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Fundamental Fresh State Properties of Self-Consolidating Concrete: A Meta-Analysis of Mix Designs

Auteur(s):
Médium: article de revue
Langue(s): anglais
Publié dans: Advances in Civil Engineering, , v. 2018
Page(s): 1-13
DOI: 10.1155/2018/5237230
Abstrait:

The study reported in this paper is the first meta-analysis aimed at obtaining statistical models for the fresh state behavior of self-consolidating concrete (SCC) mixes which effectively reproduce the complex relationships between mix design and fresh state performance. A database compiled with data from more than 120 different sources was analyzed. This study proves that SCC fresh state performance is determined by three fundamental, uncorrelated properties: flow time, flow spread, and resistance to segregation, which constitute a robust mathematical framework for the optimization of SCC mixes. The models obtained for these fundamental properties have proved consistent and reproduce very well the general trends and interactions implicit in SCC mix design recommendations, which in effect constitute the mathematical validation of recommendations well sanctioned by practice. It has been proved that, if no supplementary cementitious materials (SCMs) are used, there is a remarkably narrow margin in which the three fundamental properties of fresh SCC mixes can be simultaneously optimized. The most stable mixes were found to be associated with sand-to-coarse aggregate ratios of at least 1.1. The flowability of SCC mixes in terms of both flow times and flow spread can be optimized when the following conditions concur: w/c ratio of 0.45, SCMs content below 100 kg/m³, and sand content not lower than 750 kg/m³. Furthermore, it was also proved that, in general, it is best to keep the dosages of superplasticizers (HRWRs) and viscosity-modifying agents (VMAs) below 1.7% and 0.7%, respectively, subject of course to variation across the different types of products available.

Copyright: © 2018 Emilio Garcia-Taengua
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.

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    sur cette fiche
  • Reference-ID
    10236594
  • Publié(e) le:
    13.12.2018
  • Modifié(e) le:
    02.06.2021