Predicting the Ultimate Shear Capacity of Near-Surface-Mounted Fiber-Reinforced Polymer-Strengthened Reinforced Concrete Beams Using Finite Element Analysis and Gene Expression Programming

Reliable evaluation of reinforced concrete (RC) beams strengthened in shear remains challenging because of the complex interaction between concrete properties, strengthening configuration, and material characteristics. This study presents a complementary numerical and data-driven framework for near-surface-mounted (NSM) fiber-reinforced polymer (FRP)-strengthened RC beams. A validated finite element model was used to conduct a parametric study explaining how concrete compressive strength, FRP type, strengthening orientation, and FRP spacing govern the shear response, including beams with residual (post-heating) concrete properties. Independently, a Gene Expression Programming (GEP) model was developed using a database of 126 experimental beam tests collected from the published literature on undamaged and damaged strengthened beams, with damage represented through the residual concrete compressive strength; 70% of the data were used for training and 30% for validation. The proposed GEP model achieved a coefficient of determination (R2) of 0.964 for training and 0.945 for validation, and showed improved predictive accuracy compared with the ACI 440.2R provisions. Concrete strength, FRP orientation, and FRP spacing were identified as governing parameters by both the finite element study and the GEP equation. The developed GEP equation provides a practical and transparent tool for rapid prediction of shear capacity in engineering design and assessment.