Abstract
In this paper, a fuzzy logic (FL)-based expert system (ES) has been developed to predict the results of finite element (FE) analysis, while solving a rubber cylinder compression problem. As the performance of an ES depends on its knowledge base (KB), an attempt is made to develop the KB through three different approaches by using a genetic algorithm (GA). To collect the training data, two input parameters, namely element size and shape ratio are varied, while solving the said physical problem using an FEM package. The performance of the trained fuzzy logic-based expert system is tested for several test cases, differing significantly from the training cases. Results of these approaches are compared with those of FE analysis. Once developed, the ES is able to determine the values of parameters to be used in FE analysis, in order to obtain the results within a reasonable accuracy, at the cost of a much lower computation compared to that of the FEM package itself.
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