Completed
Data-driven Modeling of Traveling Waves
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Fluid Dynamics
Automatically move to the next video in the Classroom when playback concludes
- 1 Machine Learning for Fluid Mechanics
- 2 Machine Learning for Fluid Dynamics: Patterns
- 3 Machine Learning for Fluid Dynamics: Models and Control
- 4 What Is Turbulence? Turbulent Fluid Dynamics are Everywhere
- 5 Turbulence is Everywhere! Examples of Turbulence and Canonical Flows
- 6 Turbulence: Reynolds Averaged Navier-Stokes (Part 1, Mass Continuity Equation)
- 7 Turbulence: Reynolds Averaged Navier Stokes (RANS) Equations (Part 2, Momentum Equation)
- 8 Turbulence Closure Models: Reynolds Averaged Navier Stokes (RANS) & Large Eddy Simulations (LES)
- 9 Deep Learning for Turbulence Closure Modeling
- 10 Deep Reinforcement Learning for Fluid Dynamics and Control
- 11 Robust Principal Component Analysis (RPCA)
- 12 Robust Modal Decompositions for Fluid Flows
- 13 Data-driven nonlinear aeroelastic models of morphing wings for control
- 14 Data-driven Modeling of Traveling Waves
- 15 Finite-Horizon, Energy-Optimal Trajectories in Unsteady Flows
- 16 Modeling synchronization in turbulent flows
- 17 Data-Driven Resolvent Analysis
