R. Ball

Physics-Informed Hybrid Machine Learning Model for Carbonation Depth Prediction in Concrete through Residual Correction and Variogram Analysis of Response Surfaces

A hybrid residual correction framework that integrates a physics-based carbonation model with a stacked ensemble of machine learning algorithms: gradient boosted regression trees (GBRT), support vector regression (SVR), and Gaussian process regression (GPR), combined through an XGBoost metamodel, demonstrating that the...