Shear Behavior of Steel-Fiber-Reinforced Recycled Aggregate Concrete Deep Beams
Autor(en): |
Nancy Kachouh
Tamer El-Maaddawy Hilal El-Hassan Bilal El-Ariss |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Buildings, 25 August 2021, n. 9, v. 11 |
Seite(n): | 423 |
DOI: | 10.3390/buildings11090423 |
Abstrakt: |
Results of an experimental investigation aimed at studying the effect of steel fibers on the shear behavior of concrete deep beams made with a 100% recycled concrete aggregate (RCA) are presented in this paper. The study comprised testing of seven concrete deep beam specimens with a shear span-to-depth ratio (a/h) of 1.6. Two beams were made of natural aggregates (NAs) without steel fibers, two beams were made of a 100% RCA without steel fibers, and three beams were made of RCA-based concrete with steel fibers at volume fractions (vf) of 1, 2, and 3%. Two of the beams without steel fibers included a minimum shear reinforcement. Test results showed that the beam with a 100% RCA without steel fibers exhibited a lower post-cracking stiffness, reduced shear cracking load, and lower shear capacity than those of the NA-based control beam. The detrimental effect of the RCA on the shear response was less pronounced in the presence of the minimum shear reinforcement. The addition of steel fibers significantly improved the shear response of the RCA-based beams. The post-cracking stiffness of the RCA-based concrete beams with steel fibers coincided with that of a similar beam without fibers containing the minimum shear reinforcement. The use of steel fibers in RCA beams at vf of 1 and 2% restored 80 and 90% of the shear capacity, respectively, of a similar beam with the minimum shear reinforcement. The response of the RCA specimen with vf of 3% outperformed that of the NA-based control beam with the minimum shear reinforcement, indicating that steel fibers can be used in RCA deep beams as a substitution to the minimum shear reinforcement. The shear capacities obtained from the tests were compared with predictions of published analytical models. |
Copyright: | © 2021 by the authors; licensee MDPI, Basel, Switzerland. |
Lizenz: | Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden. |
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