Maia Lino
CONSTRUCT-LABEST, Faculty of Engineering (FEUP), University of Porto, Rua Dr. Roberto Frias, Porto 4200-465, Portugal.
Faculty of Exact Sciences and Engineering, University of Madeira, Campus da Penteada, Funchal 9020-105, Portugal.
Data Brief. 2021 Dec 21;40:107738. doi: 10.1016/j.dib.2021.107738. eCollection 2022 Feb.
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/Cement, Superplasticyzer/Powder, Water/Powder, Sand/Mortar. 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 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.
水泥基材料的新拌性能和硬化性能是正确选择组成材料及其配合比的关键因素。为了针对特定应用优化基于设计的砂浆配方，响应模型经常应用于从科学方法收集的数据。在此，给出了通过具有五个自变量的中心复合设计在砂浆中进行的实验设计的实验数据集。在这五个自变量中，四个是定量变量：水灰比、减水剂/粉料、水/粉料、砂/砂浆。另一个自变量是定性变量：减水剂A或减水剂B。总共制备了60种砂浆配方：对于每个定性变量，采用2因子设计，包括16个处理组合，再加上8个轴向试验点和6个中心点，从而得到一个包含30种砂浆试配配方的中心复合设计。测试了以下因变量：用于评估新拌性能的D值流动度和t型漏斗流动时间，以及用于评估硬化性能的24小时和28天龄期的抗压强度。基于该数据集，可以应用响应模型来找到优化的配合比，同时确定两个定性变量的影响。
