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

dc.contributor
Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
dc.contributor
Centre Internacional de Mètodes Numèrics en Enginyeria
dc.contributor
Universitat Politècnica de Catalunya. DECA - Grup de Recerca del Departament d'Enginyeria Civil i Ambiental
dc.contributor.author
Benard, N.
dc.contributor.author
Pons Prats, Jordi
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Periaux, Jacques Francis
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Bugeda Castelltort, Gabriel
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Braud, P.
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Bonnet, J.P.
dc.contributor.author
Moreau, E.
dc.date.issued
2016-02
dc.identifier
Benard, N., Pons, J., Périaux, J., Bugeda, G., Braud, P., Bonnet, J., Moreau, E. Turbulent separated shear flow control by surface plasma actuator: experimental optimization by genetic algorithm approach. "Experiments in fluids", Febrer 2016, vol. 57, núm. 2, p. 1-17.
dc.identifier
0723-4864
dc.identifier
https://www.researchgate.net/publication/291390203_Turbulent_separated_shear_flow_control_by_surface_plasma_actuator_experimental_optimization_by_genetic_algorithm_approach
dc.identifier
https://hdl.handle.net/2117/118969
dc.identifier
10.1007/s00348-015-2107-3
dc.description.abstract
The final publication is available at Springer via http://dx.doi.org/10.1007/s00348-015-2107-3
dc.description.abstract
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 (U0 = 15 m/s, Reh = 30,000, Re¿ = 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.
dc.description.abstract
Peer Reviewed
dc.description.abstract
Postprint (author's final draft)
dc.format
17 p.
dc.format
application/pdf
dc.language
eng
dc.relation
http://link.springer.com/article/10.1007%2Fs00348-015-2107-3
dc.rights
Open Access
dc.subject
Àrees temàtiques de la UPC::Física::Física de fluids::Flux de fluids
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Turbulence--Mathematical models
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Particle Image Velocimetry Shear Layer Dielectric Barrier Discharge Vortex Pairing Plasma Actuator
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Turbulència -- Models matemàtics
dc.title
Turbulent separated shear flow control by surface plasma actuator: experimental optimization by genetic algorithm approach
dc.type
Article


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