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Data-Driven Turbulence Modeling: Summary and Outcomes of the 2022 NASA SymposiumA three-day symposium sponsored by NASA was held in July 2022 in Suffolk, Virginia on the subject of Turbulence Modeling: Roadblocks, and the Potential for Machine Learning. This meeting brought together over 80 experts from academia, government, and industry to discuss critical issues for Reynolds-averaged Navier-Stokes (RANS) turbulence and transition models, as well as to evaluate the results from a collaborative testing challenge based on data-driven methods and machine learning (ML) technology. The symposium represents a continuation of an earlier symposium sponsored by the University of Michigan and NASA, held in Ann Arbor, MI in 2017. The 2022 symposium included a wide variety of talks on the subjects of RANS and ML, five invited talks, and three panel discussions. This talk summarizes the main outcomes of the symposium, and includes suggested recommendations and future directions.
Document ID
20220015694
Acquisition Source
Langley Research Center
Document Type
Presentation
Authors
Chris Rumsey
(Langley Research Center Hampton, Virginia, United States)
Gary Coleman
(Langley Research Center Hampton, Virginia, United States)
Date Acquired
October 19, 2022
Subject Category
Aerodynamics
Meeting Information
Meeting: High-Fidelity Large-Eddy Simulations (LES) and Direct Numerical Simulations (HiFiLeD) Symposium 2022
Location: Brussels
Country: BE
Start Date: December 14, 2022
End Date: December 16, 2022
Sponsors: European Research Community On Flow, Turbulence and Combustion
Funding Number(s)
WBS: 109492.02.07.05.01
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Keywords
machine learning
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