Soft computing technics to predict the early-age compressive strength of flowable ordinary Portland cement

In this study, the effect of two water reducer polymers with smooth and rough surfaces on the compression strength of ordinary Portland cement (OPC) was investigated. Three different initial ratios between water and cement (w/c) 0.5, 0.6, and 1 were used in this study. The amount of polymer contents varied from 0 to 0.06% (%wt) for the cement paste with an initial w/c of 0.5. The cement paste's polymer contents ranged between 0 and 0.16% (%wt) with an initial w/c of 0.6 and 1 were investigated. SEM test was conducted to identify the impact of polymers on the behavior of cement paste. The compression strength of OPC cement increased significantly by increasing the polymer contents. Because a fiber net (netting) around cement paste particle was developed when the polymers were added to the cement paste, which leads to decrease the void between the particles, binding the cement particles, therefore, increased the viscosity and compression strength of the cement rapidly. In this analysis, the hardness of cement paste with polymer contents has been evaluated and modeled using four different model technics: more environmentally sustainable construction, and lower cost than conventional building materials and early-age strengths of the cement. To overcome the mentioned matter, this study aims to establish systematic multiscale models to predict the compression strength of cement paste containing polymers and to be used by the construction industry with no theoretical restrictions. For that purpose, comprehensive data of 280 tested cement paste modified with polymers have been conducted, analyzed, and modeled. Linear, nonlinear regression, M5P-tree, and artificial neural network (ANN) technical approaches were used for the qualifications. In the modeling process, the most relevant parameters affect the strength of cement paste, i.e., polymer incorporation ratio (0-0.16% of cement's mass), water-to-cement ratio (0.5-1), and curing ages (1-28 days). According to the correlation coefficient (R), mean absolute error, and the root-mean-square error, the compression strength of cement paste can be well predicted in terms of w/c, polymer content, and curing time using four various simulations techniques. Adding polymer creates an amorphous gel that fills the porous between the particles of the cement, which causes a reduction in the voids and porosity and enhances the dry density of the cement; subsequently, the compression strength of the cement-grouted sands increases significantly. Among the used approaches and based on the training data set, the model made based on the nonlinear regression, ANN, and M5P-tree models seems to be the most reliable models. The sensitivity investigation concludes that the polymer content is the most affected parameter for predicting the compression strength of cement paste.