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dc.contributor.authorBenard, N.
dc.contributor.authorPons Prats, Jordi
dc.contributor.authorPeriaux, Jacques Francis
dc.contributor.authorBugeda Castelltort, Gabriel
dc.contributor.authorBonnet, J.P.
dc.contributor.authorMoreau, E.
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Resistència de Materials i Estructures a l'Enginyeria
dc.date.accessioned2015-10-01T12:46:26Z
dc.date.available2015-10-01T12:46:26Z
dc.date.issued2015
dc.identifier.citationBenard, N., Pons, J., Périaux, J., Bugeda, G., Bonnet, J., Moreau, E. Multi-input genetic algorithm for experimental optimization of the reattachment downstream of a backward-facing step with surface plasma actuator. A: 46th AIAA Plasmadynamics and Lasers Conference. "46th AIAA Plasmadynamics and Lasers Conference". Dallas: American Institute of Aeronautics and Astronautics (AIAA), 2015, p. 1-23.
dc.identifier.urihttp://hdl.handle.net/2117/77252
dc.description.abstractThe practical interest of flow control approaches is no more debated as flow control provides an effective mean for considerably increasing the performances of ground or air transport systems, among many others applications. Here a fundamental configuration is investigated by using non-thermal surface plasma discharge. A dielectric barrier discharge is installed at the step corner of a backward-facing step (Reh=30000, Re¿=1650). Wall pressure sensors are used to estimate the reattaching location downstream of the step. The primary objective of this paper is the coupling of a numerical optimizer with an experiment. More specifically, optimization by genetic algorithm is implemented experimentally in order to minimize the reattachment point downstream of the step model. Validation through inverse problem is firstly demonstrated. When coupled with the plasma actuator and the wall pressure sensors, the genetic algorithm finds the optimum forcing conditions with a good convergence rate, the best control design variables being in agreement with the literature that uses other types of control devices than plasma. Indeed, 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 phenomena. At the best forcing conditions, the mean flow reattachment is reduced by 20%. This article, with its experiment-based approach, demonstrates the robustness of a single-objective multi-design optimization method, and its feasibility for wind tunnel experiments.
dc.format.extent23 p.
dc.language.isoeng
dc.publisherAmerican Institute of Aeronautics and Astronautics (AIAA)
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes numèrics
dc.subject.lcshNumerical analysis
dc.titleMulti-input genetic algorithm for experimental optimization of the reattachment downstream of a backward-facing step with surface plasma actuator
dc.typeConference report
dc.subject.lemacAnàlisi numèrica
dc.contributor.groupUniversitat Politècnica de Catalunya. RMEE - Grup de Resistència de Materials i Estructures en l'Enginyeria
dc.relation.publisherversionhttps://www.aiaa.org/EventDetail.aspx?id=21016
dc.rights.accessOpen Access
local.identifier.drac16653118
dc.description.versionPostprint (published version)
local.citation.authorBenard, N.; Pons, J.; Périaux, J.; Bugeda, G.; Bonnet, J.; Moreau, E.
local.citation.contributor46th AIAA Plasmadynamics and Lasers Conference
local.citation.pubplaceDallas
local.citation.publicationName46th AIAA Plasmadynamics and Lasers Conference
local.citation.startingPage1
local.citation.endingPage23


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