Application of Artificial Neural Network to Analyze Hexagonal Plate with Hole Considering Different Geometrical and Loading Parameters

Saket Rusia, K. K. Pathak

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Artificial Neural Networks; Finite Element Analysis; Hexagonal Plate; ANSYS


In the competitive nature of structural engineering, industry and its heuristic problem-solving needs, among other reasons, have contributed to the development of some advanced decision making tools. A step ahead from soft computing techniques, now artificial intelligence has proved itself as an efficient tool for solving the problem in construction industry over old tedious analytical methods. In this study, Artificial Neural Network is compared with finite element techniques in order to find the stress, strain and deflection in plates with holes. For approaching the complexity of the problem, hexagonal plates with holes and different geometrical and loading parameters have been taken as specimens. Finite element analysis for 81 cases are carried out using the software based on finite element method (FEM), ANSYS Workbench 15.0 software. Using these data of FEM analysis an Artificial Neural Network has been trained. The successfully trained network is further used for analysis of four new cases which are also validated by using FEM based software. It was found that most of the results were quite close to the FEM results. Such a technique can be used to reduce the computation time and labour.

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