| About this Abstract |
| Meeting |
MS&T24: Materials Science & Technology
|
| Symposium
|
Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
|
| Presentation Title |
Modeling of Shape Transition from Conduction to Keyholing for AA6061 in the Laser Power Bed Fusion Additive Manufacturing |
| Author(s) |
Tianyu Zhang, Lang Yuan, Karna Sivaji, Al-Aridi Rimah, Can Sun, Baldauff Justin, Gross Andrew, Christian Rossmann, Timothy Krentz, Dale Hitchcock |
| On-Site Speaker (Planned) |
Tianyu Zhang |
| Abstract Scope |
In laser powder bed fusion, the transition from conduction to keyholing governs the morphology of the melt pool, profoundly influenced by melt dynamics and laser absorption. In this study, bead-on-plate experiments of AA6061 were conducted to explore melt pool morphologies evolution across varying laser power and speed parameters. Employing a machine learning algorithm, we classified melt pool, culminating in the generation of a processing map specifically for conduction mode melt pools. Notably, a distinct shift was observed between conduction and keyholing modes with a narrow range of energy density change, which has not been observed in other materials. Employing the numerical simulation by AdditiveLab software to replicate and further comprehend this phenomenon, distinct heat source configurations were proposed to unify the transition in melt pool modes, elucidating the underlying physics steering this transition. Furthermore, the transitional impact on the printing of bulk materials is discussed. |