Generating microstructures for materials based on machine learning models
US12118645B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Dec 16, 2021 |
| Grant date | Oct 15, 2024 |
| Priority date | — |
| Expiry date | Jun 8, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment, a method is provided. The method includes determining a set of spheres for a volume of a material. The volume of the material comprises the set of spheres and additional materials. The sizes of the set of spheres are based on a Gaussian mixture model (GMM). The method also includes determining a set of locations for the set of spheres within the volume of the material. The method further includes generating a set of images of the volume of the material based on a first generative adversarial network and a second generative adversarial network. The set of images depict a microstructure of the volume of material.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.