Strength enhancement modeling of concrete cylinders confined with CFRP composites using artificial neural networks

Enhancement of strength and ductility is the main reason for the extensive use of fiber reinforced polymer (FRP) jackets to provide external confinement to reinforced concrete columns especially in seismic areas. Therefore, numerous researches have been carried out in order to provide a better description of the behavior of FRP-confined concrete for practical design purposes.This study presents a new approach to obtain strength enhancement of concrete cylinders confined with carbon fiber reinforced polymer (CFRP) composites by applying artificial neural networks (ANNs). The proposed ANN model is based on experimental results collected from literature. It represents the ultimate strength of concrete cylinders after CFRP confinement which is also given in explicit form in terms of geometrical and mechanical parameters. The accuracy of the proposed ANN model is quite satisfactory as compared to experimental results. Moreover the results of proposed ANN model are compared with five important theoretical models proposed by researchers so far and considered to be in good agreement.