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Meeting 2026 TMS Annual Meeting & Exhibition
Symposium Verification, Calibration, and Validation Approaches in Modeling the Mechanical Performance of Metallic Materials
Presentation Title Understanding Elastoplastic Deformation at the Grain Scale Using High-Energy Diffraction Microscopy and Graph Theory
Author(s) Yuefeng Jin, Xiongye Xiao, Peiyu Zhang, Will Hobson-Rhoades, Amlan Das, Katherine Shanks, Hongyi Xiao, Paul Bogdan, Ashley N. Bucsek
On-Site Speaker (Planned) Ashley N. Bucsek
Abstract Scope In this presentation, we describe the use of three-dimensional (3D) in-situ synchrotron x-ray experiments combined with graph-based analysis and modeling to understand the mechanical behavior of polycrystalline and granular materials at the grain scale. High-energy diffraction microscopy (HEDM) measures grain-specific properties (location, orientation, strain, volume), and graph network descriptions can be used to model a 3D grain network, where grains are nodes and grain contacts are edges. In the first example, we discuss the application to understanding crystal plasticity in titanium-aluminum alloys during room-temperature creep. Using HEDM combined with graph neural networks (GNNs), we show that the grain-scale plastic deformation can be predicted with high fidelity. Topological descriptors further enhance prediction, and subgraph-based modeling highlights the importance of local structure. In the second example, we use HEDM, microcomputed tomography, and graph descriptors to understand topology and force distributions within 3D disordered contact networks of frictional granular materials.
Proceedings Inclusion? Planned:

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