3/28/2024 0 Comments Airfoil performance databaseSuppressing this vortex prevented the counterclockwise trailing edge vortex from growing at the end of the airfoil. The optimal jet suppressed the dynamic stall vortex, which resulted from the combination of two clockwise vortices: LEV and turbulent separation vortex. The average lift coefficient increases from about 0.58 to about 0.92 using this jet, while the average drag coefficient decreases from about 0.23 to about 0.02. The major part of this improvement is related to reducing drag force. The optimum jet can increase the average performance coefficient (average ratio of lift to drag during a period) by about 24 times. The optimal jet location was near the leading edge vortex (LEV) (between 3% and 6% of the chord). The optimal jet had the maximum velocity and opening length and was normal to the airfoil surface. The control parameters were location, velocity, opening length, and suction jet angle relative to the airfoil surface. The objective function was the mean performance coefficient, defined as the ratio of the average lift to the average drag during an oscillation period. Neural networks based on multilayer perceptrons were used to train the aerodynamic coefficients as functions of the control parameters and reduce the number of simulations. In this study, a genetic algorithm was employed to optimize the configuration of a pure suction jet actuator on an oscillating airfoil at a Reynolds number of 1.35 × 10 5. The SpalartAllmaras (SA) model was used to calculate the airfoil performance of FX63, and the polynomial fitting method was utilized to establish the airfoil database of the lift and drag coefficient. Flow separation control on oscillating airfoils is crucial for enhancing the efficiency of turbine blades. In this paper, a performance prediction method is proposed for the design of a stratospheric propeller.
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