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PrandtlPlane wing-box least-weight design: A multi-scale optimisation approach

Authors :: Marco Picchi Scardaoni
Enrico Panettieri
Marco Montemurro
Institut de Mécanique et d'Ingénierie (I2M)
Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Arts et Métiers Sciences et Technologies
HESAM Université (HESAM)-HESAM Université (HESAM)
Université de Pise
This paper presents part of the activities carried out within the research project PARSIFAL (PrandtlPlane ARchitecture for the Sustainable Improvement of Future AirpLanes), which has been funded by the European Union under the Horizon 2020 Research and Innovation Program (Grant Agreement n.723149).
Source :: Aerospace Science and Technology, Aerospace Science and Technology, 2020, ⟨10.1016/j.ast.2020.106156⟩
Abstract: The PrandtlPlane (PrP) aircraft wing-box least-weight design is presented in this work. This design problem is formulated as a constrained non-linear programming problem (CNLPP), by integrating static, buckling, fatigue and manufacturability requirements, under different loading conditions. The solution search is carried out by means of a suitable multi-scale optimisation (MSO) approach. The physical responses involved into the CNLPP formulation are evaluated at the wing-box architecture level (macroscopic scale) and at the stiffened panel level (component scale), as well. The scale transition is ensured by means of a suitable global-local (GL) modelling approach, while the CNLPP is solved by means of an in-house genetic algorithm. The effectiveness of the proposed approach is tested on the PrP wing-box structure, but the presented strategy can be easily extended to conventional aircraft wings. This paper presents part of the activities carried out within the research project PARSIFAL (PrandtlPlane ARchitecture for the Sustainable Improvement of Future AirpLanes), which has been funded by the European Union under the Horizon 2020 Research and Innovation Program (Grant Agreement n.723149).