Abstract

This study showcases the predictive and optimization capabilities of response surface methodology with respect to the fresh and hardened properties of waste tyre steel fibre reinforced concrete containing limestone powder. Response surface methodology has the advantage of simultaneously varying chosen independent variables to provide a useful model for overall response variation. The study identifies aspect ratio (50–140), water cement ratio (0.2–0.4) and cement content (25%–40%) as independent variables while limestone powder was kept constant at 5% by weight of concrete. Predictive equations for the water intake/absorption, compressive strength, flexural strength, split tensile strength and slump of fibre reinforced concrete were obtained using the independent variables. The analysis of variance (ANOVA) for all properties indicates that the modified quadratic model was able to effectively predict the fresh and hardened properties of fibre reinforced concrete with coefficient of determination ranging between 0.86 and 0.98. In addition, RSM model predictive efficiency was classified as very good for compressive strength, splitting tensile strength, slump and water absorption and acceptable for FS in terms of Nash & Sutcliffe coefficient of model efficiency. An optimum condition of 140 for the aspect ratio, 0.26 for water cement ratio and 40% for cement content corresponding to 0.94%, 42.69 N/mm2, 7.97 N/mm2 5.23 N/mm2 7.65 cm for water intake/absorption, compressive strength, flexural strength, split tensile strength and slump respectively was achieved. These predictions were validated and a good correlation was observed between the experimental and predicted values judging by the absolute relative percent error of 0.842, 11.35, 3.6, 18.22 and 2.04 for water intake/absorption, compressive strength, flexural strength, split tensile strength and slump respectively. The proposed mathematical models are capable of predicting the required fresh and hardened properties of fibre-reinforced concrete as to inform early decision making when utilized in construction.

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