Physics-Encoded Neural Network Modeling of Ductile Fracture in Pearlitic Steel

  • Gunnarsson, Jacob (Chalmers University of Technology)
  • Larsson, Fredrik (Chalmers University of Technology)
  • Meyer, Knut Andreas (Chalmers University of Technology)

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Pearlitic steels, consisting of cementite lamellas embedded in ferrite, are widely used in railway applications due to high ductility and strength at a low cost. In railway rails, the large accumulated plastic deformations give rise to complex fracture networks close to the wheel contact, which alter the contact conditions and affect crack propagation mechanisms. To accurately predict rolling contact fatigue, under the complex loading and environmental conditions, high fidelity models are required. However, resolving the complex fracture patterns is not feasible when simulating rolling contact loading conditions. To provide a link between the complex microstructural behavior of pearlitic steels and rolling contact loading cases, we propose a macroscopic physics-encoded ductile damage model that capture the effect of evolving crack networks on the microstructural level. The high-fidelity model for ferrite is based on Auth et al. [1], extended to include the kinematic hardening contributions but without gradient-hardening crystal plasticity. Due to their higher strength, the cementite lamellas are modeled as hyperelastic. Due to the anisotropic lamellar structure, the homogenized result of the high-fidelity model is an anisotropic damage model. To account for this, we propose a modeling framework based on the ”effective configuration concept” from Menzel et al. [3]. But the evolution laws are formulated following Meyer and Ekre [4], allowing the complex interactions between the plastic loading and damage evolution. [1] Kim Louisa Auth, Jim Brouzoulis, and Magnus Ekh. “Phase-Field Modeling of Ductile Fracture Across Grain Boundaries in Polycrystals”. In: International Journal for Numerical Methods in Engineering 126.12 (2025). ISSN: 10970207. DOI: 10.1002/nme.70056. [2] Mathias Wallin, Matti Ristinmaa, and Niels Saabye Ottosen. “Kinematic hardening in large strain plasticity”. In: European Journal of Mechanics - A/Solids 22.3 (2003), pp. 341–356. ISSN: 09977538. DOI: 10.1016/S0997-7538(03)00026-3. [3] A. Menzel et al. “Anisotropic damage coupled to plasticity: Modelling based on the effective con-figuration concept”. In: International Journal for Numerical Methods in Engineering 54.10 (2002), pp. 1409–1430. DOI: 10.1002/nme.470. [4] Knut Andreas Meyer and Fredrik Ekre. “Thermodynamically consistent neural network plasticity modeling and discovery of evolution laws”. In: Journal of the Mechanics and Physics of Solids 180 (2023), p. 105416. DOI: 10.1016/j.