About this Abstract |
| Meeting |
MS&T26: Materials Science & Technology
|
| Symposium
|
Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
|
| Presentation Title |
Decoupling Energy Density Effects in Laser Powder Bed Fusion of Aluminum Alloy |
| Author(s) |
Caleb Beckwith, Rajesh Subramani, Mrityunjay Doddamani, Nikhil Gupta |
| On-Site Speaker (Planned) |
Nikhil Gupta |
| Abstract Scope |
The laser powder bed fusion (PBF) additive manufacturing technology is now widely used for manufacturing aluminum alloy components for a variety of applications. This work investigates PBF processing of AlF357 aluminum alloy under controlled energy density conditions, while systematically varying the parameters such as laser power and scan speed used to achieve that density to generate eight distinct parameter sets. Although the overall energy input is held constant, these parameter combinations alter thermal histories, melt pool stability, and solidification conditions, leading to distinct microstructural features. Resulting specimens are characterized through microstructural analysis to quantify grain morphology followed by mechanical testing. This work demonstrates that nominally equivalent energy densities produce markedly different performance outcomes and further optimization of processing parameters is possible for obtaining improved properties. These findings provide critical insight into process–structure–property relationships in PBF for future process optimization and development for metal additive manufacturing. |