Numerical and Experimental Investigation of the Influence of Cement Compressive Strength on the Mechanical Properties of Concrete Using Artificial Intelligence-Based Models

The role of compressive strength of standard sand-cement mortar in the undeniable strength of concrete is crucial. Additionally, the Blaine of cement is one of the key factors in the compressive strength of cement mortar and concrete. In this research, the Artificial Neural Network (ANN) and Gene Expression Programming (GEP) methods are employed as comprehensive processes to predict the compressive strength of concrete based on the compressive strength of corresponding cement mortar. To achieve this goal, 286 mixed designs of sand-cement mortar with consistent ratios of raw materials were introduced into the cement kiln, focusing on Type 2 cement (32.5 MPa strength). The results of compressive strength tests on standard sand-cement mortar samples (3 specimens) and concrete produced with consistent mix designs (3 specimens) at the age of 28 days were obtained. Based on these results, the developed model can accurately and effectively predict the compressive strength of concrete based on the compressive strength of corresponding mortar, emphasizing the role of cement Blaine.