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Multi-scale analysis and optimisation of three-dimensional woven composite structures combining response surface method and genetic algorithms

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Abstract

The paper proposes an optimisation strategy for the design of structures made of three-dimensional woven composites. The knowledge of the weaving architecture is essential to properly optimise the design of the structural components subjected to specific load conditions. Owing to the hierarchy and periodicity of the textile composite materials, a multi-scale parameterisation modelling strategy combining the adoption of a representative volume element and periodic boundary conditions is employed to estimate the behaviour of stiffened panels. In order to minimise the expensive computational cost, response surface method techniques are used to generate the approximated structural responses in an efficient and applicable way. The approach here proposed consists of a multi-scale parameterization analysis strategy and an optimisation framework based on the response surface technique and genetic algorithms. The optimal design results are verified by finite element analysis proving that the response surface method integrated with genetic algorithms allows to easily investigate the influence of the fabrics constitutive parameters on the structural behaviour.

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Acknowledgements

The research leading to these results has partially received funding from the European Union’s Seventh Framework Programme [FP7/2007-2013] under grant agreement “MAPICC 3D One-shot manufacturing on large scale of 3D up graded panels and stiffeners for lightweight thermoplastic textile composite structures” No. 263159. The first author would like also to acknowledge the financial support from China Scholarship Council (CSC), No. 2011626036.

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Correspondence to Sergio Ricci.

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Fu, X., Ricci, S. & Bisagni, C. Multi-scale analysis and optimisation of three-dimensional woven composite structures combining response surface method and genetic algorithms. CEAS Aeronaut J 8, 129–141 (2017). https://doi.org/10.1007/s13272-016-0227-y

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  • DOI: https://doi.org/10.1007/s13272-016-0227-y

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