Experimental investigation and optimization of lightweight concrete bricks developed using vermiculite

Abstract

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.

Prediction of steel plate-based damper for improving the behavior of concentrically braced frames based on RSM and ML approaches for sustainable structures

“…Analysis of variance (ANOVA): ANOVA is used to assess the significance of the model terms and identify the factors that have a significant impact on the response. It helps in understanding the relative importance of the factors and their interactions 45 . Optimization: Once the model is developed and validated, RSM allows for optimization of the response.…”