Mechanical Performance and Strength Prediction of Rubberized Silica Fume Concrete: An Experimental and Machine Learning Investigation for Sustainable Construction
This study investigates the mechanical performance of rubberized silica fume concrete through experimental testing and machine learning, demonstrating that while rubber powder and silica fume enhance specific properties and existing design codes underestimate strength, advanced predictive models like Artificial Neural Networks offer superior accuracy for estimating compressive and flexural strength to support sustainable construction.