| About this Abstract |
| Meeting |
2023 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2023)
|
| Symposium
|
2023 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2023)
|
| Presentation Title |
Component Geometry Feature-based Heat Source Model for Temperature History Fast Prediction in the Directed Energy Deposition Process |
| Author(s) |
Lei Yan, Wei Gao, Frank Liou |
| On-Site Speaker (Planned) |
Lei Yan |
| Abstract Scope |
Temperature prediction is critical in metal directed energy deposition (DED) for process parameters optimization, especially comes to components with large sizes and complex geometry features. To improve prediction efficiency with accuracy guaranteed, a component geometry feature-based heat source model is proposed and developed with ANSYS APDL. The heat source model is applied layer-wise and has energy intensity redistributed according to the geometry features of each slice. Predicted temperature history is validated with thermocouple data and shows a maximum 50K temperature difference. This model provides a promising tool for high-efficiency process window optimization. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |