Machine learning assisted propeller design

Propellers are one of the most widely used propulsive devices for generating thrust from rotational engine motion both in marine vehicles and subsonic air-crafts. Due to their simplicity, robustness and high efficiency, propellers remained the mainstream design choice over the last hundred years. On the other hand, finding the optimal application-specific geometry is still challenging. This work in progress report describes application of modern and rapidly developing Machine Learning (ML) techniques to gain novel designs. We rely on a rich set of preexisting parametric design patterns and accumulated engineering knowledge supplemented by high-fidelity simulation models to formulate the design process as a supervised learning problem.