About this Abstract |
Meeting |
2023 TMS Annual Meeting & Exhibition
|
Symposium
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AI/Data Informatics: Computational Model Development, Validation, and Uncertainty Quantification
|
Presentation Title |
Generation of 3D Synthetic Polycrystalline Microstructures using Gaussian Random Fields and Two Point Spatial Correlations |
Author(s) |
Michael Buzzy, Andreas Robertson, Surya Kalidindi |
On-Site Speaker (Planned) |
Michael Buzzy |
Abstract Scope |
The generation of synthetic microstructures is critical for many tasks such as the creation of artificial datasets, microstructure sensitive design, and process optimization. Current frameworks for synthetically generating polycrystalline microstructures are limited to enforcing mean field statistics, such as grain size distributions and orientation distribution functions. We propose a new method to generate polycrystalline microstructures which incorporates higher order spatial correlations. These added statistics enable generative models to better express a desired grain morphology and capture spatial patterns of orientations. Our method also allows for easy interpolation between polycrystalline structures allowing for the creation of large datasets from limited experimental data. We will discuss the necessary theoretical and computational development as well as showcase potential applications. |
Proceedings Inclusion? |
Planned: |
Keywords |
Computational Materials Science & Engineering, Machine Learning, Modeling and Simulation |