ANALYSIS OF THICK PLATES ON ELASTIC FOUNDATION BY BACK-PROPAGATION ARTIFICIAL NEURAL NETWORK USING ONE PARAMETER FOUNDATION MODEL

In this study, the purpose of this paper is prediction of nondimensional maximum displacement and bending moments of thick plates on Winkler-type elastic foundation using Artificial Neural Network. For this purpose, training and testing database were created by using a computer software, coded in Fortran, based on Finite Element Model. An eight-noded (PBQ8) quadrilateral finite element based on Mindlin plate theory and Winkler foundation model are adopted for the finite element solution. Nondimensional subgrade reaction modulus, span/thickness ratio of the plate and aspect ratio of the plate were considered as input parameters and nondimensional vertical displacement and bending moments of thick plates were considered as output parameters. It is seen that the solutions by ANN agree very well with the solutions by FEM, and ANN significantly reduces analysis time

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