Bond Strength of Glass FRP Bars in Concrete Subjected to Freeze-Thaw Cycles and Sustained Loads

Author(s):  
Juliana Alves ◽  
Amr El-Ragaby ◽  
Ehab El-Salakawy
2022 ◽  
pp. 136943322110651
Author(s):  
Ruiming Cao ◽  
Bai Zhang ◽  
Luming Wang ◽  
Jianming Ding ◽  
Xianhua Chen

Alkali-activated materials (AAMs) are considered an eco-friendly alternative to ordinary Portland cement (OPC) for mitigating greenhouse-gas emissions and enabling efficient waste recycling. In this paper, an innovative seawater sea-sand concrete (SWSSC), that is, seawater sea-sand alkali-activated concrete (SWSSAAC), was developed using AAMs instead of OPC to explore the application of marine resources and to improve the durability of conventional SWSSC structures. Then, three types of fiber-reinforced polymer (FRP) bars, that is, basalt-FRP, glass-FRP, and carbon-FRP bars, were selected to investigate their bond behavior with SWSSAAC at different alkaline dosages (3%, 4%, and 6% Na2O contents). The experimental results manifested that the utilization of the alkali-activated binders can increase the splitting tensile strength ( ft) of the concrete due to the denser microstructures of AAMs than OPC pastes. This improved characteristic was helpful in enhancing the bond performance of FRP bars, especially the slope of bond-slip curves in the ascending section (i.e., bond stiffness). Approximately three times enhancement in terms of the initial bond rigidity was achieved with SWSSAAC compared to SWSSC at the same concrete strength. Furthermore, compared with the BFRP and GFRP bars, the specimens reinforced with the CFRP bars experienced higher bond strength and bond rigidity due to their relatively high tensile strength and elastic modulus. Additionally, significant improvements in initial bond stiffness and bond strength were also observed as the alkaline contents (i.e., concrete strength) of the SWSSAAC were aggrandized, demonstrating the integration of the FRP bars and SWSSAAC is achievable, which contributes to an innovative channel for the development of SWSSC pavements or structures.


2005 ◽  
Vol 9 (6) ◽  
pp. 470-479 ◽  
Author(s):  
Ehab El-Salakawy ◽  
Brahim Benmokrane ◽  
Amr El-Ragaby ◽  
Dominique Nadeau

2006 ◽  
Vol 33 (11) ◽  
pp. 1426-1437 ◽  
Author(s):  
F Shahidi ◽  
L D Wegner ◽  
B F Sparling

Although the use of fibre-reinforced polymer (FRP) bars to replace steel in reinforced concrete is becoming more common, uncertainty remains concerning the long-term performance of FRP, including the effect of a sustained load on the bond between the FRP bars and the concrete. An experimental study was therefore undertaken to investigate the long-term durability of the bond for various types of bars embedded in concrete: one type of glass FRP, two types of carbon FRP, and conventional steel reinforcing bars. Pullout specimens were tested both statically to failure and under sustained loads for periods of up to 1 year while free-end slip was monitored. Results revealed lower short-term bond strengths for FRP bars relative to steel and significant variability in long-term bond-slip performance among FRP bars of different types. Post-testing investigations revealed damage to bar surfaces at the macroscopic level, as well as broken longitudinal fibres and damage to the surface coatings at the microscopic level.Key words: reinforced concrete, fibre-reinforced polymer (FRP), bond, creep, pullout, sustained loads.


2021 ◽  
Vol 267 ◽  
pp. 120919
Author(s):  
Ahmed Godat ◽  
Shaima Aldaweela ◽  
Hamda Aljaberi ◽  
Noura Al Tamimi ◽  
Ebtesam Alghafri

Technologies ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 42 ◽  
Author(s):  
Hamed Bolandi ◽  
Wolfgang Banzhaf ◽  
Nizar Lajnef ◽  
Kaveh Barri ◽  
Amir H. Alavi

Accurate prediction of bond behavior of fiber reinforcement polymer (FRP) concrete has a pivotal role in the construction industry. This paper presents a soft computing method called multi-gene genetic programming (MGGP) to develop an intelligent prediction model for the bond strength of FRP bars in concrete. The main advantage of the MGGP method over other similar methods is that it can formulate the bond strength by combining the capabilities of both standard genetic programming and classical regression. A number of parameters affecting the bond strength of FRP bars were identified and fed into the MGGP algorithm. The algorithm was trained using an experimental database including 223 test results collected from the literature. The proposed MGGP model accurately predicts the bond strength of FRP bars in concrete. The newly defined predictor variables were found to be efficient in characterizing the bond strength. The derived equation has better performance than the widely-used American Concrete Institute (ACI) model.


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