Factorial design modelling of cement grout containing dolomitic quarry dust powder. (2022)

• Record Type: Journal Article
• Authors: Abdalqader, Ahmed; Sonebi, Mohammed; Thornton, Neil; Taylor, Su
• Is Part Of: Materials today. Volume 58:Part 4(2022)
• Page Start: 1258
• Page End: 1264
• Publication Date: 2022
• Subjects: Factorial design -- Dolomite, Grout -- Quarry dust -- Optimisation; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2022.02.011
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: Aggregate processing in quarries results in huge amount of waste materials and dust. These pose a growing threat to the environment and urge more sustainable management and practices. A very promising way to use the quarry waste and dust is to be incorporated as a filler in cement and concrete composites such as cement grout and self-compacting concrete. This paper examines and models the influence of key parameters including quarry dust (QD) content on the properties of fresh and hardened Portland cement-based grouts. A full factorial design was carried out to mathematically model the spread, flowability, cohesion and compressive strength of grouts containing dolomitic quarry dust. The parameters considered in this study were water-to-binder (w/b) ratio, QD content as percentage of total mass of dry powder, and dosage of superplasticiser (SP). The w/b ratio varied between 0.3 and 0.4, while the QD content and SP dosage were in the range of 0–20% and 0.4–1%, respectively. Additionally, the effect of incorporating QD into the grout on the reaction kinetics was studied. The main findings showed that the grout spread and flowability improved by increasing all the factors. However, an interaction effect between w/b and SP dosage led to loss of the spread and flowability of the grout. The cohesion of the grout followed a similar trend with an additional interaction effect of QD content and SP dosage. The effect of the studied parameters on compressive strength was found to be dependent on the age of the testing. The derived models are helpful to optimise the mix proportions for a specific set of criteria.