Drag Reduction of Turbulence Air Channel Flow with Distributed Micro Sensors and Actuators

Abstract

A prototype system for feedback control of wall turbulence is developed, and its performance is evaluated in a physical experiment. Arrayed micro hot-film sensors with a spanwise spacing of 1 mm are employed for the measurement of streamwise shear stress fluctuations, while arrayed magnetic actuators of 2.4 mm in spanwise width are used to introduce control input through wall deformation. A digital signal processor with a time delay of 0.1 ms is employed to drive the actuators based on the sensor signals. The driving voltage of each actuator is determined with a linear combination of the wall shear stress fluctuations at three sensors located upstream of the actuator, and a noise-tolerant genetic algorithm is employed to optimize the control parameters. Feedback control experiments are conducted in a fully-developed turbulent air channel flow at the Reynolds number of Reτ=300. It is found that about 6% drag reduction has been achieved in a physical experiment for the first time. Through turbulent statistics measurements with LDV, it is also found that the Reynolds shear stress close to the wall is decreased by the present control scheme. A conditional average of a DNS database is also made to extract coherent structures associated with the present control input. It is shown that the wall-deformation actuators induce a wall-normal velocity away from the wall when the high-speed region is located above the actuator.

Keywords

• turbulence control
• wall turbulence
• genetic algorithm
• optimal control
• microelectromechanical systems (mems)
• hot-film wall shear stress sensor
• magnetic actuator