Case-Based Reasoning for Predicting Bond Strength in Fiber Reinforced Polymer (FRP) and Concrete

The increasing adoption of Fiber Reinforced Polymer (FRP) bars in concrete structures necessitates accurate prediction of bond strength to ensure structural integrity and reliability. This study introduces Case-Based Reasoning (CBR) as an interpretable and efficient approach for predicting FRP-concrete bond strength. Utilizing a dataset of 227 experimental results, the CBR model achieves high accuracy, with an R2 of 0.98 and a low Mean Squared Error (MSE) of 0.226 MPa. Sensitivity analysis identifies critical parameters such as bar diameter (db), concrete compressive strength (fc’), cover-to-bar diameter ratio (c/db), and embedment length-to-bar diameter ratio (ld/db), demonstrating their varying influence across different surface types: helical lugged, spiral-wrapped, and sand-coated. The findings emphasize the practical applicability of CBR in tailoring design strategies for FRP-reinforced structures, offering engineers an interpretable and reliable tool to optimize performance while reducing computational complexity.