About this Abstract |
Meeting |
2023 TMS Annual Meeting & Exhibition
|
Symposium
|
Advances in Magnetic Materials
|
Presentation Title |
Computer-aided Optimization of Packing Behavior of Soft-magnetic Amorphous Powder |
Author(s) |
Jungjoon Kim, Junhyub Jeon, Seok-Jae Lee, Youngkyun Kim, Hwi-Jun Kim, Youngjin Kim, Hyunjoo Choi |
On-Site Speaker (Planned) |
Jungjoon Kim |
Abstract Scope |
For the effective use of magnetic materials, many studies have investigated the prevention of magnetic dilution by increasing the density of the magnetic material. To prepare ceramic or crystalline magnetic materials, high-temperature and high-pressure processes are used. However, when these processes are used to prepare amorphous materials, their magnetic properties deteriorate due to crystallization.
This study investigated the change in packing fraction by varying the mixing ratios of different-sized powders. We determined the mixing ratio of high-density powders using various approaches, including simulation, theoretical modeling, experimental verification, and machine learning. These methods enabled us to achieve results similar to those obtained when simulating the behavior of an actual powder, as the interaction of the powder can be reflected by the angle of repose. Finally, our study found that the packing fraction was improved through the machine learning approach. |
Proceedings Inclusion? |
Planned: |
Keywords |
Magnetic Materials, Modeling and Simulation, Machine Learning |