Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bluff body uses deep-reinforcement-learning trained active flow control
  to achieve hydrodynamic stealth   We propose a novel active-flow-control (AFC) strategy for bluff bodies to
hide their hydrodynamic traces from predators. A group of
windward-suction-leeward-blowing (WSLB) actuators are adopted to control the
wake of a circular cylinder submerged in a uniform flow. An array of velocity
sensors are deployed in the near wake to provide feedback signals. Through the
data-driven deep reinforcement learning (DRL), effective control strategies are
trained for the WSLB actuation to mitigate the cylinder's hydrodynamic
signatures, i.e., strong shears and periodically shed vortices. Only a 0.29%
deficit in streamwise velocity is detected, which is a 99.5% reduction from the
uncontrolled value. The same control strategy is found to be also effective
when the cylinder undergoes transverse vortex-induced vibration (VIV). The
findings from this study can shed some lights on the design and operation of
underwater structures and robotics to achieve hydrodynamic stealth.

30
The categories of this paper are: q-alg
23
The categories of this paper are: solv-int
9
The categories of this paper are: nlin
28
The categories of this paper are: alg-geom
27
The categories of this paper are: comp-gas
10
The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
8
The categories of this paper are: hep-ex
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org
5
The categories of this paper are: gr-qc