91 citations · 251 across the 10 of their papers we have counts for
11 papers
From resolvent to Gramians: extracting forcing and response modes for control
Benjamin Herrmann, Peter J. Baddoo, Scott T. M. Dawson +3
During the last decade, forcing and response modes produced by resolvent analysis have demonstrated great potential to guide sensor and actuator placement and design in flow contro…
Pilot-Wave Dynamics: Using Dynamic Mode Decomposition to characterize Bifurcations, Routes to Chaos and Emergent Statistics
J. Nathan Kutz, Andre Nachbin, Peter J. Baddoo +1
We develop a data-driven characterization of the pilot-wave hydrodynamic system in which a bouncing droplet self-propels along the surface of a vibrating bath. We consider drop mot…
Physics-informed dynamic mode decomposition (piDMD)
Peter J. Baddoo, Benjamin Herrmann, Beverley J. McKeon +2
In this work, we demonstrate how physical principles -- such as symmetries, invariances, and conservation laws -- can be integrated into the dynamic mode decomposition (DMD). DMD i…
Generalization of waving-plate theory to multiple interacting swimmers
Peter J. Baddoo, Nicholas J. Moore, Anand U. Oza +1
Early research in aerodynamics and biological propulsion was dramatically advanced by the analytical solutions of Theodorsen, von Kármán, Wu and others. While these classical solut…
Kernel Learning for Robust Dynamic Mode Decomposition: Linear and Nonlinear Disambiguation Optimization (LANDO)
Peter J. Baddoo, Benjamin Herrmann, Beverley J. McKeon +1
Research in modern data-driven dynamical systems is typically focused on the three key challenges of high dimensionality, unknown dynamics, and nonlinearity. The dynamic mode decom…
Data-driven resolvent analysis
Benjamin Herrmann, Peter J. Baddoo, Richard Semaan +2
Resolvent analysis identifies the most responsive forcings and most receptive states of a dynamical system, in an input--output sense, based on its governing equations. Interest in…