Machine learning-based method for designing high-strength high-toughness steel
US12242779B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 28, 2021 |
| Grant date | Mar 4, 2025 |
| Priority date | — |
| Expiry date | Jan 3, 2044 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02P90/30
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A machine learning-based method for designing a high-strength high-toughness steel, including: (S1) obtaining data and filling in missing parts to form a data set; (S2) selecting feature data in the data set to form a standard data set; (S3) constructing two machine learning models of the high-strength high-toughness steel; (S4) completing training after the two models are evaluated to be qualified; (S5) finding frontier points, drawing a Pareto front, and distinguishing a known region and a feature space; (S6) in the feature space, setting a step for the feature data, drawing a grid space, and performing multiple training predictions on each grid point by using the models, to obtain predicted Gaussian distributions of two objectives; and (S7) searching for an expected improvement point through an efficient global optimization algorithm, and obtaining design parameter values of corresponding features.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.