Fracture Mechanic

Fracture mechanics studies how materials break, aiming to predict crack initiation and propagation. Current research heavily utilizes machine learning, particularly deep learning architectures like UNets and graph neural networks, to model complex fracture behavior in diverse materials, often leveraging transfer learning to reduce data requirements and improve generalization. These advancements enable faster and more accurate simulations, improving safety assessments in fields like nuclear engineering and civil infrastructure, as well as enhancing the design of more resilient materials. The integration of digital image correlation and fracture mechanics principles further refines experimental crack detection and analysis.