Schooling Hydrodynamics of 300 Fish
ORAL
Abstract
We present 2D and 3D Direct Numerical Simulations of the collective behaviour of 300 swimmers.
The study relies on solving the incompressible Navier Stokes equations using Adaptive Mesh Refinement
techniques, efficiently deployed on massively parallel computer architectures. The coordinated swimming
is achieved through synchronised control of the individual swimmer motions in response to the flow environment
by the Remember and Forget Experience Replay Reinforcement Learning framework developed in our group.
We examine the variation of hydrodynamic benefits with a progressive increase of the school size.
We demonstrate the importance of controlling the vorticity field generated by the synchronised swimmers and
present hydrodynamic quantities (pressure, drag) for the individual swimmers and the school.
The study relies on solving the incompressible Navier Stokes equations using Adaptive Mesh Refinement
techniques, efficiently deployed on massively parallel computer architectures. The coordinated swimming
is achieved through synchronised control of the individual swimmer motions in response to the flow environment
by the Remember and Forget Experience Replay Reinforcement Learning framework developed in our group.
We examine the variation of hydrodynamic benefits with a progressive increase of the school size.
We demonstrate the importance of controlling the vorticity field generated by the synchronised swimmers and
present hydrodynamic quantities (pressure, drag) for the individual swimmers and the school.
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Presenters
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Michail Chatzimanolakis
ETH Zurich, Switzerland
Authors
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Michail Chatzimanolakis
ETH Zurich, Switzerland
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Pascal Weber
ETH Zurich, Switzerland
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Michael Triantafyllou
MIT
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Petros Koumoutsakos
Harvard University, ETH Zurich / Harvard University