Reliability based optimisation of composite plates under aeroelastic constraints via adapted surrogate modelling and genetic algorithms - Laboratoire Interdisciplinaire des Sciences du Numérique
Journal Articles Composite Structures Year : 2024

Reliability based optimisation of composite plates under aeroelastic constraints via adapted surrogate modelling and genetic algorithms

Abstract

Composite materials are vital in aerospace for their exceptional strength-to-weight ratio. This study delves into reliability-based optimisation of composite plates within aeroelastic constraints, employing an efficient global optimisation method and genetic algorithms. Initial analysis focuses on aeroelastic responses such as limit flutter speed, gust response, and static loads, emphasising maximum strain assessment. To tackle optimisation challenges of composite stacking sequences, a homogenisation technique with lamination parameters is applied. We then formulate a constrained optimisation problem to minimise gust response while meeting flutter and maximum strain constraints. Surrogate models based on conditioned Gaussian Processes are developed for each aeroelastic response, facilitating optimisation within the composite design space. These models, with potential for local refinement, expedite optimal solution identification. Further, we integrate reliability-based optimisation into the framework to determine a robust stacking sequence using genetic algorithms, accounting for random fibre orientation variations. This holistic approach integrates aeroelastic analysis, constrained optimisation, surrogate modelling, and reliability-based optimisation, proving effective in designing reliable, efficient composite structures for aerospace, thus enhancing performance and safety.
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Origin Publication funded by an institution

Dates and versions

hal-04671263 , version 1 (14-08-2024)

Identifiers

Cite

Roger Ballester Claret, Ludovic Coelho, Christian Fagiano, Cédric Julien, Didier Lucor, et al.. Reliability based optimisation of composite plates under aeroelastic constraints via adapted surrogate modelling and genetic algorithms. Composite Structures, 2024, 347, pp.118461. ⟨10.1016/j.compstruct.2024.118461⟩. ⟨hal-04671263⟩
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