Department Seminar of Zohar Aharony - Parametric Investigation and Optimization Process for Improved Performance of a Flow Control Actuator
SCHOOL OF MECHANICAL ENGINEERING SEMINAR
Monday. April 25, 2022 at 14:00
Parametric Investigation and Optimization Process for Improved Performance of a Flow Control Actuator
Zohar Aharony
M.Sc. student of Prof. Avraham “Avi” Seifert
Recent studies show that one of the main factors that influence aircraft efficiency and its fuel consumption is the development of boundary layer flow separation on its wings and body. The closer this separation occurs to the wing’s leading edge, the greater the aircraft’s fuel consumption becomes. Hence, new advanced and innovative methods (e.g., active flow control devices such as oscillators, suction slots, pulsed blowing actuators, and others) can provide added benefits beyond the capabilities of passive methods already used, such as flaps, slats, vortex generators, and more. These methods are necessary for saving energy by increasing aircraft efficiency.
One of the most efficient active flow control methods that has been studied to date is the fluidic oscillator, also called the ‘sweeping jet’. A fluidic oscillator is a device that emits a continuous, but rapidly changing, directional jet when connected to a fluid supply source, without the use of any moving part. The sweeping jet causes a turbulent flux, which can energize and therefore potentially delay the boundary layer separation. As a result, lift force is increased and drag force is reduced. In recent years, researchers have been interested in parametric studies of the fluidic oscillator’s internal geometry, but so far it does not appear that these parametric investigations have been used to identify a more efficient geometry of the device.
The purpose of the current study is to enhance the performance of a fluidic oscillator by an optimization process. Before this process, a parametric investigation based on CFD simulations was performed in order to understand how each geometric parameter influences the functionality of the device. These results enabled low influence geometrical parameters to be omitted from the optimization process. Next, a machine-learning algorithm processed a large database of mass-flow data through the device, as well as pressure supply versus velocity and spreading angle of the outlet jet. The database was generated by numerical simulations that in-turn were selectively verified by experiments. Finally, an improved design of a sweeping jet was created based on the findings of this study. The experiments verified a 15% increase of the outlet velocity, an 11% increase in the jet deflection angle while decreasing the required fluid supply by 15% to 20%.
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