Determination of moment, shear and ductility capacities of spiral columns by intelligent system

Abstract Intelligent systems are frequently used to solve difficult and complex problems in today's world. Especially in the discipline of civil engineering, much research has been conducted with the help of intelligent systems. The objective of this study is to identify the moment and shear force bearing capacities of reinforced concrete spiral columns and their displacement ductility values by using an algorithm based on an Artificial Neural Network (ANN). In the study, 86 different spiral column experiments tested in the literature were compiled and the moment and shear force bearing capacities obtained through experiments were arranged at a certain level. In addition, the ductility values of the tested columns were calculated using experimental graphical data. The output layer consists of four neural network models which are ANN 1 (with three output neurons), ANN 2 , ANN 3, and ANN 4 (with one output neurons) and moment, shear force bearing capacity and displacement ductility parameters were obtained, respectively. According to results of the study, it was observed that moment and shear force capacities of spiral columns could be particularly estimated with a high success ratio using ANN. However, it was found that the estimation of ductility is rather difficult due to approximations in acceptances.