A dual-stage constitutive modeling framework based on finite strain data-driven identification and physics-augmented neural networks

Ähnliche Einträge

• A physics-augmented neural network framework for finite strain incompressible viscoelasticity
  von: Kalina, Karl A., et al.
  Veröffentlicht: (2025)
• Viscoelasticty with physics-augmented neural networks: Model formulation and training methods without prescribed internal variables
  von: Rosenkranz, Max, et al.
  Veröffentlicht: (2024)
• Neural networks meet anisotropic hyperelasticity: A framework based on generalized structure tensors and isotropic tensor functions
  von: Kalina, Karl A., et al.
  Veröffentlicht: (2024)
• A data-driven multiscale scheme for anisotropic finite strain magneto-elasticity
  von: Roth, Heinrich T., et al.
  Veröffentlicht: (2025)
• Inverse design of anisotropic microstructures using physics-augmented neural networks
  von: Jadoon, Asghar A., et al.
  Veröffentlicht: (2024)