Experimental dataset from a central composite design with two qualitative independent variables to develop high strength mortars with self-compacting properties

Fresh and hardening properties of cement-based materials are key factors for correctly choosing the constituent materials and their mix proportions. To optimize design-based mortar compositions for specific applications, response models are frequently applied to data collected from scientific approaches. Here, experimental dataset regarding to a design of experiments carried out in mortars through a central composite design with five independent variables is presented. Among the five independent variables, four were quantitative ones: Water(v)/Cement(v), Superplasticyzer(m)/Powder(v), Water(v)/Powder(v), Sand(v)/Mortar(v). The other independent variable was a qualitative one: Superplasticiser A or Superplasticiser B. In total 60 mortar compositions were done: for each qualitative variable a 2(4) factorial design comprising of 16 treatment combinations enlarged by 8 axial runs plus 6 central runs, resulting in a central composite design with 30 mortar trial mix compositions. The following dependent variables were tested: the D-flow and the t-funnel to evaluate the fresh properties and the compressive at the age of 24 h and at the age of 28 days to evaluate the hardened properties. Based on this dataset, response models can be applied to find optimized mix compositions, with the effect of the two qualitative variables being determined. (c) 2022 The Author. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Automated summary

This study presents an experimental dataset obtained from a central composite design of mortar experiments to evaluate the fresh and hardened properties. The data can be used to optimize mix compositions and determine the effects of different types of superplasticisers on the performance.