Evaluation of Ultimate Torsional Strength of Reinforcement Concrete Beams Using Finite Element Analysis and Artificial Neural Network

Calculation of torsional strength of reinforcement concrete members due to the lacks of the theory of elasticity is a difficult task. Therefore, the finite element analysis could be applied to determination ofstrength of concrete beams. As well, for modeling of complicated, highly nonlinear and ambiguousphenomena, artificial neural networks (ANN) are appropriate tools. The main purpose of this paper is an evaluation of ultimate torsional strength of rectangular concrete beams. A three-dimensional finiteelement model (FEM) along with establishing the artificial neural network is used for achieving thisaim. The finite element model utilizes the brittle failure criterion for concrete fracture, and experimental data are applied for training of the ANN.The commercial software is used for numerical modeling, and existing experimental tests are used in validation of the proposed failure criterion. In order to apply the data for training of the network, they are divided into three categories: training, testing and validating data. For training of the proposed network, three-layer perceptron network with a back propagation error algorithm is used. Comparison of accuracies for applied failure criterion in the numerical modeling, and neural network predictions are carry out using the experimental tests.

Keywords:

Ultimate Torsional Strength , Finite Element Modeling , Brittle Failure Criterion , Artificial Neural Network , Concrete Reinforcement Beams