About this Abstract |
Meeting |
2022 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2022)
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Symposium
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2022 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2022)
|
Presentation Title |
NEW TIME (was 1:30 pm) A Data-driven Model for Reconstructing 3D Melt Pool Geometries in Additive Manufacturing |
Author(s) |
Shuheng Liao, Jian Cao |
On-Site Speaker (Planned) |
Shuheng Liao |
Abstract Scope |
In metal additive manufacturing processes, melt pool size can influence the geometric accuracy and material properties of the fabricated part. While online monitoring and control of the 2D melt pool size have been successfully developed, controlling the 3D melt pool characteristic, i.e., melt pool depth or melt pool volume is still challenging because the 3D melt pool geometry cannot be directly monitored during the process. In this study, a data-driven model is proposed to reconstruct the 3D melt pool geometries from the 2D melt pool images. Synthetic data generated from FEM simulation are generated and used to train the proposed model. Experimental validation of the developed model will be provided. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |