Guang-Yi Zhang

Machine learning-based prediction of shear and flexural capacity of reinforced concrete beams: a parallel modeling framework with SHAP interpretability and design code benchmarking

Design-code equations for the shear and flexural capacity of reinforced concrete (RC) beams are conservative and variable across structural conditions. This study develops a parallel modeling framework — two structurally independent machine-learning pipelines, one trained only on shear-failure specimens and one onl...

Experiments and Machine Learning Prediction of Interfacial Bond Strength Between Magnesium Oxychloride Cement and Ordinary Concrete