t-PiNet: A thermodynamics-informed hierarchical learning for discovering constitutive relations of geomaterials

2025/01/27 by Pin Zhang, Konstantinos Karapiperis, Oliver Weeger
Environmental Science · Engineering · #Landslides and related hazards #Rock Mechanics and Modeling #Soil and Unsaturated Flow

paper · doi:10.1016/j.jmps.2025.106049

Citations

• Thermodynamics with Internal State Variables
• A physics-informed data-driven approach for consolidation analysis
• Multiscale Thermodynamics-Informed Neural Networks (MuTINN) towards fast and frugal inelastic computation of woven composite structures