4.6 Article

Curing Effect on Durability of Cement Mortar with GGBS: Experimental and Numerical Study

Journal

MATERIALS
Volume 15, Issue 13, Pages -

Publisher

MDPI
DOI: 10.3390/ma15134394

Keywords

durability; permeability; GGBS; curing conditions; Markov chain Monte Carlo

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This paper investigates the influence of curing conditions on the durability of mortar samples consisting of various amounts of ground granulated blast-furnace slag (GGBS), which is used as a substitute for cement to reduce carbon dioxide emissions. Experimental results show that samples cured in standard conditions perform the best, and samples with 45% GGBS content exhibit superior durability properties. A developed numerical model accurately estimates the hydraulic characteristics of mortar samples.
In this paper, supplementary cementitious materials are used as a substitute for cement to decrease carbon dioxide emissions. A by-product of the iron manufacturing industry, ground granulated blast-furnace slag (GGBS), known to improve some performance characteristics of concrete, is used as an effective cement replacement to manufacture mortar samples. Here, the influence of curing conditions on the durability of samples including various amounts of GGBS is investigated experimentally and numerically. Twelve high-strength Portland cement CEM I 52.5 N samples were prepared, in which 0%, 45%, 60%, and 80% of cement were substituted by GGBS. In addition, three curing conditions (standard, dry, and cold curing) were applied to the samples. Durability aspects were studied through porosity, permeability, and water absorption. Experimental results indicate that samples cured in standard conditions gave the best performance in comparison to other curing conditions. Furthermore, samples incorporating 45% of GGBS have superior durability properties. Permeability and water absorption were improved by 17% and 18%, respectively, compared to the reference sample. Thereafter, data from capillary suction experiments were used to numerically determine the hydraulic properties based on a Bayesian inversion approach, namely the Markov Chain Monte Carlo method. Finally, the developed numerical model accurately estimates the hydraulic characteristics of mortar samples and greatly matches the measured water inflow over time through the samples.

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