About this Abstract |
| Meeting |
MS&T25: Materials Science & Technology
|
| Symposium
|
Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
|
| Presentation Title |
Melt Pool Plume Behavior in Laser Powder Bed Fusion |
| Author(s) |
Jack L Beuth, Alexander Myers, Christian Gobert, Jonathan Malen |
| On-Site Speaker (Planned) |
Jack L Beuth |
| Abstract Scope |
In this work, high-speed imaging with varied processing conditions and materials is used to understand the behavior of melt pool vapor plume in a commercial laser powder bed fusion machine. Metrics for characterizing the plume are chosen related to its size, trajectory, and severity. A U-Net convolutional neural network (CNN) is trained to segment the plume from experimental images. Process mapping the plume in power and scanning velocity space shows that the plume transitions from ejecting toward the rear of the melt pool in the transitional regime to ejecting directly above the melt pool in both the severe keyholing and conduction-dominated regimes, consistent with the vapor depression geometry under the laser. The effect of powder is studied for both Ti-6Al-4V and 316L SS. The temporal variability of the plume increases with increasing power-to-velocity ratio, which is attributed to melt pool and vapor depression instability. |