About this Abstract |
Meeting |
2021 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2021)
|
Symposium
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Physical Modeling
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Presentation Title |
Predicting Part Distortion and Recoater Crash in Laser Powder Bed Fusion Using Graph Theory |
Author(s) |
Humaun Kobir, Reza Yavari, Alex Riensche, Leandro Castro, Ben Bevans, Kevin Cole, Prahalada Rao |
On-Site Speaker (Planned) |
Humaun Kobir |
Abstract Scope |
The laser powder bed fusion (LPBF) process tends to create flaws, such as part distortion, which limits its use for making mission-critical components. Flaw formation in LPBF parts is influenced by the temperature distribution (thermal history) during the process. To preclude flaw formation, such as distortion (deformation) and subsequent recoater crash, a key need is to develop fast and accurate models to predict the thermal history. Accordingly, we developed a graph theory-based thermal model that predicts the thermal history of the LPBF in less than 20% of the time taken by finite element-based models (FEM). Subsequently, the thermal history from the graph theory was coupled with FEM to predict distortion. This hybrid model is verified with FEM and Netfabb. it is also validated with the experimental data in the context of recoater crash prediction. The approach correctly predicted recoater crashes and distortion within 5% of FEM predictions. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |