| About this Abstract |
| Meeting |
2025 TMS Annual Meeting & Exhibition
|
| Symposium
|
Powder Materials Processing and Fundamental Understanding
|
| Presentation Title |
DEM Modeling of Spherical Particles to Improve Packing Density and Debind Performance in Sinter-Based Additive Manufacturing Processes |
| Author(s) |
Nathan Jump, Pei Sun, Zak Fang |
| On-Site Speaker (Planned) |
Nathan Jump |
| Abstract Scope |
Discrete Element Method (DEM) modeling of spherical powders has shown high accuracy in additive manufacturing (AM) processes like Laser Powder Bed Fusion (LPBF) and Binder Jetting (BJT). Traditional models focusing on packing density often use simplified particle size distributions (PSD), limiting further advancements. This study integrates realistic powder dimensions from imaging techniques and sieve-size isolated particles to generate model-predicted blends closely mirroring actual powder characteristics. The findings reveal significant improvements in packing density, deeper insights into particle-binder interactions, and reduced interstitial element pick-up during consolidation processes in reactive metals like titanium. By refining DEM models with realistic inputs, this work addresses common issues in powder consolidation, such as porosity and coarse microstructures. This research aims to optimize powder blends in sinter-based manufacturing, enhancing process performance and cost-efficiency. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Modeling and Simulation, Powder Materials, Additive Manufacturing |