Short-Beam Shear Strength of New-Generation Glass Fiber-Reinforced Polymer Bars Under Harsh Environment: Experimental Study and Artificial Neural Network Prediction Model

In this study, the short-beam shear strength (SBSS) retention of two types of glass fiber-reinforced polymer (GFRP) bars-sand-coated (SG) and ribbed (RG)-was subjected to alkaline, acidic, and water conditions for up to 12 months under both high-temperature and ambient laboratory conditions. Comparative assessments were also performed on older-generation sand-coated (SG-O) and ribbed (RG-O1 and RG-O2) GFRP bars exposed to identical conditions. The results demonstrate that the new-generation GFRP bars, SG and RG, exhibited significantly better durability in harsh environments and exhibited SBSS retentions varying from 61 to 100% in SG and 90-98% in RG under the harshest conditions compared to 56-69% in SG-O, 71-80% in RG-O1, and 74-88% in RG-O2. Additionally, predictive models using both artificial neural networks (ANNs) and linear regression were developed to estimate the strength retention. The ANN model, with an <i>R</i>² of 0.95, outperformed the linear regression model (<i>R</i>² = 0.76), highlighting its greater accuracy and suitability for predicting the SBSS of GFRP bars.