Parametric analysis in sustainable self-compacting mortars using genetic programming

Abstract

This study addresses the capabilities of genetic programming to predict the behaviour of cement-based mixtures by focusing on the influence of quaternary binders (incorporating metakaolin, biomass ash and granite powder as novel powder materials) on the rheological properties of self-compacting mixtures, including spread diameter in mini-cone test and time to flow in mini-funnel test. Using a previous dataset, GP techniques are applied to obtain predicted models and to compare them with those developed throughout analysis of variance. The results demonstrate that the equations obtained by the GP technique showed the best statistical indices for the analysed properties. Afterwards, a parametric analysis was performed to analyse the influence of the composition of quaternary binders on the fresh behaviour of mortar mixtures. The parametric analysis indicated that changes in the binder composition that increased granite powder content damage the fresh behaviour of the mortars (the funnel time increases, and the spread diameter decreases), being this negative effect more significant when the water content is low, and especially noteworthy in the Tfunnel time. It is concluded that genetic programming and design of experiments are powerful tools that can be used to analyse the influence of new raw materials in different mortar properties.