About this Abstract |
Meeting |
2025 TMS Annual Meeting & Exhibition
|
Symposium
|
Additive Manufacturing Modeling, Simulation and Machine Learning
|
Presentation Title |
Towards a Fully Predictive Additive Manufacturing Module |
Author(s) |
Amer Malik, Minh-Do Quang, Johan Jeppsson, Andreas Markström |
On-Site Speaker (Planned) |
Amer Malik |
Abstract Scope |
During the last years, Thermo-Calc has developed new models to predict thermophysical material properties using the CALPHAD method with unprecedented accuracy.
While the treatment of heat and fluid flow is state of the art in current FEM models, material properties are treated in a highly simplified manner. This gives us the unique possibility to address the solidification problem during Additive Manufacturing with the focus on a unified treatment of both process parameters and also alloy dependent thermophysical properties. A module for Additive Manufacturing, using this approach, was implemented in 2023b release.
The latest developments aim for a fully predictive module where the user input is minimal. Meaning physics-based properties, including absorptivity, can be automatically generated and that the module captures transition from conduction- to keyhole- mode including the impact of fluid flow. This talk will give insight in this development and how it can be applied to process/materials development. |
Proceedings Inclusion? |
Planned: |
Keywords |
Additive Manufacturing, Computational Materials Science & Engineering, Modeling and Simulation |