most citedTowards human-interpretable, automated learning of feedback control for the mixing layer

2 citations · 2 across the 1 of their papers we have counts for

collaborators

2 papers

physics.flu-dyn2020★ 2 cited

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…

physics.flu-dyn2020

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…