About this Abstract |
Meeting |
2022 TMS Annual Meeting & Exhibition
|
Symposium
|
Additive Manufacturing: Materials Design and Alloy Development IV: Rapid Development
|
Presentation Title |
Applications of a Subspace-inclusive Sampling Method for the Computational Design of Compositionally Graded Alloys |
Author(s) |
Marshall Allen, Raymundo Arroyave, Richard Malak |
On-Site Speaker (Planned) |
Marshall Allen |
Abstract Scope |
Previously, the authors developed a compositionally graded alloy design algorithm that avoids common problems, such as deleterious phases, while optimizing for performance objectives. This previous methodology was limited in that it only sampled the interior of the composition space. Since even small amounts of additional alloying elements can introduce new deleterious phases, this characteristic often neglected potentially simpler solutions to otherwise unsolvable problems such as using a single component in a layer, or navigating a binary subsystem, and, consequently, discouraged adding elements to the state space. In this work, the authors developed a new sampling method that considers all subspaces of the composition state space. Ultimately, this advancement facilitates a complete investigation of the composition space and thereby more robust and flexible gradient design. This improved methodology could enable solutions for difficult problems like grading 6-4 titanium and aluminum alloys or grading for properties like stacking fault energy. |
Proceedings Inclusion? |
Planned: |
Keywords |
Additive Manufacturing, Computational Materials Science & Engineering, |