Uncertainty Quantification for Nonlinear Reduced-Order Elasto-Dynamics Computational Models
The present work presents an improvement of a computational methodology for the uncertainty quantification of structures in presence of geometric nonlinearities. The implementation of random uncertainties is carried out through the nonparametric probabilistic framework from a nonlinear reduced-order model. With such usual modeling, it is difficult to analyze the influence of uncertainties on the nonlinear part of the operators with respect to its linear counterpart. In order to address this problem, an approach is proposed to take into account uncertainties for both the linear and the nonlinear operators. The methodology is then validated in the context of the linear and nonlinear mistuning of an industrial integrated bladed-disk.
KeywordsMistuning Geometric nonlinearities Uncertainties Reduced-order model Structural dynamics
This work was supported by the DGA (French defence procurement agency) in the context of the TURBODYNA project (project number ANR-13-ASTR-0008-01) related to the ANR ASTRID research program (specific support scheme for research works and innovation defence). SAFRAN Turbomeca is also acknowledged for giving permission to publish this work.
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