Study of the behavior of eccentrically-loaded fiber-reinforced polymer (FRP) confined RC columns using a novel approach based on probabilistic gene expression programming

Fiber-reinforced polymer (FRP) confining of reinforced concrete columns (RCCs) is a widely adopted strengthening technique in civil engineering. However, accurately predicting the axial strength and ductility of eccentrically-loaded FRP-confined RCC remains a challenge. In this study, finite element models (FEM) were employed in conjunction with a novel approach of gene expression programming (GEP)-probabilistic based modeling to develop predictive models for the axial strength and ductility of eccentrically-loaded FRP-confined circular RCCs. Extensive FEM simulations were conducted, considering various input parameters such as eccentricity-to-section diameter ratios, height-to-section diameter ratios, concrete cover to diameter, concrete compressive strength, FRP layer thickness, and reinforcement ratios. The study pursues three main objectives: first, to assess the stress–strain behavior of FRP-confined RCCs and analyze the effects of various input parameters on their axial strength, axial and lateral strains, and ductility; second, to develop mathematical equations using the GEP algorithm to estimate the axial strength and ductility based on input variables such as eccentricity-to-section diameter ratios, concrete compressive strength, FRP layer thickness, and reinforcement ratios; and third, to conduct probabilistic evaluation and analysis of uncertainties in the predictions resulting from the GEP models. The resulting database facilitated the development of data-driven models, achieving correlation coefficients of 0.943 and 0.947 for axial strength and ductility, respectively. External validation and sensitivity analyses demonstrated the superior performance and accuracy of the proposed models compared to existing literature models. Additionally, a semi- and full-probabilistic approach was implemented to account for uncertainties in input variables, yielding probability distributions for GEP-based models of axial strength and ductility. These distributions enable the assessment of associated risks and aid in informed decision-making for design and structural solutions. Overall, the developed models offer valuable tools for design purposes and contribute to advancing the understanding and optimization of FRP-confined RC column behavior under eccentric loading conditions.