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Flexural Behavior of GBFS-Based Geopolymer-Reinforced Concrete Beams

Auteur(s): ORCID
ORCID
Médium: article de revue
Langue(s): anglais
Publié dans: Buildings, , n. 1, v. 13
Page(s): 141
DOI: 10.3390/buildings13010141
Abstrait:

Geopolymer concrete (GC) is an emerging alternative construction material due to it being eco-friendly in production with considerably low carbon emissions. Despite being an alternative material, the structural behavior of GC is a rarely studied subject in the literature. The studies concerning the mechanical behavior of structural members made from GC have established the foundations of its practical usability. The current structural codes are exclusively for ordinary Portland cement concrete (OPCC), and the utilization of these for GC constitutes an open question. In this study, 12 GC beams with different shear span-to-effective depth ratios of 2.5, 3.5 and 4.5 were manufactured and tested in a three-point bending test setup. The effect of the shear reinforcement ratio was also taken into account (0, 0.34, 0.45 and 0.67%). The results were compared with the predictive capabilities of four structural codes and two equations in the literature (all for OPCC). In addition, comparisons were made with a very limited number of studies, which included predictive tools for the strength of GC. All specimens’ cracking moments were calculated with flexural tensile strength predictions and compared with experimental cracking moments. Moreover, particularly for the beams that failed in flexure, the ultimate bending moments were compared with the predictions of two structural codes for OPCC. It was observed that the best predictions of the cracking moment could be made by the equation of Diaz-Loya et al. (2011), which resulted in the lowest coefficient of variation (COV) and consistently predicted on the safe side, whereas, even with a lower COV, EC2 consistently overestimated the cracking moment. For the ultimate moment capacity, it was observed that both ACI318 (2019) and TS500 (2000) delivered relatively good predictions and could be employed confidently.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10712578
  • Publié(e) le:
    21.03.2023
  • Modifié(e) le:
    10.05.2023
 
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