| About this Abstract |
| Meeting |
2024 TMS Annual Meeting & Exhibition
|
| Symposium
|
Functionally Graded Materials, Coatings and Claddings: Toward Microstructure and Property Control
|
| Presentation Title |
Gradient Design for Alloy Stacking Fault Energy with Autonomous Path Planning |
| Author(s) |
James Hanagan, Nicole Person, Daniel Salas, Daniel Lewis, Marshall Allen, Wenle Xu, Raymundo Arróyave, Brady Butler, Ibrahim Karaman |
| On-Site Speaker (Planned) |
James Hanagan |
| Abstract Scope |
Functionally graded materials (FGMs) are complex systems that require thoughtful consideration for not only the alloy compositions at each end of the gradient, but also those within the gradient itself. A novel method has been developed by the Arróyave group at Texas A&M Univeristy that adapts a path planning algorithm originally developed for robotics into compositional space for intelligent FGM design. This versatile framework allows for a great deal of control over the design of any metallic composition gradient, enabling gradients that are truly optimized from end to end. This presentation will focus on the application of this framework for the design of a gradient in alloy stacking fault energy (SFE) predicted by a machine-learned model developed by the Arróyave group. The computational design of the gradient, the underlying models and frameworks used, and characterization of the FGM manufactured via powder-blown directed energy deposition (DED) will be discussed. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Modeling and Simulation, Computational Materials Science & Engineering |