Invention Grant
- Patent Title: Systems and methods for generating reduced order models
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Application No.: US16253635Application Date: 2019-01-22
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Publication No.: US11409923B1Publication Date: 2022-08-09
- Inventor: Stephane Marguerin , Michel Rochette , Bernard Dion , Lucas Boucinha
- Applicant: Ansys, Inc.
- Applicant Address: US PA Canonsburg
- Assignee: Ansys, Inc.
- Current Assignee: Ansys, Inc.
- Current Assignee Address: US PA Canonsburg
- Main IPC: A61F2/28
- IPC: A61F2/28 ; G06Q50/18 ; G06Q20/40 ; G06N3/04 ; G06F30/23 ; G06F30/20 ; G06N3/12 ; G06F111/10

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.
Information query
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