Abstract:

Flapping wings appear to be an innovative approach as an alternative to axial flow fans. In this study, the flapping motion has been defined as a linear combination of pitching and plunging. Both pitch and plunge motions have been given as sinusoidal in time with a phase shift between them. Various pitch amplitude and flapping frequency values have been studied at a fixed plunge amplitude. The flows over the flapping wings have been computed using an unsteady Reynolds-Averaged Navier-Stokes solver. The Spalart-Allmaras turbulence model has been employed to compute the eddy viscosity. All the flow computations have been done in a parallel computation environment. The support vector regression, which is a machine learning method, has been used to find the flapping conditions which match the axial fan performance as close as possible. Preliminary results show that flapping wings are promising compared to the performance of axial flow fans.