Discovering neural cohesive zone laws from displacement fields

Key Points

• Neural cohesive zone laws enhance understanding of material behavior under stress, promoting effective modeling.
• Key evidence included notable correlations between predicted and observed displacement fields, achieving a 95% accuracy rate.
• Assessment using advanced neural network algorithms was conducted, enabling detailed mappings of cohesive zone responses.
• Highlights the potential for machine learning to transform the modeling of complex material interactions.