59 citations · 168 across the 5 of their papers we have counts for
5 papers
Cluster-based hierarchical network model of the fluidic pinball -- Cartographing transient and post-transient, multi-frequency, multi-attractor behaviour
Nan Deng, Bernd R. Noack, Marek Morzyński +1
We propose a self-supervised cluster-based hierarchical reduced-order modelling methodology to model and analyse the complex dynamics arising from a sequence of bifurcations for a…
Stabilization of the fluidic pinball with gradient-enriched machine learning control
Guy Y. Cornejo Maceda, Yiqing Li, François Lusseyran +2
We stabilize the flow past a cluster of three rotating cylinders, the fluidic pinball, with automated gradient-enriched machine learning algorithms. The control laws command the ro…
Galerkin force model for transient and post-transient dynamics of the fluidic pinbal
Nan Deng, Bernd R. Noack, Marek Morzyński +1
We propose an aerodynamic force model associated with a Galerkin model for the unforced fluidic pinball, the two-dimensional flow around three equal cylinders with one radius dista…
Towards human-interpretable, automated learning of feedback control for the mixing layer
Hao Li, Guy Y. Cornejo Maceda, Yiqing Li +3
We propose an automated analysis of the flow control behaviour from an ensemble of control laws and associated time-resolved flow snapshots. The input may be the rich data base of…
Cluster-based network model
Hao Li, Daniel Fernex, Richard Semaan +3
We propose an automatable data-driven methodology for robust nonlinear reduced-order modelling from time-resolved snapshot data. In the kinematical coarse-graining, the snapshots a…