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Poster communications

Adaptive Model Reduction for Local Post-Buckling Analysis

Abstract : Large aeronautical stiffened structures are subjected to local static instabilities like buckling. On the first hand this phenomenon does not lead directly to failure, but it changes the stress distribution and may initiate damages like skin-stiffener debonding. On second hand, mass can be saved by allowing local post-buckling behavior in the working range of the structure. The best way to achieve local post-buckling oriented sizing of structures is to perform large scale non-linear analysis (sereval millions of degrees of freedom) in order to predict local-global interactions and damage initiation. As computational cost is limiting, an adaptive model reduction strategy is proposed and then combined with a domain decomposition method, rationalising expensive computation steps
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Contributor : Pierre Naegelen <>
Submitted on : Monday, July 15, 2019 - 2:18:53 PM
Last modification on : Wednesday, June 24, 2020 - 4:18:57 PM


  • HAL Id : hal-02183553, version 1


L. Barrière, Jean-Charles Passieux, Steven Marguet, Bruno Castanié, P. Cresta. Adaptive Model Reduction for Local Post-Buckling Analysis. 2nd International Workshop on Reduced Basis, POD and PGD model (Blois, Fr), 2013, Blois, France. 2013. ⟨hal-02183553⟩



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