| About this Abstract |
| Meeting |
2022 TMS Annual Meeting & Exhibition
|
| Symposium
|
Defects and Properties of Cast Metals IV
|
| Presentation Title |
Uncertainty Quantification of Model Predictions due to Fluid Flow in Laser Powder Bed Fusion of IN625 |
| Author(s) |
Scott M. Wells, Matthew J. M. Krane |
| On-Site Speaker (Planned) |
Scott M. Wells |
| Abstract Scope |
Computational modeling of the laser powder bed fusion process is often restricted to the conduction dominant regime whereby advective heat transfer and fluid flow can be disregarded. Under processing conditions that result in high energy densities, fluid flow driven by Marangoni effects influence the uncertainty in solidification dynamics and melt pool dimensions which affect the as-built microstructure and scan strategies development. Using a computational fluid dynamics model for melt pool predictions of Inconel 625, and applying sparse grids and interpolation techniques, the uncertainty in input parameters including thermophysical properties and the surface tension gradient can be propagated to predictions of solidification time, cooling rates, and melt pool geometries. Results show the uncertainty in surface tension gradient had the largest affect of melt pool dimensions whereas uncertainty in laser absorptivity and specific heat capacity were the most influential on the solidification dynamics. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Computational Materials Science & Engineering, Modeling and Simulation |