Predictive modeling of concrete strength utilizing recycled materials: a DOE methodology

Abstract

The DOE methodology was applied to identify the best combination of variables-Recycled Aggregate (RA), Aluminium Ash dross (AAD), and Magnesium oxide dross (MOD)-to enhance concrete's mechanical properties. Utilising the Response Surface Methodology's Central Composite Design (CCD), the study examined four variables: the concrete's split tensile and compressive strengths at 14 and 28 days. ANOVA was used to test regression models for these factors, with the results displayed in a Pareto chart for visualization. The impact of each independent variable was evaluated, and second-order polynomial equations were devised to represent the models obtained. The findings suggested a positive contribution from the inclusion of RA, AAD, and MOD to improve mechanical properties, though higher levels of their inclusion led to reduced strength. Through surface plots, Pareto charts, and regression analysis, it was revealed that Recycled Aggregate and AAD were the most significant factors distressing compressive strength (CS) and split tensile strength (STS) at both 14 and 28 days. Validation tests were similar to predicted results for both compressive strength and split tensile strength, signifying the consistency of these models in predicting strength properties based on the selected variables.

Keywords:
Recycled aggregate; Aluminium ash dross; Magnesium oxide dross; Analysis of variance; Pareto chart; Contour plot