Systematic multiscale models to predict the effect of high-volume fly ash on the maximum compression stress of cement-based mortar at various water/cement ratios and curing times

Abstract

Advances in technology and environmental issues enable the building industry to use more high-performance materials. In this analysis, the hardness of cement mortar with high-volume fly ash has been evaluated and modeled using different model techniques. To establish systematic multiscale models to predict the compressive strength of cement mortar containing a high volume of fly ash (FA) and to be used by the construction industry with no theoretical restrictions. For that purpose, a wide experimental data (a total of 450 tested cement mortar modified with FA) from different academic research studies have been statistically analyzed and modeled. For that purpose, Linear and Nonlinear regression, M5P-tree, and Artificial Neural Network (ANN) approaches were used. In the modeling process, the most relevant parameters affecting the strength of cement mortar, i.e. fly ash (class C and F) incorporation ratio (0–70% of cement's mass), water-to-binder ratio (0.235–1.2), and curing ages (1 to 365 days). According to the correlation coefficient (R), Mean Absolute Error (MAE), and the Root Mean Square Error (RMSE), the compressive strength of cement mortar can be well predicted in terms of w/b, fly ash, and curing time using various simulation techniques. The sensitivity investigation concludes that the curing time is the most dominating parameter for the prediction of the compressive strength of cement mortar with this data set.