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Exploring the Potential and the Practical Usability of a Machine Learning Approach for Improving Wall Friction Predictions of RANS Wall Functions in Non-equilibrium Turbulent Flows

Erwan Rondeaux, Adele Poubeau, Christian Angelberger, Miguel Munoz Zuniga, Damien Aubagnac-Karkar and Roberto Paoli

Article (2024)

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Department: Department of Mechanical Engineering
PolyPublie URL: https://publications.polymtl.ca/58114/
Journal Title: Flow Turbulence and Combustion
Publisher: Springer
DOI: 10.1007/s10494-024-00539-1
Official URL: https://doi.org/10.1007/s10494-024-00539-1
Date Deposited: 30 Apr 2024 12:41
Last Modified: 30 Apr 2024 12:41
Cite in APA 7: Rondeaux, E., Poubeau, A., Angelberger, C., Zuniga, M. M., Aubagnac-Karkar, D., & Paoli, R. (2024). Exploring the Potential and the Practical Usability of a Machine Learning Approach for Improving Wall Friction Predictions of RANS Wall Functions in Non-equilibrium Turbulent Flows. Flow Turbulence and Combustion, 26-26. https://doi.org/10.1007/s10494-024-00539-1

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