About this Abstract |
| Meeting |
MS&T25: Materials Science & Technology
|
| Symposium
|
Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
|
| Presentation Title |
Cellular Automata Modeling of Microstructure and Porosity Formation in Al-10Si Alloy Laser Powder Bed Fusion Process |
| Author(s) |
Buwei Chen, Michael Moodispaw, Jianyue Zhang, Qigui Wang, Alan Luo |
| On-Site Speaker (Planned) |
Buwei Chen |
| Abstract Scope |
Laser Powder Bed Fusion (LPBF) of aluminum alloys enables high-precision metal additive manufacturing (AM), but challenges such as hydrogen porosity and microstructural variation hinder component reliability. This study presents an advanced Cellular Automata (CA) model to simulate grain evolution and hydrogen porosity formation in an Al-10Si alloy during LPBF. The model incorporates a realistic melt pool temperature profile, non-equilibrium grain growth under rapid cooling, and a supersaturation-based pore nucleation criterion. Predicted grain and porosity size and morphology show strong agreement with experimental results. The transition from fine columnar to equiaxed grains across the melt pool is well captured. Two porosity morphologies—spherical and intergranular—are observed in both simulation and experiment, and their possible formation mechanisms are discussed. This framework offers a computationally efficient tool for understanding defect evolution and supports process parameter optimization in AM of aluminum alloys. |