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    Post-Buckling Optimisation of Composite Stiffened Panels Using Neural Networks

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    This paper deals with the definition of a post-buckling optimisation procedure for the design of composite stiffened panels subjected to compression loads. The optimised structures are then characterised by a local skin buckling between the stiffeners and by a high ratio between the collapse load and the buckling load. To overcome too expensive analyses from a computational point of view, an optimisation procedure is developed. It is based on a global approximation strategy, where the structure response is given by a system of neural networks trained by means of finite element analyses, and on genetic algorithms, that results particularly profitable due to the presence of integer variables. The optimisation procedure reduces considerably the computational costs, offers a complete separation between the system modelling and the optimisation problem and shows that a local skin buckling between the stiffeners allows a weight reduction equal to 18%

    Application of an Iterative Global Approximation Technique to Structural Optimizations

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    An iterative global approximation technique based on the Kriging method is proposed. The technique is validated through analytical test cases and then applied to solve two practical optimization problems: the optimization of aluminium-foam filled absorbers against crashworthiness requirements and the optimization of composite stiffened panels against buckling and strength constraints. The absorbers of the first application consist of two co-axial aluminium alloy tubes filled with lightweight aluminium foam. They were optimized to collapse at a controlled force level and to be the lightest possible. Explicit Finite element analyses were performed to evaluate the structural behavior of the absorbers in the sample points used to build the approximation. In the second application stiffened panels were optimized against buckling and strength constraints. The Tsai-Wu criterion was used to estimate first-ply failures as strength limit of the structure. Non-linear Riks analyses were performed with ABAQUS/Standard to evaluate the shell behavior in the sample points used to build the response surfaces. Basing on the obtained results the proposed iterative procedure seems a promising alternative to the classic a-priori building of response surface allowing better accuracy and saving of sample points
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