Performance Evaluation of Fiber-reinforced Ferroconcrete using Response Surface Methodology

Abstract

Fibre-reinforced ferroconcrete is a new-generation type of concrete that has been found to have adequate performance. Global emissions of CO2 as a result of concrete production have damaged the earth's atmosphere. These emissions, together with construction waste, such as ceramic powder and aluminium waste, are considered one of the most harmful wastes to the environment, eventually leading to pollution. In this study, the fibre-reinforced ferroconcrete (FRFC) contained waste aluminium fibre, cement, ceramic waste powder, corrugated wire mesh, and fine and coarse aggregate. The cement content in the concrete mix was partially replaced with Ceramic Powder (CP) in proportions of 0%, 10%, and 20%, while the Aluminum Fibers (AF) were added in proportions 0, 1, and 2% to the concrete mix. The variation of ceramic powder and aluminium fibres was done using the central composite design of Response Surface Methodology (RSM) to create experimental design points meant to improve the fibre-reinforced ferroconcrete's mechanical performance. The results conclude that the mechanical performance of the FRFC was slightly improved more than conventional concrete, where at 20% replacement of ceramic powder and 1% addition of aluminium fibre to the concrete mix. There was more compressive, flexural, and split tensile strength increase than conventional concrete, with control concrete having strengths of 13.060, 5.720, and 3.110 N/mm2 and ferroconcrete 15.88, 6.68, and 3.83 N/mm2 respectively. This was further confirmed with microstructural images. The RSM model, with parameters such as; contour plots, analysis of variance, and optimisation, was used to effectively predict and optimise the responses of the ferroconcrete based on the independent variables (Aluminum fibre and Ceramic Powder) considered. The results of the predicted data show a straight-line linear progression as the coefficient of determination (R2) tends to 1, indicating that the RSM model is suitable for predicting the response of the variables on the FRFC. Doi: 10.28991/CEJ-2023-09-04-014 Full Text: PDF