About this Abstract |
Meeting |
Superalloys 2024
|
Symposium
|
Superalloys 2024
|
Presentation Title |
C-11: Prediction of the Creep Strength of Single Crystalline Superalloys via a Microstructure-informed Deep Neural Network |
Author(s) |
Andreas Bezold, Toni Albert, Mathias Göken, Steffen Neumeier |
On-Site Speaker (Planned) |
Andreas Bezold |
Abstract Scope |
The design of superalloys is traditionally based on numerous experimental iterations guided by expert insights. The advent of computational tools that can calculate and predict thermophysical and mechanical properties has transformed this process. These tools have facilitated the discovery and evaluation of new alloys, leading to advancements in high-temperature capabilities and other design objectives, such as reducing the content of Re. |
Proceedings Inclusion? |
Definite: At-meeting proceedings |