Abstract

Use of active flow control techniques has become important in flow separation control. Continuous blowing jet is one of the most effective methods that can be used to improve aerodynamic performance of an airfoil. In the present work, different operational parameters of a continuous blowing jet were optimized to improve the aerodynamic performance of an oscillating NACA0012 airfoil. The airfoil underwent a sinusoidal motion about its quarter-chord between −5 and 25 degrees at the Reynolds number of 1.35 × 105. Unsteady Navier-Stokes equations were solved with k-ω SST turbulence model. Due to the time-consuming nature of large number of numerical simulations required during the optimization process, two neural networks were employed to reduce the number of simulations required. The optimization was carried out with the use of a genetic algorithm. The objective function was defined as the lift-to-drag ratio. In these networks, the relationship between the jet operational characteristics and the aerodynamic coefficients were trained. The jet operational parameters that were considered in this study, included jet location (at 1–60 percent of chord length), jet-opening length (0.05 to 0.3 percent of chord length), blowing jet velocity magnitude (0 to 5U), and blowing jet incident angle (0 to 180 degrees). Obtained results indicated that jet-opening length and blowing velocity magnitude have a greater effect on the aerodynamic performance when reached their upper values. Concerning the jet location, it was observed that the best jet location was about 2 to 5 percent of the chord Jet angle (θ) was found to results in the best performance when oriented at range 55 to 70 angle. Results indicated a significant improvement of the aerodynamic performance at the optimum blowing jet configuration.

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