About this Abstract |
Meeting |
2022 TMS Annual Meeting & Exhibition
|
Symposium
|
Algorithm Development in Materials Science and Engineering
|
Presentation Title |
Highly Accurate Prediction of Material Microstructure Using High-performance Phase-field Simulation and Data Assimilation |
Author(s) |
Tomohiro Takaki |
On-Site Speaker (Planned) |
Tomohiro Takaki |
Abstract Scope |
A phase-field model is a numerical model that is widely employed for simulating material microstructure evolution because it exhibits higher accuracy than other models. However, lack of material parameters is the primary issue that needs to be addressed in phase-field studies. Presently, there are no effective methods for determining such material parameters both through experiments and simulations. A solution for addressing this issue is to conduct phase-field simulation by simultaneously performing the experiments or molecular dynamics simulations. To this end, data assimilation is a promising technique that integrates the aforementioned two methods. Furthermore, application of data assimilation has become possible owing to the recent advancements in computer performance, such as computing using graphics processing units. In this presentation, I will demonstrate our current approach for determining material parameters by utilizing both high-performance phase-field simulation and data assimilation. |
Proceedings Inclusion? |
Planned: |
Keywords |
Modeling and Simulation, Computational Materials Science & Engineering, Solidification |