L. Castillo-Suárez

Machine Learning Prediction of 28-Day Compressive Strength in Recycled Aggregate Concretes with Supplementary Cementitious Materials: Experimental Validation Using Metakaolin and Spent Fluid Catalytic Cracking Catalyst Residue

This study develops an interpretable machine learning framework for predicting the 28-day compressive strength of recycled aggregate concrete containing supplementary cementitious materials and validates it experimentally using metakaolin and spent fluid catalytic cracking catalyst residue. A broad multi-source databas...