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Developing Nonlinear Behavior of Reinforced Concrete Elements Using an Intelligent Approach

In this paper, attempts are made to present an intelligent procedure, namely, least square supported vector machine (LSSVM) to provide the reinforced concrete (RC) elements’ nonlinear model. For this purpose, an existing database developed from several experiments is taken from PEER reports and a simple mathematical procedure is presented to estimate parameters of the expected model. This idealized model is capable of predicting the monotonic as well as cyclic characteristics of RC beams and columns. In order to investigate the accuracy of the proposed procedure, a RC structure with six stories is designed and the intelligent method is used to find the inelastic characteristics of the frames’ elements. Afterward, different comparisons are made between the results of the suggested procedure and the outputs of an introduced method usually used for modeling the nonlinear behavior of concrete structures. This comparison shows the good agreement between the results of the intelligent method with existing procedure. In addition, nonlinear static analysis, as well as statistics analysis, is performed to obtain median inter-story drift distribution along the height of the structure, structural members’ ductility and dissipated energy under design basis earthquake (DBE). It is revealed that the outputs of the new method have less deviation with the utilized experimental database in comparison with the other ones. Furthermore, the plastic hinges constructed by the new approach indicate more ductility and energy dissipation than the results of existing method.

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