Assessment of Oscillating Wings to Deliver Air Mass Flow Under Power and Thrust Constraints

An oscillating wing was evaluated for its ability to deliver air mass flow. The evaluation was based on exploring the oscillation parameters that provide a given mass flow rate at the least power requirement with the highest possible thrust generation. Wing oscillation was defined as coupled pitch and plunge motions. The support vector regression algorithm was implemented as a machine learning tool to link the oscillation parameters to power and thrust values. The required power and generated thrust values were computed by solving the unsteady turbulent flows around the wings. The results were also compared to the performance of an axial flow fan that delivered the same amount of air mass flow. It was found that an oscillating wing is compatible with an axial fan in terms of power requirement and thrust generation.