Utilization of Levenberg Algorithm for Optimization and Strength Prediction of Sustainable Self-Compacting Concrete

Self-compacting concrete (SCC) is a special sort of concrete that fills shapes spontaneously without the need for vibration, increasing structural durability and beauty. SCC mixture optimization to attain the required qualities while utilizing sustainable ingredients is still difficult. The Levenberg algorithm, a numerical optimization approach, is suggested in this work to optimize SCC mixes to meet specified strength requirements while considering sustainability factors. By taking into account several variables, including cementitious materials, mineral admixtures, and chemical admixtures, the Levenberg algorithm is utilized to optimize SCC compositions. The algorithm iteratively modifies the mixture proportions to attain the target strength while using the fewest non-renewable resources possible and minimizing the environmental effect of concrete production. The model is calibrated and its accuracy is validated using experimental data on SCC combinations containing sustainable resources such as fly ash, and limestone powder. Utilizing the optimal mixture proportions, the Levenberg method predicts the compressive strength of SCC. The Levenberg method offers useful insights into the creation of sustainable SCC mixtures for upcoming construction applications by optimizing SCC mixtures and forecasting their strength.