About this Abstract |
| Meeting |
MS&T25: Materials Science & Technology
|
| Symposium
|
Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
|
| Presentation Title |
Interpreting Peak Temperature Distributions in Laser Powder Bed Fusion Through Surface Geometry and Simulated Imaging |
| Author(s) |
Craig Weeks, Jonathan Malen, Satbir Singh |
| On-Site Speaker (Planned) |
Craig Weeks |
| Abstract Scope |
Understanding the formation of defects in Laser powder bed fusion (L-PBF) is important for manufacturing parts that perform to desired specifications. The region of molten material underneath the laser beam and inside the vapor depression governs the formation of keyhole porosity in the final part as well as the alloy composition due to preferential evaporation of elements. Although this region is important to defect formation, it is not well quantified by current experimental techniques such as thermal imaging because of reflections in the vapor depression that distort the perceived temperature. We present a method for simulating thermal imaging experiments on difficult concave surfaces that accounts for these reflections. The method can reproduce experimental temperatures and gives insight into what vapor depression temperatures are possible. This method can be used by both experimentalists and modelers to help control part porosity, determine powder feedstock alloy composition, and validate multi-physics models. |