4 papers
Data-Driven Reduced-Complexity Modeling of Fluid Flows: A Community Challenge
Oliver T. Schmidt, Aaron Towne, Adrian Lozano-Duran +2
We introduce a community challenge designed to facilitate direct comparisons between data-driven methods for compression, forecasting, and sensing of complex aerospace flows. The c…
Observer-based neural networks for flow estimation and control
Tarcísio C. Déda, William R. Wolf, Scott T. M. Dawson +1
Neural network observers (NNOs) are proposed for real-time estimation of fluid flows, addressing a key challenge in flow control: obtaining real-time flow states from a limited set…
Sparsity-promoting methods for isolating dominant linear amplification mechanisms in wall-bounded flows
Scott T. M. Dawson, Jaime Prado Zayas, Barbara Lopez-Doriga
This work proposes a method to identify and isolate the physical mechanisms that are responsible for linear energy amplification in fluid flows. This is achieved by applying a spar…
Transient growth and nonlinear breakdown of wavelet-based resolvent modes in turbulent channel flow
Eric Ballouz, Scott T. M. Dawson, H. Jane Bae
We study the effectiveness of the time-localised principal resolvent forcing mode at actuating the near wall cycle of turbulence. The mode is restricted to a wavelet pulse and comp…