The plastic hinge length prediction of RC members by using ANN

For many years, plastic hinges have been a very interesting and complex topic for researchers and engineers due to plastic deformations. The prediction of plastic hinge length is difficult since it depends on the characteristics' parameters of both the concrete and the reinforcement. This study aims to analyze studies and formulas used for the calculation of plastic hinges in reinforced concrete (RC) columns and RC shear walls. In addition, this study also evaluated the effect of plastic hinge behavior on other structural members. In addition, the data for columns and/or shear walls included in the literature have been evaluated in order to develop a unique formula that anticipates the length of plastic hinges of columns and/or shear walls. In this study, the use of Levenberg-Marquardt Algorithm based on artificial neural network (ANN) models in estimating the plastic hinge length of columns and shear walls was investigated. It was observed that the R2 values of the model outputs are greater than 0.98. It has been determined that the developed ANN model is a practical and useful method for estimating the plastic hinge length of columns and shear walls, both.