Optimization and Prediction of Concrete with Recycled Coarse Aggregate and Bone China Fine Aggregate Using Response Surface Methodology

Abstract

Construction recycled material is crucial for protecting natural resources and promoting sustainable human development in a rapidly industrializing world. Many administrations worldwide accepted that it is beneficial to use demolition waste in the concrete building industry to reduce manufacturing costs and minimize the use of virgin aggregates. However, control measures should be done as their mechanical properties are poorer than traditional aggregates. To overcome this problem, pozzolanic materials like bone chine can be incorporated, providing extra CSH gel, which improves mechanical strength. Therefore, this research is aimed at producing eco-friendly concrete, which can be used for medium-grade strength, using recycled construction waste (RCA) as coarse and bone china fine aggregate (BCA) as fine aggregate. Workability, density, compressive, split tensile, and flexural strength are used to compare the fresh and hardened properties of the concrete. Experimental and statistical research is employed in the current study to evaluate the impact of RCA and BCA on the performance of concrete. To simulate all measurable responses, including workability, density, compressive, flexural, and split strength, RSM (response surface methodology) was utilized. The CCD (Central Composite Design) approach in RSM was used to create and analyze mixes in an experiment. Based on the experiment's results, mathematical models were designed and assessed using the analysis of variance test (ANOVA). The analysis of variance results demonstrated the statistical significance of each constructed model. Three-dimensional response surface plots created using established regression models were used to investigate the interaction between the respective variables and to optimize the mixing ratio. The results indicate that the optimum utilization of RCA is up to 40% and BCA up to 60% as coarse and fine aggregate replacement in concrete, respectively, which not only helps to reduce costs but also offers sustainability. Finally, it was concluded that the generated models might be employed by obtaining the maximum tested features of concrete to assure a quick mix design approach. To conduct the microstructure study, thin section techniques were used to observe a strong aggregate-matrix interaction.