A Thermodynamically Consistent Hyperelastic Potential for Unbound Granular Materials: Critical-State Formulation, Machine-Learning Benchmarking, and Finite Element Application
Two paradigms dominate the literature on resilient strain behaviour of unbound granular materials (UGMs): empirical formulations, often lacking theoretical grounding, and machine learning (ML) models, operating as black boxes. This study proposes a hyperelastic strain energy potential—the KHP (Karasahin Hyperelastic Po...