Physical, mechanical, and thermal properties of concrete roof tiles produced with vermiculite

Viana, Queilla Santos; Eugênio, Tony Matheus Carvalho; Sabino, Ticyane Pereira Freire; Scolforo, José Roberto Soares; Mendes, Rafael Farinassi

doi:10.1007/s11356-022-19337-1

Cited by 4 publications

(1 citation statement)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lightweight concrete brick is a concrete brick with an over-dry density between 300 and a maximum of 2,000 kg/m 3 . It is a mixture of cement, water, vermiculite (Nandhini and Vallabhy, 2018;Viana et al, 2022), and fines (sand). As a result, it is easier for the aggregates to be incorporated into cement when wetted with water first (Shafigh et al, 2010;Liu et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation and optimization of lightweight concrete bricks developed using vermiculite

2023

View full text Add to dashboard Cite

Concrete production requires a wealth of resources, including cement, aggregate, and water. Therefore, in terms of maintaining the Earth’s natural ecosystems and resources, researchers need to find sustainable and green methods for producing concrete. The focus of the current research was the use of potentially harmful alternative aggregates to manufacture lightweight concrete bricks. In this study, cement, fine aggregates, and vermiculite were the concrete brick mix components. Three trail mixes were followed by a replacement ratio of 60:40, 50:50, and 40:60 for fine aggregates in bricks. Statistical techniques were exerted to compare all the experimental results. Initially, regression analysis was employed to determine the precise relationship between the dependent and independent variables of the study. Furthermore, the compressive strength of the concrete brick was investigated. As a result of the research, vermiculite concrete bricks with the compressive strengths ranging from 3.2 to 5.9 kN/mm2 and densities ranging from 1,780 to 2,142 kg/m3 were obtained. The regression model captured the variability of the data, as evidenced by the suitable R2 threshold (R2 > 0.9935). Subsequently, every property of the concrete bricks was predicted using regression, surface plots, main plots, and a heatmap. The conclusion of the study demonstrated that the models generated very effective results.

show abstract

Section: Introductionmentioning

confidence: 99%