Presentation
The AIAA is a major player in the field of aeronautics, and this award is a “technical” prize awarded by experts such as Boeing, NASA and many others, from among a hundred or so international papers submitted.
It is an annual prize that is rarely awarded to a European player. It’s a great accolade for ISAE-SUPAERO and ONERA,” says Paul Saves.
This prize rewards the work of two ISAE-SUPAERO research departments, in numerical optimisation of the DISC (Prof. Y. Diouane), and in multidisciplinary optimal design of the DMSM (Prof. J. Morlier). The results obtained on a DRAGON-type hybrid electric aircraft are very encouraging in terms of decarbonising aviation by reducing induced pollution and fuel consumption in particular.
This prize is the fruit of a fruitful collaboration with Polytechnique Montréal and ONERA as part of Paul Saves’ doctoral thesis. It also rewards a long-standing collaboration, since 2011, between ONERA and ISAE-SUPAERO on the subject of optimisation using substitution models for MDO and aircraft design, with ONERA Toulouse research engineers Nathalie Bartoli and Thierry Lefevbre.
Solve an optimisation problem at lower computational cost
Paul wanted to work in aeronautics, and being from Toulouse, he was in the right place. After graduating from INSA GMM (Mathematical Engineering and Modelling), he did an ENAC master’s degree to work specifically on optimisation in the aeronautical field. As he was still young, he took the opportunity to do a bit of research, and it was at ISAE-SUPAERO and ONERA, which he considers to be excellent laboratories, that he found his doctoral position. His thesis is in the same field as his prize-winning paper, the pre-project optimisation of more environmentally-friendly aircraft concepts. The idea here is to digitally optimise the shape and/or electrical configurations of the aircraft as quickly as possible. A numerical calculation can be very energy- and time-intensive, and one of the subsidiary aims is to optimise the use of expensive models by evaluating them as little as possible. Optimisation has therefore been a personal theme for Paul for a long time.
The title of his thesis is Bayesian optimisation for mixed variables using an adaptive dimension reduction process: applications to aircraft design.
Paul sums up his work as follows:
“Multidisciplinary design optimisation methods aim to adapt numerical optimisation techniques to the design of engineering systems involving several disciplines. In this context, a large number of mixed continuous, integer and categorical variables may arise during the optimisation process, and practical applications involve a large number of design variables. Recently, there has been a growing interest in Bayesian mixed-variable constrained optimisation, but most existing approaches significantly increase the number of hyperparameters related to the surrogate model.”
In this paper, we address this problem by constructing substitution models that use fewer hyperparameters. The reduction process is based on the partial least squares method. An adaptive procedure for choosing the number of hyperparameters is proposed. The performance of the proposed approach is confirmed by analytical tests and by two real applications linked to aircraft design.
To find out more, his paper is available here: https://hal.archives-ouvertes.fr/hal-03514915/. And the core of the work is available as open source here: https://github.com/SMTorg/smt
This prize was the subject of an article in Aerospace America and on Aerospace Research Central. It is already listed among the best papers in MDO and aircraft design by the AIAA. A new presentation of Paul Saves’ work took place in January at the National Harbor, near Washington, in front of numerous industrialists and technical experts such as NASA and Boeing, but also non-American aerospace companies such as Airbus, Aurora, Leonardo, ATR, etc.
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