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Experimental Study of Dynamical Airfoil and Aerodynamic Prediction
by
Qin, Chen
, Shi, Zheyu
, Wen, Xin
, Zhou, Kaiwen
in
Active control
/ Aerodynamics
/ Airfoil oscillations
/ Airfoils
/ Artificial intelligence
/ Composite materials
/ Delay
/ dynamic mode decomposition
/ Dynamic pressure
/ dynamical airfoil
/ Embedding
/ Experiments
/ Flow control
/ Machine learning
/ prediction
/ Pressure
/ Pressure distribution
/ Pressure-sensitive paints
/ R&D
/ Research & development
/ Reynolds number
/ Sensors
/ Stalling
/ time-delay embedding
/ Vortices
2022
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Experimental Study of Dynamical Airfoil and Aerodynamic Prediction
by
Qin, Chen
, Shi, Zheyu
, Wen, Xin
, Zhou, Kaiwen
in
Active control
/ Aerodynamics
/ Airfoil oscillations
/ Airfoils
/ Artificial intelligence
/ Composite materials
/ Delay
/ dynamic mode decomposition
/ Dynamic pressure
/ dynamical airfoil
/ Embedding
/ Experiments
/ Flow control
/ Machine learning
/ prediction
/ Pressure
/ Pressure distribution
/ Pressure-sensitive paints
/ R&D
/ Research & development
/ Reynolds number
/ Sensors
/ Stalling
/ time-delay embedding
/ Vortices
2022
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Do you wish to request the book?
Experimental Study of Dynamical Airfoil and Aerodynamic Prediction
by
Qin, Chen
, Shi, Zheyu
, Wen, Xin
, Zhou, Kaiwen
in
Active control
/ Aerodynamics
/ Airfoil oscillations
/ Airfoils
/ Artificial intelligence
/ Composite materials
/ Delay
/ dynamic mode decomposition
/ Dynamic pressure
/ dynamical airfoil
/ Embedding
/ Experiments
/ Flow control
/ Machine learning
/ prediction
/ Pressure
/ Pressure distribution
/ Pressure-sensitive paints
/ R&D
/ Research & development
/ Reynolds number
/ Sensors
/ Stalling
/ time-delay embedding
/ Vortices
2022
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Experimental Study of Dynamical Airfoil and Aerodynamic Prediction
Journal Article
Experimental Study of Dynamical Airfoil and Aerodynamic Prediction
2022
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Overview
Dynamic stall is a critical limiting factor for airfoil aerodynamics and a challenging problem for active flow control. In this experimental study, dynamic stall was measured by high-frequency surface pressure tapes and pressure-sensitive paint (PSP). The influence of the oscillation frequency was examined. Dynamic mode decomposition (DMD) with time-delay embedding was proposed to predict the pressure field on the oscillating airfoil based on scattered pressure measurements. DMD with time-delay embedding was able to reconstruct and predict the dynamic stall based on scattered measurements with much higher accuracy than standard DMD. The reconstruction accuracy of this method increased with the number of delay steps, but this also prolonged the computation time. In summary, using the Koopman operator obtained by DMD with time-delay embedding, the future dynamic pressure on an oscillating airfoil can be accurately predicted. This method provides powerful support for active flow control of dynamic stall.
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