Experiments and probabilistic models of bond strength between GFRP bar and different types of concrete under aggressive environments. (1st September 2017)

• Record Type: Journal Article
• Authors: Bazli, Milad; Ashrafi, Hamed; Oskouei, Asghar Vatani
• Is Part Of: Construction & building materials. Volume 148(2017)
• Page Start: 429
• Page End: 443
• Publication Date: 2017-09-01
• Subjects: Glass fiber reinforcement bars -- Durability -- Acceleration -- Pull-out strength -- Degradation -- Probabilistic models; Building materials -- Periodicals; 624.18
• DOI: 10.1016/j.conbuildmat.2017.05.046
• Languages: English
• ISSNs: 0950-0618

Abstract

Graphical abstract: Highlights: Bond strength degradation of GFRP bars under aggressive environments is investigated. High strength and self-compacting concrete showed appropriate bond durability. Bond strengths of light-weight concrete showed considerable reductions. Maximum development lengths were obtained for acid conditioned specimens. Abstract: Bond durability of FRP bars and concrete is an important issue to the overall integrity and long-term performance of a strengthening structure. This paper examines the bond durability of GFRP bars embedded in different types of concrete (Normal, self-compacting, light weight, and high strength) exposed to aggressive environments, namely, sea water, alkaline, and acid. A total of 132 specimens were tested in direct pull-out. The development lengths of both control and conditioned specimens were obtained and compared to the current standards. The results revealed bond strength reductions of 0–21% for the light weight, 1–16% for the normal, 5–9% for the high strength, and 4–12% for the self-compacting concrete in different environmental conditions. Furthermore, the specimens immersed in acid solution had the maximum development length. According to the results, using concrete with higher strength and density may lead to a higher bond durability of GFRP bars and concrete in aggressive environments. Finally, the contribution of variable parameters in bond strength reduction was investigated by Bayesian regression method.