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physics.flu-dyn2026
Physics-guided surrogate learning enables zero-shot control of turbulent wings
Yuning Wang, Pol Suarez, Mathis Bode +1
Turbulent boundary layers over aerodynamic surfaces are a major source of aircraft drag, yet their control remains challenging due to multiscale dynamics and spatial variability, p…
physics.flu-dyn2026
Modeling subgrid scale production rates on complex meshes using graph neural networks
Priyabrat Dash, Mathis Bode, Konduri Aditya
Large-eddy simulations (LES) require closures for filtered production rates because the resolved fields do not contain all correlations that govern chemical source terms. We develo…
physics.flu-dyn2026
Super-resolution of turbulent reacting flows on complex meshes using graph neural networks
Priyabrat Dash, Konduri Aditya, Christos E. Frouzakis +1
State-of-the-art deep learning models have been extensively utilized to reconstruct small-scale structures from coarse-grained data in turbulent flows. However, their application h…