Synergistic effects of supplementary cementitious materials and compressive strength prediction of concrete using machine learning algorithms with SHAP and PDP analyses

In order to reduce the CO2 associated with cement production, this study explored the potential of rice husk ash (RHA) and fly ash (FA) as supplementary cementitios materials for partially replacing cement in concrete production. The study aimed to analyze the synergistic effects of a cement-based mixture consisting of RHA and FA in different proportions on concrete's fresh, hardened, non-destructive and microscopic properties. In addition to the experimental work, this study successfully applied machine learning to predict the compressive strength of RHA-FA concrete using three types of algorithms: ANN (Analytical Neural Network), XGB (Extreme Gradient Boosting), and GBM (Gradient Boosting Model). A total of 138 data points were used for this prediction, and statistical and parametric analyses were performed to…