Physics-Informed Machine Learning for Predicting Buckling Performance and Damage Evolution in Graphene Reinforced Basalt/Epoxy Composites
This study presents an integrated experimental and computational framework demonstrating that dual-phase reduced graphene oxide functionalization significantly enhances the mechanical and buckling performance of basalt/epoxy composites, while leveraging multiscale modeling and machine learning to accurately predict critical loads and damage evolution for optimized structural design.