Turbulent separated shear flow control by surface plasma actuator: experimental optimization by genetic algorithm approach

The potential benefits of active flow control are no more debated. Among many others applications, flow control provides an effective mean for manipulating turbulent separated flows. Here, a nonthermal surface plasma discharge (dielectric barrier discharge) is installed at the step corner of a backw...

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Vydané v:Experiments in fluids Ročník 57; číslo 2
Hlavní autori: Benard, N., Pons-Prats, J., Periaux, J., Bugeda, G., Braud, P., Bonnet, J. P., Moreau, E.
Médium: Journal Article Publikácia
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2016
Springer Verlag (Germany)
Predmet:
Engineering
Engineering Fluid Dynamics
Engineering Thermodynamics
Fluid- and Aerodynamics
Flux de fluids
Física
Física de fluids
Heat and Mass Transfer
Mathematical models
Models matemàtics
Particle Image Velocimetry Shear Layer Dielectric Barrier Discharge Vortex Pairing Plasma Actuator
Physics
Research Article
Turbulence
Turbulència
Àrees temàtiques de la UPC
Vortex Pairing
Plasma Actuator
Dielectric Barrier Discharge
Shear Layer
Particle Image Velocimetry
ISSN:0723-4864, 1432-1114
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Popis
Shrnutí:The potential benefits of active flow control are no more debated. Among many others applications, flow control provides an effective mean for manipulating turbulent separated flows. Here, a nonthermal surface plasma discharge (dielectric barrier discharge) is installed at the step corner of a backward-facing step ( U 0  = 15 m/s, Re h  = 30,000, Re θ  = 1650). Wall pressure sensors are used to estimate the reattaching location downstream of the step (objective function #1) and also to measure the wall pressure fluctuation coefficients (objective function #2). An autonomous multi-variable optimization by genetic algorithm is implemented in an experiment for optimizing simultaneously the voltage amplitude, the burst frequency and the duty cycle of the high-voltage signal producing the surface plasma discharge. The single-objective optimization problems concern alternatively the minimization of the objective function #1 and the maximization of the objective function #2. The present paper demonstrates that when coupled with the plasma actuator and the wall pressure sensors, the genetic algorithm can find the optimum forcing conditions in only a few generations. At the end of the iterative search process, the minimum reattaching position is achieved by forcing the flow at the shear layer mode where a large spreading rate is obtained by increasing the periodicity of the vortex street and by enhancing the vortex pairing process. The objective function #2 is maximized for an actuation at half the shear layer mode. In this specific forcing mode, time-resolved PIV shows that the vortex pairing is reduced and that the strong fluctuations of the wall pressure coefficients result from the periodic passages of flow structures whose size corresponds to the height of the step model.
ISSN:0723-4864
1432-1114
DOI:10.1007/s00348-015-2107-3