ABSTRACT
Alkali-activated materials (AAM) are binders that are considered an eco-friendly alternative to conventional binders based on Portland cement. The utilization of industrial wastes such as fly ash (FA) and ground granulated blast furnace slag (GGBFS) instead of cement enables a reduction of the CO2 emissions caused by clinker production. Although researchers are highly interested in the use of alkali-activated concrete (AAC) in construction, its application remains very restricted. As many standards for hydraulic concrete's gas permeability evaluation require a specific drying temperature, we would like to emphasize the sensitivity of AAM to such preconditioning. Therefore, this paper presents the impact of different drying temperatures on gas permeability and pore structure for AAC5, AAC20, and AAC35, which contain alkali-activated (AA) binders made from blends of FA and GGBFS in slag proportions of 5%, 20%, and 35% by the mass of FA, respectively. The preconditioning of samples was performed at 20, 40, 80, and 105 °C, up to the obtainment of constant mass, and then gas permeability was evaluated, as well as porosity and pore size distribution (mercury intrusion porosity (MIP) for 20 and 105 °C). The experimental results demonstrate up to a three-percentage-point rise in the total porosity of low-slag concrete after 105 °C in comparison to 20 °C, as well as a significant increase in gas permeability, reaching up to 30-fold amplification, contingent upon the matrix composition. Notably, the alteration in pore size distribution, influenced by the preconditioning temperature, exhibits a substantial impact. The results highlight an important sensitivity of permeability to thermal preconditioning.
ABSTRACT
The purpose of this study was to investigate the properties of hardened alkali-activated concrete, which is considered an eco-friendly alternative to Portland cement concrete. In this paper, the precursors for alkali-activated concrete preparations are blends of fly ash and ground-granulated blast-furnace slag in three slag proportions: 5%, 20%, and 35%, expressed as a percentage of fly ash mass. Thus, three concretes were designed and cast, denominated as AAC5, AAC20, and AAC35. Their physical and mechanical characteristics were investigated at 28 and 180 days, as well as their properties of chloride ion transport. The modified NT BUILD 492 migration test was applied to determine the chloride ions' penetration of the alkali-activated concretes. Improvement of mechanical strength and resistance to chloride aggression was observed with ground-granulated blast-furnace slag content increase in the compositions of the tested concretes. Mercury intrusion porosimetry tests provided insight into the open pore structures of concretes. A significant decrease in the total pore volume of the concrete and a change in the nature of the pore diameter distribution due to the addition of ground granulated blast furnace slag were demonstrated.
ABSTRACT
Sediments valorization (recycling) has revealed limitations due to different restrains and practical difficulties. When it comes to different recovery methods, the possibility of valuing diverse types of sediments still needs to be defined. Using a statistical approach, the present study aims to quantitatively estimate the mechanical resistance of stabilized sediments. A database that included 22 fine sediments is selected and assembled from the literature. These sediments were treated with distinct types and quantities of additives (fillers and/or binders). The present study includes two parts. On one hand, using multivariate linear regression tool of XLstat software, an analytical model that highlights the effects of various parameters influencing the mechanical resistance of treated sediments after 28 days is obtained. This model showed that organic matter content and plasticity index are the most significant factors of sediments characteristics, while cement is the best mechanical strength booster. On the other hand, the evolution of treated sediments mechanical resistance over time is modelled by an exponential relationship using a least square regression method. Both models showed acceptable accuracies compared to a panel of selected experimental values.