Low-Reynolds Number Adaptive Flow Control Using Dielectric Barrier Discharge Actuator.

Low-Reynolds Number Aerodynamics;Dielectric Barrier Discharge Actuator;Adaptive Feedback Flow Control;Markov Parameter-based System Identification;Surrogate Modeling;Free-stream Disturbance Rejection;Aerospace Engineering;Engineering;Aerospace Engineering

Cho, Young-ChangSchultz, William W. ;

University of Michigan

关键词: Low-Reynolds Number Aerodynamics;    Dielectric Barrier Discharge Actuator;    Adaptive Feedback Flow Control;    Markov Parameter-based System Identification;    Surrogate Modeling;    Free-stream Disturbance Rejection;    Aerospace Engineering;    Engineering;    Aerospace Engineering;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/78845/yccho_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Active flow control offers insight into fluid physics as well as possible improvements in flight performance for low-Reynolds number flyers – those at the chord-based Reynolds number of 105 or below – whose aerodynamic performance is sensitive to wind gusts, flow separation, and laminar-turbulent transition. Recently, the dielectric barrier discharge (DBD) actuator, characterized by a fast response without moving parts, has emerged as a promising flow control device. Although numerous studies have explored DBD physics and flow generation mechanisms, there is a limited understanding of the performance of the DBD actuator and surrounding flows under different operating and material parameters. Moreover, the disparity of time- and spatial-scales in plasma-dynamics makes direct numerical simulation of the DBD actuator impractical for real-time flow control. In this study aimed at flow control, surrogate modeling techniques are adopted to characterize the impact of the dielectric constant, and the voltage frequency and waveform on the force generation and power requirements of the DBD actuator. Global sensitivity and Pareto front analyses identify parametric dependencies and distinctive regions of interest in the design space. The feedback control is devised by combining surrogate modeling, system estimation and a penalty-based adaptive law. The control algorithm (minimizing a quadratic function of the retrospective performance) requires knowledge of the first nonzero Markov parameter and nonminimum-phase zeros of the linearized flow-actuator model, which are easy to identify. The estimates of these system parameters are analyzed under various flow and actuation conditions using impulse and step response tests. For finite and infinite wings with the SD7003 airfoil geometry with chord-based Reynolds numbers between 300 and 1000, and a 15-degree angle-of-attack, the present control law can stabilize lift under modest free-stream fluctuations. The interaction between control and flow responses indicates that the adjusted pressure and suction regions around the DBD actuator can stabilize lift. Furthermore, by minimizing the lift fluctuation, the drag fluctuation can either increase or decrease depending on flow conditions. The limitations of the linear modeling approach are addressed based on the system’s nonlinear behavior. The present modeling, estimation and control framework offers a new approach for control of low-Reynolds number aerodynamics.