This study aims to apply the response surface methodology (RSM) to develop a statistical model that predicts and models the performance of both the fresh and hardened properties of self-compacting concrete (SCC). RSM was used to model processes involving three variables: the water/binder ratio, and the percentages of waste marble, and glass powder. Tests, including slump flow diameter, sieve stability, and L-box, were carried out to evaluate the fresh properties of the self-compacting concrete; compressive strength was analyzed at 7, 28, and 90 days. Statistical significance was only observed in the water/binder ratio for both the slump flow and sieve stability tests. Furthermore, these results indicate that the models used in the compressive strength tests demonstrate a high statistical significance for all ages. The findings suggest that incorporating waste marble powder (MP) and glass powder (GP) in SCC necessitates a significant amount of superplasticizer to counteract the workability loss, and it improves the compressive strength of SCC. The coefficients analyzed using the RSM approach validate its effectiveness as a predictive tool for determining the hardened properties of self-compacting concrete.

Many researchers have studied the various properties of selfcompacting concrete (SCC) with the addition of several types of powders, utilizing both traditional and statistical (mathematical) methods. The novelty of our research is to use the response surface methodology (RSM) to develop a mathematical model that forecasts and simulates the performance of the Flexural Strength tests of self-compacting concrete, Contains a quantity of marble and glass powders. The response surface methodology was utilized to create models for processes that encompassed three variables: the water-tobinder ratio, as well as the proportions of waste marble and glass powder. This methodology was utilized to gather a substantial amount of data and acquire the essential predictions for comprehending the studied phenomenon. Flexural strength tests were analyzed at intervals of 7, 28, and 90 days. Results indicate that the models employed in the flexural strength tests showed high statistical significance for 7 and 28 days (p-value < 0.01), and for 90 days, the models exhibit statistical significance (p-value < 0.05). The analysis of coefficients through the RSM approach validates its effectiveness as a predictive tool for evaluating the flexural strength tests of self-compacting concrete.