Method to Improve Propeller Performance Using Real-coded Genetic Algorithm

概要

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This paper presents a numerical optimization method to improve propeller performance using real-coded genetic algorithm. In the method presented, UNDX (Unimodal Normal Distribution Crossover) and MGG (Minimal Generation Gap) models are used as crossover operator and generation-alternation models, respectively. Propeller performance is evaluated by a simple surface panel method "SQCM" in the optimization process. The blade section of the original propeller is replaced by the NACA66 a=0.8 section. However, original chord, skew, rake and maximum blade thickness distributions in the radial direction are unchanged. Pitch and maximum camber distributions in the radial direction and the position of maximum camber in the chord wise direction are selected as the design variables. Optimization is conducted to maximize the propeller efficiency while keeping the target thrust coefficient constant. Cavitation performance is also considered as a constraint condition. Propellers for a product tanker and a cargo ship were improved by utilizing the present method. Propeller open tests and cavitation tests of the original and improved propellers were carried out. It was confirmed that both improved propellers had higher efficiencies compared to those of the original propellers. It was also found that both cavitation performances of the improved propellers are permissible.
公益社団法人日本マリンエンジニアリング学会の論文