Artificial neural networks in marine propeller design

Abstract

Various neural network systems were developed for examining propeller performance data that were derived experimentally. This study is aiming to establish an accurate mapping thus facilitating propeller selection during the design process. Different neural network architectures and learning rates were tested, aiming at establishing a near optimum setup. It is evident from the findings so far, that this technology can be used effectively in modeling the performance of a series of marine propellers and thus may be used for propeller selection, and for extrapolation to new designs.