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Numerical Design and Optimisation of Self-Compacting High Early-Strength Cement-Based Mortars.

Authors :
Cangussu, Nara
Matos, Ana Mafalda
Milheiro-Oliveira, Paula
Maia, Lino
Source :
Applied Sciences (2076-3417); Apr2023, Vol. 13 Issue 7, p4142, 22p
Publication Year :
2023

Abstract

The use of SCC in Europe began in the 1990s and was mainly promoted by the precast industry. Precast companies generally prefer high early-strength concrete mixtures to accelerate their production rate, reducing the demoulding time. From a materials science point of view, self-compacting and high early-strength concrete mixes may be challenging because they present contradicting mixture design requirements. For example, a low water/binder ratio (w/b) is key to achieving high early strength. However, it may impact the self-compacting ability, which is very sensitive to Vw/Vp. As such, the mixture design can be complex. The design of the experimental approach is a powerful tool for designing, predicting, and optimising advanced cement-based materials when several constituent materials are employed and multi-performance requirements are targeted. The current work aimed at fitting models to mathematically describe the flow ability, viscosity, and mechanical strength properties of high-performance self-compacting cement-based mortars based on a central composite design. The statistical fitted models revealed that Vs/Vm exhibited the strongest (negative) effect on the slump-flow diameter and T-funnel time. Vw/Vp showed the most significant effect on mechanical strength. Models were then used for mortar optimisation. The proposed optimal mixture represents the best compromise between self-compacting ability—a flow diameter of 250 mm and funnel time equal to 10 s—and compressive strength higher than 50 MPa at 24 h without any special curing treatment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
13
Issue :
7
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
163038027
Full Text :
https://doi.org/10.3390/app13074142