Gradient-Enhanced Metamodels and Multiparametric Strategies for Designing Structural Assemblies

Abstract : This paper proposes a multilevel model optimization strategy for structural assemblies. The general objective is to reduce computation costs; here, we focus on the costs which are associated with the generation of metamodels. Our goal is achieved through the introduction of two main elements: the multiparametric Strategy based on the LATIN method, which reduces the computation costs when the parameters vary, and the use of gradient-based metamodels. Cokriging and radial basis functions (RBF) metamodels are presented and performance of these approximations is illustrated with analytical and mechanical examples with one to four design variables.
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https://hal.archives-ouvertes.fr/hal-01431905
Contributor : Luc Laurent <>
Submitted on : Wednesday, January 11, 2017 - 1:18:50 PM
Last modification on : Saturday, May 25, 2019 - 1:44:42 AM

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Luc Laurent, Pierre-Alain Boucard, Bruno Soulier. Gradient-Enhanced Metamodels and Multiparametric Strategies for Designing Structural Assemblies. Eleventh International Conference on Computational Structures Technology, Sep 2012, Dubrovnik, Croatia. ⟨10.4203/ccp.99.230⟩. ⟨hal-01431905⟩

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