About this Abstract |
Meeting |
2022 TMS Annual Meeting & Exhibition
|
Symposium
|
Materials Design and Processing Optimization for Advanced Manufacturing: From Fundamentals to Application
|
Presentation Title |
Towards Laser Powder Bed Process Optimization: An Approach for Fast Process-microstructure Predictions |
Author(s) |
Mason Jones, Jean-Pierre Delplanque |
On-Site Speaker (Planned) |
Mason Jones |
Abstract Scope |
This work investigates the feasibility of a fast method for predicting part scale microstructural characteristics of objects produced using the laser powder bed fusion process. Traditional predictive computational models for this process are at present too slow to be used for effective optimization of process parameters. The proposed approach uses a fast physics-based surrogate thermal model and identified thermal characteristics to predict selected microstructural characteristics. Verification of this method will be enabled by a custom SPPARKS kinetic Monte Carlo (KMC) application capable of using the temperature field predicted by the thermal model for predictions of the microstructure. The development of this KMC application and its validation using available experimental data will also be discussed. |
Proceedings Inclusion? |
Planned: |
Keywords |
Additive Manufacturing, Modeling and Simulation, |