An adaptive model reduction strategy for post-buckling analysis of stiffened structures

Abstract : The finite element simulation of structures subjected to post-buckling still faces computational limits, especially for large stiffened structures. Several solving strategies have already been proposed in response to this issue. Among them are the adaptive model reduction solving techniques which demonstrated their ability to drastically reduce the number of unknowns as well as to control the approximation error of solving non-linear problems like post-buckling. The challenges regarding these techniques are the computation of a reduced basis at lower cost, the use of an efficient adaptive procedure and the limitation of the number of call to the adaptive procedure. This paper proposes a Post-Buckling Adaptive Model Reduction (PBAMR) strategy, which requires only two initial Ritz vectors without compromising the accuracy of the simulation. This solving method is tested in the case of shear of a stiffened panel.
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Submitted on : Tuesday, October 8, 2013 - 10:01:35 AM
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Ludovic Barrière, Steven Marguet, Bruno Castanié, Philippe Cresta, Jean-Charles Passieux. An adaptive model reduction strategy for post-buckling analysis of stiffened structures. Thin-Walled Structures, Elsevier, 2013, 73, pp.81-93. ⟨10.1016/j.tws.2013.07.009⟩. ⟨hal-00870773⟩

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