Performance of green RPC containing nanoparticles and reinforced with hybrid fibers used for repairing damaged concrete
Source abstract
Abstract
Recently, there is an increased research awareness towards the use of high strength cementitious matrices like reactive powder concrete (RPC) for rehabilitation and repairing damaged structures in addition to their use in the maintenance of concrete structures. Therefore, this research has been conducted to present some RPC mixes prepared from various percentages of cement replacement, nanoparticles materials, and reinforced with three different types of fibers. The green RPC mixes were prepared with a total 30 % replacement of cement by silica fume, slag powder, and glass powder. Then, the addition of Nanoparticles combination as 2.5 % Nano glass powder (NG) plus 2.5 % Nano Iron slag powder (NS) was performed. Besides, the uses of mono micro steel fibers and hybridization of micro steel fibers (MSF), sisal fibers (SIF), and human hair fibers (HHF) were achieved. The combined systems of substrate concrete and such different green RPC mixes which were proposed here as repair materials besides epoxy were tested in bi-surface shear, oblique shear, flexural bond strength, splitting bond strength, and Pull-out. The results showed that the reinforcing of green RPC with hybrid nanoparticles (2.5 %NG + 2.5 %NS) and hybrid fibers (1.5 %MSF with 0.25 %SIF and 0.25 %HHF) boosted the best performances among green RPC mixes in bi-surface shear, oblique shear and Pull-out tests. Also, the said mix gives higher bond strengths between RPC with substrate concrete than that of epoxy by 2.273 %, 3.663 %, 6.168 % and 10 % through bi-surface shear, oblique shear, splitting strength and flexural strength, respectively.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Innovative concrete reinforcement materials · Concrete and Cement Materials Research · Magnesium Oxide Properties and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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