About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Fatigue in Materials: Fundamentals, Multiscale Characterizations and Computational Modeling
|
| Presentation Title |
Microstructure-Informed Fatigue Life Prediction via Parametrically Upscaled Continuum Damage Modeling |
| Author(s) |
Kishore Appunhi Nair, Tawqeer Nasir Tak, Somnath Ghosh, Adam Pilchak, David Furrer |
| On-Site Speaker (Planned) |
Kishore Appunhi Nair |
| Abstract Scope |
Short crack propagation is a critical stage in the fatigue failure of metals, where multiscale mechanisms and microstructure strongly influence crack behavior. It contributes a significant fraction of total fatigue life after crack nucleation, making accurate modeling essential for reliable life prediction. However, existing multiscale fatigue models face a trade-off, compromising either computational efficiency or mechanistic fidelity. To address this, a novel, thermodynamically consistent multi-scale modeling framework called the Parametrically Upscaled Continuum Damage Model (PUCDM) is presented. Key to this framework is the concept of Representative Aggregate Microstructural Parameters (RAMPs), which encode microstructural features into macroscale constitutive equations. Machine learning is used to extract the functional relationship between model parameters and RAMPs from data generated by high-fidelity micromechanical simulations using a crystal plasticity phase-field model. The resulting macroscale model links microstructure directly to fatigue response and enables large-scale simulations of engineering components, where microstructural sensitivity and computational efficiency are critical. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Modeling and Simulation, Computational Materials Science & Engineering, Machine Learning |