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Using Machine-Learning to Develop Non-Traditional Unsteady RANS Capabilities for Accurate Flow and Noise Predictions of Naval Applications

Grant number: N62909-20-1-2046 | Funding period: 2020 - 2024

Completed

Related publications (3)

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Challenges and perspective on the modelling of high-Re, incompressible, non-equilibrium, rough-wall boundary layers

R García-Mayoral, D Chung, P Durbin, N Hutchins, T Knopp, BJ McKeon, U Piomelli, RD Sandberg

2024-01-01

The present paper gives an overview of the recent modelling activities under NATO-STO AVT-349, focussed on the understanding and m..

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Non-equilibrium turbulent boundary layers in high reynolds number flow at incompressible conditions: effects of streamline curvature and three dimensionality

T Lowe, AJ Smits, M Visonneau, G Deng, L Ding, E Guilmineau, R Sandberg, A Haghiri, A Gargiulo, J Duetsch-Patel, P Lavoie, D MacGregor, L Savio, YL Jenssen, C Roy, O Williams, S Toxopeus, W Devenport

2024-01-01

The physics and computational prediction of turbulent boundary layer flow over axisymmetric and three-dimensional bodies are exami..

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Modeling the Surface Pressure Spectrum Beneath Turbulent Boundary Layers in Pressure Gradients

DJ Fritsch, V Vishwanathan, CJ Roy, KT Lowe, WJ Devenport, P Croaker, O Tkachenko, D Pook, G Lane, S Shubham, RD Sandberg

2023-05-01

A wide variety of models and methods for the prediction of the surface pressure spectrum beneath turbulent boundary layers is pres..

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Richard Sandberg

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