317 publications from this institution
Glass Fiber Reinforced Polymer (GFRP) composites have low permeability and high corrosion resistance. In recent years, as the use of GFRP in applications requiring high corrosion resistance has gradually expanded, its long-term performance in highly corrosive environments has caught public attention worldwide. Nevertheless, there is only limited theoretical research and accumulated test data on the corrosion resistance of GFRP. This paper analyses the long-term performance of GFRP in highly corrosive environments. Samples cut from pultruded GFRP profiles were exposed to alkaline, saline, and acidic solutions of different concentrations at 60°C. Additionally, the effects of acidic solutions at high temperature (90°C) were investigated. Flexural properties, changes in the flexural fracture mechanism, hardness, the rate of weight gain, changes in appearance, and scanning electron microscopy (SEM) images of fracture sections were analyzed over periods of 7, 15, 30 and 90days. Results indicate that flexural strength decreases with increased exposure time to both acidic and alkaline solutions. Under conditions of high concentration acidity and high temperature acidity, respectively, flexural strength decreases even more drastically. Additionally, it was found that saturated NaCl solution has little effect on GFRP.
The connection between FRP profile and concrete is critical for structural performance. This study introduces a novel fiber-bridging interface to enhance the FRP-concrete interfacial behavior. The interface comprises an epoxy resin adhesive layer, a carbon fabric layer, a mixture of adhesive and sand layer, and U-shaped steel fibers. Central pull-out tests were conducted to investigate the mechanical performance of this novel interface. The investigated variables included bond length and fiber volume fraction. Test results indicate that all specimens failed in a brittle mode at the adhesive layer, with load plateauing after reaching the peak. The number of steel fibers had limited influence on the interfacial behavior. Based on the load-slip curves, a bond stress-slip model for the tangential behavior was developed. An interfacial expansion model was further developed by means of FE analysis and machine learning. The three most widely used machine learning models, i.e., the BP neural network model, the random forest model, and the XGBoost model were selected. Comparisons show that all three models provide reasonable predictions, with the XGBoost model demonstrating the best performance. These models for the tangential and normal behavior of FRP-concrete interface were implemented into FE models for numerical analysis. Comparisons between numerical and experimental results show that the proposed models accurately describe the interfacial behavior of the fiber-bridging interface under brittle failure mode. The innovative interface proposed in this paper can be used for connecting concrete and FRP in various scenarios, and the proposed methodology of calibrating local bond behavior parameters from global response offers a new approach for establishing interfacial bond models.
