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Session: Classical and Machine learning methods in flow control III
Session starts: Tuesday 04 November, 14:50
Presentation starts: 14:50
Room: Lecture room B

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Ayano Watanabe ()
Naoki Takada ()
Satoshi Shimomura ()
Shuji Otomo ()
Akira Oyama ()
Hiroyuki Nishida ()

Abstract:
Flow separation over aerofoils causes stall, a loss of lift and an increase in drag, which is an unwanted phenomenon for many engineering devices. To suppress flow separation, feedback control is effective in responding to rapid changes in the flow field. Feedback control requires a highly responsive fluid control actuator, and plasma actuators (PA) have attracted much attention as such an actuator. In a previous study, a control strategy called burst-in-burst control was obtained by feedback control using PAs and deep reinforcement learning. Burst-in-burst control is the control method in which the PA is repeatedly turned on and off in a burst actuation to repeat separated and attached. This control method has obtained a higher control effect than the conventional fixed burst frequency control, but has not yet achieved continuous separation suppression. The aim of this study is to clarify the necessity for the duration when the PA drives off in burst-in-burst control, in order to obtain continuous separation suppression in high angle of attack separated flow. We conduct a predetermined control by varying the PA OFF duration to investigate its effect on the pressure time-history, and the pressure history of the fixed burst frequency case was measured and the average pressure distribution around the aerofoil was compared with between PA drive on and off.