| 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 |
A Machine Learning Approach to Part Scale Microstructure Predictions in LPBF |
| Author(s) |
Mason Jones, Brian Weston, Theron Rodgers, Daniel Moser, Jean-Pierre Delplanque |
| On-Site Speaker (Planned) |
Mason Jones |
| Abstract Scope |
Laser powder bed fusion additive manufacturing uses microscale processes to create macroscale parts with complex microstructures. This makes part-scale modeling and simulation of microstructures challenging and expensive. A newly developed machine learning based surrogate microstructure model for this process has been shown to significantly accelerate predictions of microstructure statistics while maintaining accuracy. This work uses ensemble modeling in conjunction with this surrogate model to identify and explore viable routes for scaling this surrogate model to part scale predictions for the purposes of process parameter optimization. This will include analysis and refinement of the surrogate model as well as statistical analyses to identify shortcuts to part scale modeling. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |