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Artificial Intelligence Control of Turbulence

Abstract : An artificial intelligence (AI) control system is developed to manipulate a turbulent jet targeting maximal mixing. The control system consists of sensors (two hot-wires), genetic programming for evolving the control law and actuators (6 unsteady radial minijets). The mixing performance is quantified by the jet centerline mean velocity. AI control discovers a hitherto unexplored combination of asymmetric flapping and helical forcing. Such a combination of several actuation mechanisms constitutes a large challenge for conventional methods of parametric optimization. AI control vastly outperforms the optimized periodic axisymmetric, helical or flapping forcing produced from conventional open-or closed-loop control. Intriguingly, the learning process of AI control discovers all these forcings in the order of increased performance. Our study is the first AI control experiment which discovers a non-trivial spatially distributed actuation optimizing a turbulent flow. The results show the great potential of AI in conquering the vast opportunity space of control laws for many actuators, many sensors and broadband turbulence.
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Contributor : Bernd Noack <>
Submitted on : Saturday, December 7, 2019 - 9:11:33 PM
Last modification on : Wednesday, October 14, 2020 - 3:57:12 AM


  • HAL Id : hal-02398697, version 1



Dewei Fan, Yu Zhou, Bernd Noack. Artificial Intelligence Control of Turbulence. 5th Symposium on Fluid Structure-Sound Interactions and Control (FSSIC), Aug 2019, Minoa Palace - Resort, Chania, Crete island, Greece. pp.1-4. ⟨hal-02398697⟩



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