Data Driven Fluid Dynamics

Data Driven Fluid Dynamics

Brunton Lab, University of Washington

This series gives an overview of data driven fluid mechanics.

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On Twitter: @eigensteve
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Speakers
Community
Prof. Steven L. Brunton
Assoc. Prof. Ricardo Vinuesa
Brunton Lab
Brunton Lab
Royal Institute of Technology

Enhancing Computational Fluid Dynamics with Machine Learning

Ricardo Vinuesa, Royal Institute of Technology
University of Washington

Sparse Nonlinear Models for Fluid Dynamics with Machine Learning and Optimization

Steven L. Brunton, University of Washington
University of Washington

Lagrangian Coherent Structures (LCS) in unsteady fluids with Finite Time Lyapunov Exponents (FTLE)

Steven L. Brunton, University of Washington
University of Washington

Machine Learning for Computational Fluid Dynamics

Steven L. Brunton, University of Washington
University of Washington

Deep Learning for Turbulence Closure Modeling

Steven L. Brunton, University of Washington
University of Washington

Turbulence Closure Models: Reynolds Averaged Navier Stokes (RANS) & Large Eddy Simulations (LES)

Steven L. Brunton, University of Washington
University of Washington

Turbulence: Reynolds Averaged Navier Stokes (RANS) Equations (Part 2, Momentum Equation)

Steven L. Brunton, University of Washington
University of Washington

Turbulence: Reynolds Averaged Navier-Stokes (Part 1, Mass Continuity Equation)

Steven L. Brunton, University of Washington
University of Washington

Turbulence is Everywhere! Examples of Turbulence and Canonical Flows

Steven L. Brunton, University of Washington