5 papers
Mean-flow-based reduced-order models of turbulent channel flow
Ian Addison-Smith, Igor A. Maia, André V. G. Cavalieri +1
Reduced-order models (ROMs) for turbulent flows based on Galerkin projection can achieve reasonable accuracy using equation-based modal bases derived from the linearized Navier-Sto…
Train yourself: self-compressing reduced-order models of turbulent flows
Ian Addison-Smith, Igor A. Maia, Benjamin Herrmann +1
Reduced-order models (ROMs) of turbulent flows based on Galerkin projection often require many degrees of freedom to resolve the dynamics of the turbulence, or simulation data to o…
SINDy on slow manifolds
Diemen Delgado-Cano, Erick Kracht, Urban Fasel +1
The sparse identification of nonlinear dynamics (SINDy) has been established as an effective method to learn interpretable models of dynamical systems from data. However, for high-…
Interpretable low-order representation of eigenmode deformation in parameterized dynamical systems
Nicolas Torres-Ulloa, Erick Kracht, Urban Fasel +1
Modal analysis has long been consolidated as a basic tool to interpret dynamics and build low-order models of mechanical, thermal, and fluid systems. Eigenmodes arising from the sp…
Multi-objective SINDy for parameterized model discovery from single transient trajectory data
Javier A. Lemus, Benjamin Herrmann
The sparse identification of nonlinear dynamics (SINDy) has been established as an effective technique to produce interpretable models of dynamical systems from time-resolved state…