Short-Beam Shear Strength of New-Generation Glass Fiber-Reinforced Polymer Bars Under Harsh Environment: Experimental Study and Artificial Neural Network Prediction Model
Year: 2024
Type: article
Abstract: 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 R2 of 0.95, outperformed the linear regression model (R2 = 0.76), highlighting its greater accuracy and suitability for predicting the SBSS of GFRP bars.
Source: Polymers
Author: Mesfer M. Al-Zahrani
Institution: King Fahd University of Petroleum and Minerals
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,069
OpenAlex ID: W4404855765