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Communication Dans Un Congrès Année : 2020

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

Résumé

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.
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Dates et versions

hal-02861588 , version 1 (09-06-2020)

Identifiants

Citer

Rémy Priem, Hugo Gagnon, Ian Chittick, Stephane Dufresne, Youssef Diouane, et al.. An efficient application of Bayesian optimization to an industrial MDO framework for aircraft design. AIAA AVIATION 2020 FORUM, Jun 2020, Inconnu, United States. ⟨10.2514/6.2020-3152⟩. ⟨hal-02861588⟩
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