About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Additive Manufacturing of Metals: Multiscale and Non-Equilibrium Solidification Fundamentals
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| Presentation Title |
An Overview of Current Efforts in Developing a Digital Twin Framework for Laser-based Additive Manufacturing Processes of Metallic Systems |
| Author(s) |
Dilip Kumar Banerjee, Daniel Wheeler |
| On-Site Speaker (Planned) |
Dilip Kumar Banerjee |
| Abstract Scope |
An effort is underway to construct a digital twin (DT) framework designed for rapid feedback and control of materials microstructure in the laser-based metals additive manufacturing (AM) processes such as laser powder bed fusion (L-PBF) and directed energy deposition (DED) processes. The objectives are to develop well-verified multiscale physics-based models, integrate data assimilation (DA) techniques with ensemble and reduced order modeling approaches, develop surrogate models to accelerate DT framework predictions, and develop tools for workflow management. This presentation will discuss our research efforts for AM DT development by choosing an example of multiscale L-PBF process simulation of a titanium alloy where the modeling involves sequential simulation of heat transfer, thermal stress distribution, and microstructural evolution with a phase field model. Some of the challenges in developing surrogate models, data assimilation, and building a robust approach for uncertainty quantification (UQ) associated with the DT framework development will be briefly addressed. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Computational Materials Science & Engineering, Machine Learning |