From the 1 of 8 linked papers with an AI index.
5 papers · 1 filter
Observer-based neural networks for flow estimation and control
TarcÃsio 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…
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…
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…
Wavelet-based resolvent analysis of non-stationary flows
Eric Ballouz, Barbara Lopez-Doriga, Scott T. M. Dawson +1
This work introduces a formulation of resolvent analysis that uses wavelet transforms rather than Fourier transforms in time. Under this formulation, resolvent analysis may extend…
Sparse space-time resolvent analysis for statistically-stationary and time-varying flows
Barbara Lopez-Doriga, Eric Ballouz, H. Jane Bae +1
Resolvent analysis provides a framework to predict coherent spatio-temporal structures of largest linear energy amplification, through a singular value decomposition (SVD) of the r…