Systems and methods for generating reduced order models
US11409923B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 22, 2019 |
| Grant date | Aug 9, 2022 |
| Priority date | — |
| Expiry date | Jun 10, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for generating reduced order models are provided herein. In embodiments, a set of learning points is identified in a parametric space. A 3D physical solver may be used to perform a simulation for each learning point in the set of learning points to generate a learning data set, where the 3D physical solver is selected from a plurality of compatible 3D physical solvers for simulating different physical aspects of a product or process. The learning data set may be compressed to reduce the learning data set to a smaller set of vectors. Coefficients from the learning data set and the smaller set of vectors may then be used to interpolate a set of coefficients within a design space for the reduced order model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.