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An efficient application of Bayesian optimization to an industrial MDO framework for aircraft design

Priem, Rémy and Gagnon, Hugo and Chittick, Ian and Dufresne, Stephane and Diouane, Youssef and Bartoli, Nathalie An efficient application of Bayesian optimization to an industrial MDO framework for aircraft design. (2020) In: AIAA AVIATION 2020 FORUM, 15 June 2020 - 19 June 2020 (United States).

(Document in English)

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Official URL: https://doi.org/10.2514/6.2020-3152


The multi-level, multi-disciplinary and multi-fidelity optimization framework developed at Bombardier Aviation has shown great results to explore efficient and competitive aircraft configurations. This optimization framework has been developed within the Isight software, the latter offers a set of ready-to-use optimizers. Unfortunately, the computational effort required by the Isight optimizers can be prohibitive with respect to the requirements of an industrial context. In this paper, a constrained Bayesian optimization optimizer, namely the super efficient global optimization with mixture of experts, is used to reduce the optimization computational effort. The obtained results showed significant improvements compared to two of the popular Isight optimizers. The capabilities of the tested constrained Bayesian optimization solver are demonstrated on Bombardier research aircraft configuration study cases.

Item Type:Conference or Workshop Item (Paper)
Additional Information:VIRTUAL EVENT
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
French research institutions > Office National d'Etudes et Recherches Aérospatiales - ONERA (FRANCE)
Other partners > Bombardier Inc. (CANADA)
Laboratory name:
Deposited On:30 Jun 2020 15:09

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