Predicting ultimate condition and transition point on axial stress–strain curve of FRP-confined concrete using a meta-heuristic algorithm

Accurately predicting key reference points on the axial stress–strain curve of fiber-reinforced polymer (FRP)-confined concrete is of great importance for the pre-design and modeling of structures manufactured with this composite system. This paper presents a detailed study on the development of accurate and practical expressions for predicting the ultimate condition and transition point, as key reference points, on axial stress–strain curves of FRP-confined concrete using generic programming (GP). A comprehensive data tuning and cross-validation analysis was firstly performed to develop prediction models. Afterwards, the accuracy and performance of the developed empirical expressions were examined by sensitivity analysis, parametric analysis and model validation. Finally, a comparison was made between the performance of these proposed expressions and that of the existing best-performing expressions in the literature using statistical analysis. Based on the sensitivity and parametric analysis of the database, it is shown that: compressive strength (f’_cc) and axial transition strain (ɛ_c1) are more sensitive to FRP lateral stiffness (K_l); ultimate axial strain (ɛ_cu) is more sensitive to K_l-to-unconfined compressive strength (f’_co) ratio and fiber ultimate tensile strain (ɛ_fu); hoop rupture strain (ɛ_h,rup) is more sensitive to fiber elastic modulus (E_f); and axial transition strength (f’_c1) is more sensitive to f’_co. It is also shown that the proposed expressions provided more accurate predictions of the ultimate condition and transition point on the axial stress–strain curve of FRP-confined concrete than the existing expressions. This was achieved by using a larger number of datasets and accurately capturing the effects of the most influential input parameters in the proposed expressions.