Abstract

Nowadays, there is a growing demand for the development of structures and construction materials from recycled or reused and renewable resources, in line with circular economy principles and the goal of sustainable development. The present study explores promising solutions for increasing the sustainability of concrete structures, through the application of basalt fibers reinforced polymer (BFRP) rebars, whose raw materials show an unlimited availability on earth, as well as recycled steel fibers from waste tyres (RTSF), for RTSF reinforced concrete structures with BFRP reinforcements. Three different types of self-compacting concretes with 1.1% fiber volume fractions of industrial and/or recycled steel fibers were developed, where 50% and 100% of the industrial steel fibers (ISF) weight was replaced by RTSF. Five different groups of pull-out specimens, with total number of 26 specimens, were fabricated to evaluate bond performance of BFRP rebar embedded in RTSF reinforced concrete. The understanding of the bond behaviour is critical to the effective design of reinforced concrete structures under both static and dynamic loadings. The influence of the type of reinforcement, dosage of the adopted RTSF, type of loading, and concrete flow direction on bond stress versus slip behavior, maximum bond stress, and failure mode are analysed and discussed. One of the main contributions of this research regards the understanding of the effect of RTSF orientation on bond performance obtained when BFRP rebars are pulled out from RTSF reinforced concrete. Compared to ISF, using RTSF for reinforcing concrete can increase the bond strength between BFRP rebars and fiber reinforced concrete up to 6.3% under static and 9.7% under fatigue loading regime. As the future research in this area, it is recommended to evaluate the long-term bond durability of BFRP reinforced FRC embedded in seawater, the environmental and economic feasibility of using BFRP and TRSF for reinforcing concrete structures, and fiber orientation and dispersion using image analysis and 3D visualization.

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