A divide-and-conquer machine learning approach for modeling turbulent flows
In this paper, a novel zonal machine learning (ML) approach for Reynolds-averaged Navier-Stokes (RANS) turbulence modeling based on the divide-and-conquer technique is introduced. This approach involves partitioning the flow domain into regions of flow physics called zones, training one ML model in...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Institute of Physics Inc.
2023
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| Subjects: | |
| Online Access: | View Fulltext in Publisher |