Numerical Simulations of Flow Separation Control in Low-Pressure Turbines Using Plasma Actuators
Author(s) -
Yildirim Suzen,
George Huang,
David E. Ashpis
Publication year - 2007
Publication title -
45th aiaa aerospace sciences meeting and exhibit
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2007-937
Subject(s) - plasma actuator , separation (statistics) , flow control (data) , actuator , flow separation , plasma , flow (mathematics) , pressure control , control theory (sociology) , mechanics , materials science , control (management) , computer science , mechanical engineering , engineering , physics , electrical engineering , computer network , quantum mechanics , dielectric barrier discharge , artificial intelligence , boundary layer , machine learning
NASA John H. Glenn Research Center at Lewis Field, Cleveland, OH 44135 A recently introduced phenomenological model to simulate flow control applications using plasma actuators has been further developed and improved in order to expand its use to complicated actuator geometries. The new modeling approach eliminates the requirement of an empirical charge density distribution shape by using the embedded electrode as a source for the charge density. The resulting model is validated against a flat plate experiment with quiescent environment. The modeling approach incorporates the effect of the plasma actuators on the external flow into Navier Stokes computations as a body force vector which is obtained as a product of the net charge density and the electric field. The model solves the Maxwell equation to obtain the electric field due to the applied AC voltage at the electrodes and an additional equation for the charge density distribution representing the plasma density. The new modeling approach solves the charge density equation in the computational domain assuming the embedded electrode as a source therefore automatically generating a charge density distribution on the surface exposed to the flow similar to that observed in the experiments without explicitly specifying an empirical distribution. The model is validated against a flat plate experiment with quiescent environment.
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