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The Application and Comparison of Two Different Optimization Algorithms in the Design of Propeller

Author: LiuYangHao
Tutor: HuangSheng
School: Harbin Engineering University
Course: Fluid Mechanics
Keywords: Propeller optimization design Panel method Lift-drag ratio of airfoil Geneticalgorithm Simulated annealing algorithm
CLC: U664.33
Type: Master's thesis
Year: 2012
Downloads: 121
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Abstract


The theory of propeller design method has already well developed, however, in manycircumstance, hydrodynamic performance of some propellers which already designed can notfits people’s needs, this requires further optimization design of the propeller. This paper iswrited in this background to put forward the optimal design of the propeller. The optimizationdesign of the propeller mainly includes two optimized objectives, efficiency and cavitationperformance. The mainly optimization goal of this paper is to improve the efficiency of thepropeller. This article combined the intelligent optimization algorithm and the propellerdesign theory to the optimization design of the propeller, and put the panel method theorydesign of propeller to a certain extent exploration.First of all, this article referenced many similar optimization algorithms, chose the morerepresentative two, selected genetic algorithm and simulated annealing algorithm as theoptimization algorithm in this paper. Verified the searching ability of algorithm andconvergence ability with a calculate example, it proved that the two algorithms both have theability of converge to the optimal solution and knew the effects of each arguments of thealgorithm, and lay the foundation for the follow work.Then, use the panel method to the model with lift force, and discussed the solving problemof the three dimensional airfoil flow, also discussed the airfoil theory design problems whichcombines the panel method. The process of the design on given pressure distribution and thedesign on given the lift coefficient and pressure distribution form were given.Then, the genetic algorithm and the simulated annealing algorithm were brought into thepanel method design of the airfoil theory design. The proceed optimization design aimed topromote the lift-to-drag ratio on multiple wing type, also on some blades of a propeller. It isproved that the genetic algorithm and simulated annealing algorithm can be rationaly andfeasibily used on the airfoil profile optimization in design. A comparison between the twokinds of optimization algorithm on the optimization results was made, besides, the efficiencyoptimization of the two algorithm are compared, also, the degree of optimization processvisibility were also compared in order to measure which optimization algorithm is moresuitable for application in this kind of optimal design. The paper then discusseed how theoptimization process factors effect the optimization results, and obtained some general rules. Finally, the result of airfoil profile optimization design which combined the optimizationalgorithm was brought to the optimal design of the propeller whose target is to improve theefficiency. The design took the4119propeller as a prototype, the efficiency of the propellersuccessfully improved, and it also proved that the genetic algorithm and simulated annealingalgorithm are rationaly and feasibily used in the optimization design of the propeller: For the4119propeller in the optimization design, take the case which speed coefficient is0.5as anexample, by combining the simulated annealing algorithm to optimize,the efficiency of thepropeller improved about4.33%; And by combining the genetic algorithm, the efficiency ofthe propeller improved about2.19%, the effect is obvious. During the process, many times ofcalculation helps make reasonable set of the constraints, and all the impacts of the constraintconditions were discussed. In addition, a comparison between the optimization result ofdifferent optimization algorithm was made, a conclusion that the result of simulated annealingalgorithm optimization was more ideal was get, at the same time, a comparison on efficiencybetween the two kinds of optimization algorithm was made, a conclusion that the efficiencyof simulated annealing algorithm optimize is higher than the genetic algorithm is acquired.

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CLC: > Transportation > Waterway transport > Marine Engineering > Ship machinery > Marine propulsion device > Propeller
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