Variable-fidelity modeling of structural analysis of assemblies

Nicolas Courrier (), Pierre-Alain Boucard and Bruno Soulier

Journal of Global Optimization, 2016, vol. 64, issue 3, 577-613

Abstract: This paper deals with the advantages of using variable-fidelity metamodeling strategies in order to develop a valid metamodel more rapidly than by using traditional methods. In our mechanical assembly design, we use the term “variable-fidelity” in reference to the convergence (or accuracy) level of the iterative solver being used. Variable-fidelity metamodeling is a way to improve the prediction of the output of a complex system by incorporating rapidly available auxiliary lower-fidelity data. This work uses two fidelity levels, but more levels can be added. The LATIN iterative algorithm is used along with a “multiparametric” strategy to calculate the various data and their different fidelity levels by means of an error indicator. Three main categories of variable-fidelity strategies are currently available. We tested at least one method from each of these categories, which comes to a total of five methods for calculating a valid metamodel using low- and high-fidelity data. Here, our objective is to compare the performances of these five methods in solving three mechanical examples. Copyright Springer Science+Business Media New York 2016

Keywords: Metamodel; Variable-fidelity; Partially converged data; Kriging; Cokriging (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10898-015-0345-9

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