Buckling Optimization of Composite Shells by Utilizing Finite Element Analysis, Neural Networks and Genetic Algorithm

Abstract:

The main goal in this investigation is optimization of two, four, eight and twelve layer shells in order to identify optimized fiber angle in different layers aiming maximizing critical load. In order to identify critical load parameter, a hybrid approach including Finite Element Method (FEM) and Neural Networks (NN) is employed. To achieve the above results, required data for NN is supplied by FEM and the appropriate network is trained. For optimization of obtained function, Genetic Algorithm (GA) is utilized. In this case, GA is also employed over and over in order to obtain the effect of different parameters. Furthermore, existence of several close optimized points and interactions among layers, critical load and fiber angle are discussed.

• Periodical: Advanced Materials Research (Volume 1119)
• Pages: 207-211
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1119.207
• Online since: July 2015
• Authors: Hossein Amirabadi*, Mehdi Mostofi
• Keywords: Buckling, Composite Shells, Genetic Algorithm, Neural Network, Optimization

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