About this Abstract |
Meeting |
2024 TMS Annual Meeting & Exhibition
|
Symposium
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AI/Data Informatics: Computational Model Development, Verification, Validation, and Uncertainty Quantification
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Presentation Title |
Predicting Fracture Toughness with Microstructure Sensitivity Using an Elasto-viscoplastic Fast Fourier Transform Model |
Author(s) |
Milica Letic, Benjamin Anglin, Miroslav Zecevic, Ricardo A. Lebensohn, Marko Knezevic |
On-Site Speaker (Planned) |
Milica Letic |
Abstract Scope |
We adapt an elasto-viscoplastic fast Fourier transform (EVPFFT) formulation with nonperiodic displacement-based boundary conditions to simulate fracture toughness of stainless steel 304 with sensitivity to microstructure and verify the proposed method using a crystal plasticity finite element (CPFE) model. The process of preparing the CPFE mesh of notched specimens is described, which involved creating Python scripts for cutting in Abaqus, and Sculpt scripts for meshing in Cubit of complex microstructural cells of measured data processed in DREAM.3D. In contrast, the EVPFFT model circumvents mesh generation of notched specimens. This allows us to obtain a statistical distribution of fracture toughness in function of local microstructures surrounding notches. Such distribution can then be used to reduce uncertainty in macroscopic, empirical models of material performance under service conditions. The methodology developed provides a practical simulation tool for predicting a distribution of fracture toughness with explicit consideration of microstructural variability. |
Proceedings Inclusion? |
Planned: |
Keywords |
Computational Materials Science & Engineering, Modeling and Simulation, Other |