Applications of Gene Expression Programming for Estimating CFRP Wrapping Effects on the Bond Strength After Elevated Temperature Exposure

Abstract

The study reports on the proposed gene expression programming (GEP) to predict the ability of CFRP wrapping to enhance the post-heated bond strength between steel rebar and concrete. For this purpose, the results of 80 pullout specimens (150×150×250 mm) were selected in two categories of compressive strength of concrete: C30 and C40. In the experiments, a 20 mm rebar was placed in the corner of each specimen with a 25- or 35-mm clear cover and 200 mm of bond length. The specimens were subjected to different levels of heat before using CFRP jackets. The exposure to heat reduced the concrete-rebar bond strength; however, confinement with CFRP jackets significantly improved the bond strength between steel rebar and concrete. The estimated bond strength could be predicted by the accuracy and high prediction ability of the proposed model. Based on the findings, machine learning can bring significant improvements and benefits to the civil engineering industry in terms of the estimation of the mechanical properties of the materials in various conditions.