| About this Abstract |
| Meeting |
2024 TMS Annual Meeting & Exhibition
|
| Symposium
|
Thermodynamics and Kinetics of Alloys II
|
| Presentation Title |
Parametrizing Phase Field Models for Microstructure Evolution: AMMBER, the AI-enabled Microstructure Model BuildER |
| Author(s) |
W. Beck Andrews, Alexander Mensah, Shibo Tan, Jindong Huang, Sahana Prabhu, Wenhao Sun, Katsuyo Thornton |
| On-Site Speaker (Planned) |
W. Beck Andrews |
| Abstract Scope |
Phase field methods explicitly account for the morphology of the microstructure and can therefore be higher fidelity than analytical approaches to modeling microstructure evolution. For the complex alloy systems of practical interest, however, phase field models are limited by computational resources and the need to specify many kinetic and thermodynamic model parameters. Performant open-source phase field codes have been developed, but the challenge of appropriately parametrizing phase field models remains complex and time-consuming, even for experienced users. To address this challenge, we are developing AMMBER, the AI-enabled Microstructure Model BuildER, which will provide an automated process for extracting phase field parameters from many different sources of kinetic and thermodynamic data. In the current stage of this project, we are developing an automated framework for generating thermodynamic parameters for phase field simulations of microstructure evolution. As a demonstration, we consider solidification of Al-based alloys. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Modeling and Simulation, Machine Learning, Computational Materials Science & Engineering |