About this Abstract |
Meeting |
2025 TMS Annual Meeting & Exhibition
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Symposium
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Atomistic Simulations Linked to Experiments to Understand Mechanical Behavior: A MPMD Symposium in Honor of Professor Diana Farkas
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Presentation Title |
Identification of dislocation structures in experimental Laue microdiffraction patterns |
Author(s) |
Benjamin Udofia, Markus Stricker |
On-Site Speaker (Planned) |
Benjamin Udofia |
Abstract Scope |
The understanding of defects present in real materials and how they influence macroscopic material behavior is limited. In particular, the exact dislocation structure inside a specimen is unknown during deformation.
In this study, a machine learning-based technique is presented to automatically identify dislocation structures from experimental Laue microdiffraction patterns. We present a framework that may be used for direct comparisons between experimental Laue microdiffraction patterns and virtual diffraction patterns based on discrete dislocation dynamics simulations. The mapping of patterns to dislocation structures from a catalog of structures requires an indexing scheme. We present such a scheme based on clustering techniques that can be browsed and compared to experimentally observed patterns in an automated fashion. The effectiveness of the model along with domain expertise from the underlying physics will ultimately provide a better insight into dislocation structure evolution and, therefore, material behaviour. |
Proceedings Inclusion? |
Planned: |
Keywords |
Modeling and Simulation, Mechanical Properties, Machine Learning |