About this Abstract |
| Meeting |
2027 TMS Annual Meeting & Exhibition
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| Symposium
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Microstructure-Sensitive Design and Advanced Characterization: An MPMD/SMD Symposium Honoring David T. Fullwood
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| Presentation Title |
Beyond Characteristic Spacing: A Microstructure-Sensitive Statistical Framework for Precipitate Strengthening in Complex Alloys |
| Author(s) |
Ahamed Ali N, Jing Luo, Markus Sudmanns, Jaafar El Awady |
| On-Site Speaker (Planned) |
Ahamed Ali N |
| Abstract Scope |
Accurate predictions of complex alloys require models that accurately capture the underlying microstructural heterogeneity while remaining tractable and interpretable. Classical precipitate-strengthening models often represent precipitate populations using average descriptors and characteristic obstacle spacings, which can obscure local variability and provide no direct measure of microstructure-induced variability. We present a localized statistical framework linking dislocation-scale dislocation-precipitate interaction mechanisms to microstructure-aware strength prediction. Rather than assigning average precipitate descriptors, the framework samples local dislocation-precipitate configurations using nearest-neighbor topology and geometric interaction criteria. Mechanism-sensitive sampling identifies critical configurations governing weak-pair and strong-pair couplings and Orowan looping. Evaluating the critical interaction stress for each precipitate results in a distribution of strengthening responses whose mean recovers the ensemble-critical resolved shear stress, while its spread provides an interpretable, mechanism-resolved measure of microstructure variability. This framework is shown to accurately capture transitions in mechanism across monomodal, multimodal, and chemically complex precipitate populations. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Computational Materials Science & Engineering, Mechanical Properties, Modeling and Simulation |