Marine propellers design using particle swarm optimization with independent groups to improve efficiency and reduce cavitation

Due to the presence of too many parameters in the problem of the marine propeller design has been one of the challenging subjects for designers and researchers in this field. Nowadays, meta-heuristic algorithms are used to solve complex engineering problems. In this paper, for the first time, Independent Group Particle Swarm Optimization (IGPSO) algorithm is used to design the marine propellers. For this purpose, two targets viz. maximize the efficiency and minimize the cavitation as the fitness function are considered. To do this, during several trials, the effect of two important parameters on the fitness function, i.e. chord and thickness of the propeller, are calculated and the most optimal mode is selected by the IGPSO algorithm. In order to compare the results, the benchmark algorithms such as PSO and GA are used. The results show that the propeller with 5 or 6 blades with rotation speeds between 180 to 190 RPM will have the best performance in the tradeoff between efficiency and cavitation. The designed propeller by using IGPSO algorithm produced 86.64 dB and 106.79 dB noise for cavitation and non-cavitation mode, respectively. So, they produce 1.24 dB and 0.80 dB noise level lesser than other benchmark algorithms.