  We numerically investigate the flow control problem of the flow passing a
stationary cylinder at a fixed Reynold number 500 using two attached control
cylinders with different rotation rates. Compared to the traditional uniform
(lattice) sampling method, we developed an active learning strategy based on
Gaussian Process Regression (GPR), drastically reducing the number of
simulations and accelerating the scientific findings. We also discussed the
effects of parameters on different hydrodynamic coefficients, and verified the
feasibility of this strategy. The mechanism of this asymmetric flow control
model was also further studied by analyzing flow patterns.
