TY - JOUR ID - 115527 TI - Modeling of Confined Circular Concrete Columns Wrapped by Fiber Reinforced Polymer Using Artificial Neural Network JO - Journal of Soft Computing in Civil Engineering JA - SCCE LA - en SN - AU - Abbaszadeh, Mahdi A. AU - Sharbatdar, Mohammad Kazem AD - Department of Civil Engineering, Malard Branch, Islamic Azad University, Malard, Iran AD - Associate Professor, Faculty of Civil Engineering, Semnan University, Semnan, Iran Y1 - 2020 PY - 2020 VL - 4 IS - 4 SP - 61 EP - 78 KW - Concrete columns KW - CFRP KW - Confinement KW - Artificial Neural Networks KW - Models DO - 10.22115/scce.2020.213196.1153 N2 - This study is aimed to explore using an artificial neural network method to anticipate the confined compressive strength and its corresponding strain for the circular concrete columns wrapped with FRP sheets. 58 experimental data of circular concrete columns tested under concentric loading were collected from the literature. The experimental data is used to train and test the neural network. A comparative study was also carried out between the neural network model and the other existing models. It was found that the fundamental behavior of confined concrete columns can logically be captured by the neural network model. Besides, the neural network approach provided better results than the analytical and experimental models. The neural network-based model with R2 equal to 0.993 and 0.991 for training and testing the compressive strength, respectively, shows that the presented model is a practical method to predict the confinement behavior of concrete columns wrapped with FRP since it provides instantaneous result once it is appropriately trained and tested. UR - https://www.jsoftcivil.com/article_115527.html L1 - https://www.jsoftcivil.com/article_115527_fba3e1efd17167af0a3f779755abefdb.pdf ER -