Completely random experimental design with mixture and process variables for optimization of rubberized concrete

A completely random experimental design has been used to simultaneously optimize process variables and cementitious mixture components for rubberized concrete. In this study the concrete is composed of only three mixture components, cement, aggregate (including fine and coarse) and water, and two process variables, size of rubber (chips of waste truck tires) and percentage rubber that replaced the aggregate in concrete, were varied. The calculations of regression and residual ANOVA sums of squares for regression and lack of fit are illustrated. These values are shown to be useful for model development. Two different models were evaluated. The bilinear–linear model has no lack of fit and is preferred. The significant terms in this model are capable of describing how the process response surfaces change as mixture level conditions are varied. Optimum condition in the rubberized concrete, considering the level of the variable studied is: 2.4 mm size of rubber, 2.5% rubber that replaced the aggregate, 16% of cement, 76% of aggregate and 8% of water. The optimum mixture conditions with 2.5% of rubber show a concrete value of compressive strength above 20 MPa, can generate concrete suitable for use in structures as well as pavement, curbs, walls and other applications in civil engineering.