Resumen
The mixture design of cement-based materials can be complex due to the increasing number of constituent raw materials and multiple requirements in terms of engineering performance and economic and environmental efficiency. Designing experiments based on factorial plans has shown to be a powerful tool for predicting and optimising advanced cement-based materials, such as self-compacting high-early-strength cement-based mortars. Nevertheless, the number of factor interactions required for factor scheduling increases considerably with the number of factors. Consequently, the probability that the interactions do not significantly affect the answer also increases. As such, fractioned factorial plans may be an exciting option. For the first time, the current work compares the regression models and the predicting capacity of full, fractionated (A and B fractions) and small factorial designs to describe self-compacting high-early-strength cement-based mortars? properties, namely, the funnel time, flexure and compressive strength at 24 h for the function of the mixture parameters Vw/Vc, Sp/p, Vw/Vp, Vs/Vm and Vfs/Vs for the different factorial designs. We combine statistical methods and regression analysis. Response models were obtained from the full, fractionated, and small plans. The full and fractionated models seem appropriate for describing the properties of self-compacting high-early-strength cement-based mortars in the experimental region. Moreover, the predicting ability of the full and fractionated factorial designs is very similar; however, the small design predictions reveal some concerns. Our results confirm the potentiality of fractioned plans to reduce the number of experiments and consequently reduce the cost and time of experimentation when designing self-compacting high-early-strength cement-based mortars.