Our group focuses on uncovering the mechanisms of near-wall turbulence using novel techniques driven by data and physics to enable highly-maneuverable vehicles and cheap, accurate turbulence predictions.

Machine Learning and Turbulence

Data-driven methods & Reinforcement learning

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Turbulence modeling for large-eddy simulation

Subgrid-scale modeling & Wall modeling

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Mechanisms of near-wall turbulence

Coherent structures in wall-turbulence & Self-sustaining process of wall-bounded turbulence

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