiments, solving a statistical inverse problem.
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Contributor : Olivier Ezvan <>
Submitted on : Thursday, December 15, 2016 - 6:26:42 PM
Last modification on : Tuesday, December 8, 2020 - 9:38:42 AM
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  • HAL Id : tel-01417686, version 1



Olivier Ezvan. Multilevel model reduction for uncertainty quantification in computational structural dynamics. Mechanics []. Université Paris Est, 2016. English. ⟨tel-01417686⟩



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