Sustainable and Low-Cost Hemp FRP Composite Confinement of B-Waste Concrete

Abstract

Each year, massive amount of construction waste is generated that needs proper attention in terms of its disposal without deteriorating surrounding environment. A significant portion of this waste comprises bricks. Besides, large number of new construction works are resulting in the depletion of natural resources rapidly. Intuitively, a sustainable solution demands to consume this construction waste in the best way possible. This study targeted brick waste as a potential material to be used as a partial replacement of natural aggregates in structural concrete. It has been known that the concrete constructed with recycled brick aggregates possesses substandard mechanical properties. Traditionally, synthetic FRPs are known to strengthen recycled aggregate concrete. However, recognizing high costs associated with them, this study proposed the use of natural hemp fiber ropes to strengthen recycled aggregate concrete constructed with brick aggregates. To assess the efficacy of hemp ropes in strengthening mechanical properties of the concrete with coarse aggregates partially replaced with recycled brick aggregates (B-waste), an experimental framework was conducted. Sixteen cylindrical specimens were tested in two groups depending upon the concrete strength. Within each group, 2 specimens each were strengthened with 1, 2, and 3 layers of hemp fiber ropes. Axial monotonic compressive loading was applied to each specimen. Results revealed that hemp fiber ropes significantly improved ultimate compressive strength and the corresponding strain. A substantial improvement in axial ductility was observed. For the sake of perfor-mance-based non-linear modelling, accurate constitutive modelling at material level is necessary. For this purpose, several existing analytical stress-strain models were tested in this study to predict ultimate confined compressive strength and strain. It was found that several models predicted confined compressive strengths with reasonable accuracy. However, very few models were able to predict confined peak strain with good accuracy. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.