Machine learning based rotor alloy design system
US11676009B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 4, 2019 |
| Grant date | Jun 13, 2023 |
| Priority date | — |
| Expiry date | Nov 18, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/82
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for designing a material for an aircraft component according to one example includes training a neural network to correlate microstructural features of an alloy with material properties of the alloy by at least providing a set of images of the alloy. Each of the images in the set of images has varied constituent compositions and at least one patch of corresponding data is embedded into the image. The method also includes determining non-linear relationships between the microstructural features and corresponding empirically determined material properties via a machine learning algorithm, receiving a set of desired material properties of the alloy for aircraft component, and determining a set of microstructural features capable of achieving the desired material properties of the alloy based on the determined non-linear relationships.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.