Fiber-reinforced polymer (FRP) bars have recently been introduced to the market as an alternative to steel for internal reinforcement for concrete construction exposed to situations that could cause corrosion. The bond behavior of FRP bars varies from that of steel bars, mostly due to variations in material properties and surface textures. Because of the unexpected nature of the crucial FRP–concrete interfacial (FCI) bond strength, the bond strength between FRP bars and concrete cannot be exactly determined. Numerous experimental investigations have been conducted with related empirical models established in an attempt to resolve this problem. These models were found to have a restricted capacity for generalization due to the small sample sizes of the experiments. Therefore, a more powerful numerical technique capable of processing large data sets with all possible parameters that may affect the relationship and considering the nonlinearity of data tendency is needed. In this study, the artificial neural networks technique and adaptive neuro-fuzzy inference system were utilized to predict the FRP–concrete bond behavior based on 238 data points collected from different studies in the literature. The performance of the ANN and ANFIS models in predicting the bonding strength was compared to other models published in the literature and codes. The results showed that the ANN and ANFIS models gave higher prediction performance than other models, with a slight advantage for the ANN model. For instance, the R-squared values of the proposed ANN and ANFIS were 0.94 and 0.92, respectively, for 20 data points that were not used to develop the ANN and ANFIS models. Based on the sensitivity analysis, the FRP diameter and compressive strength of concrete were found to be the most effective parameters on the bond strength in both the ANN and ANFIS models. In contrast, the bar position and surface texture had a lower importance index.

In this paper, the flexural performance of the Engineering Cementitious Composite (ECC)-concrete composite beam hybrid reinforced by steel and Fiber Reinforced Polymer (FRP) bars is assessed using nonlinear finite element analysis. The concrete damage plasticity model is used to model the nonlinear behavior of ECC and concrete materials. A perfect bond is assumed at the interface surface between the ECC and concrete. The validity of the numerical model is established through comparison with a previously published experimental study (overall error of about 5.4%). Consequently, the developed model is utilized to consider the effect of hybrid (FRP/steel) tensile reinforcement ratio, thickness of the ECC layer, type of FRP bars, and compressive strength of concrete on the flexure performance. It was evident from the results that the ratio of hybrid (FRP/steel) tensile reinforcement should be carefully chosen to achieve an adequate balance between ductility and carrying load capacity. Additionally, the thickness of the ECC layer plays a crucial role in controlling the hybrid reinforcement’s tensile ratio to prevent rapid failure following the yielding of steel rebars within the ECC layer. Furthermore, the type of FRP bars used in the hybrid reinforcement has influenced the flexural behavior of the composite beam. Conversely, increasing the compressive strength of the concrete has minimal impact on enhancing the mechanical characteristics of the beams, even when considering a change in the type of FRP bars.