About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Materials Processing Fundamentals: Towards Sustainable Process Modeling, Design, and Operation
|
| Presentation Title |
Applications of Machine Learning and AI in HPC4EI-Funded Projects for Manufacturing and Materials Research |
| Author(s) |
Victor M. Castillo |
| On-Site Speaker (Planned) |
Victor M. Castillo |
| Abstract Scope |
The High-Performance Computing for Energy Innovation (HPC4EI) Program is a DOE-funded program that leverages HPC resources from twelve participating national laboratories to help address challenges of domestic manufacturers. These projects typically use computer simulations to virtually explore key industrial processes under a variety of conditions. To date, 192 projects have been awarded, of which over a quarter have used machine learning (ML) and AI methods.
This talk will provide a survey of how ML / AI methods are used in addition to the HPC simulations. These include advanced computer vision applications, reduced-order model development, and accelerating inner loop constitutive and sub-grid scale models. We will also provide estimated impacts on productivity and energy savings. |
| Proceedings Inclusion? |
Planned: |