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Empowering Design Based on Hybrid TwinTM: Application to Acoustic Resonators

Article dans une revue avec comité de lecture
Auteur
MARTÍN, Clara Argerich
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
MÉNDEZ, Arnulfo Carazo
535967 Airbus Group Innovations [Toulouse]
SAINGES, Olivier
535967 Airbus Group Innovations [Toulouse]
PETIOT, Emilie
468139 Airbus Group
BARASINSKI, Anais
301085 Université de Pau et des Pays de l'Adour [UPPA]
PIANA, Mathieu
468139 Airbus Group
RATIER, Louis
535967 Airbus Group Innovations [Toulouse]
CHINESTA, Francisco
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]

URI
http://hdl.handle.net/10985/19483
DOI
10.3390/designs4040044
Date
2020
Journal
Designs

Résumé

In the framework of civil aviation noise levels are becoming restricted every year, on one hand to provide comfort to the passengers and on the other hand to be compliant with regulations protecting airports surroundings. New technologies are required to reduce noise to cope with this restrictions as well as to guarantee a comfortable flight for passengers. For technological industries it is compulsory to stay competitive and keep improving the technology related to air intake acoustic liners. With an unceasingly growing market, for industries it is key to stay in the vanguard of air inlet technologies, ensuring innovation and establishing a proactive environment for future product generations. One of the main objectives in this framework is the reduction of the development time of these new technologies in all the stages of the process. In this work we focus on the design stage of a new prototype and we propose a hybrid technique enabling faster design and the reduction of development time. When designing new technologies or prototypes there are usually two constraints. On one hand, more innovative prototypes may present unconventional shapes are not accurately represented by conventional physical models. On the other hand, the available data is scarce, thus limiting the use of most innovative techniques based on the state-of-art of Artificial Intelligence. In this paper we propose a solution laying in the hybrid twin paradigm, combining both, data in the low limit and physics to provide a hybrid model able to represent unconventional and innovative acoustic solutions.

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