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| Multi-object optimum design for hydraulic turbine guide vane based on NSGA-Ⅱ algorithm |
| Luo Xingqi， Guo Pengcheng， Zhu Guojun， Ding Kuang |
| （School of Hydropower Engineering, Xi′an University of Technology, Xi′an, Shaanxi 710048, China） |
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Abstract The multi-object optimization method for hydraulic machinery blades was proposed based on NSGA-Ⅱ algorithm. In the method, shape parameters of the blades were used as optimization variables, energy and cavitation performances were used as objective functions, and the multi-object optimization for the guide vane blade surface in a water power plant was carried out. The obtained results showed that the total pressure loss reduced by 26.97%, and the minimal pressure in guide vane increased by 34.176%. For the optimized guide vanes, the loss was reduced, and the cavitation performance was improved. It is concluded that the multi-object optimization method presented can control the blade profiles by using fewer variables and is available for both effectively analyzing the influence of every design variable on objective function and reducing the scale of the optimization question. So it is a valid optimization design tool for hydraulic machinery blades.
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Received: 10 November 2009
Published: 30 September 2010
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| [1]Queipo N V,Haftka R T,Shyy W,et al.Surrogate-based analysis and optimization[J].Progress in Aerospace Sciences,2005,41(1):1-28.[2]卢金铃,席光,祁大同.反问题与神经网络相结合的混流泵叶片优化设计[J].西安交通大学学报,2004,38(3):308-312.Lu Jinling,Xi Guang,Qi Datong.Blade optimization of mixed-flow pump using inverse design method and neural network[J].Journal of Xi′an Jiaotong University,2004,38(3):308-312.(in Chinese)[3]Gehrer A,Schmidl R,Sadnik D.Kaplan turbine runner optimization by numerical flow simulation (CFD) and an evolutionary algorithm[C]//Proceedings of the 23rd IAHR Symposium on Hydraulic Machinery and Systems.Yokohama,Japan:[s.n.],2006.[4]Kazuyuki N,Takanori N,Kaneo S.Design optimization of a low specific speed Francis turbine runner[C]//Proceedings of the 24th IAHR Symposium on Hydraulic Machinery and Systems.Fozdoiguassu,Brazil:[s.n.],2008:27-31.[5]Schilling R,Thum S,Muller N,et al.Design optimization of hydraulic machinery bladings by multilevel CFD-technique[C]//Proceeding of the 21st IAHR Symposium on Hydraulic Machinery and Systems.Lausanne,Switzerland:[s.n.],2002.[6]Tomas L,Pedretti C,Chiappa T,et al.Automatted design of a francis turbine runner using global optimization algorithms[C]//Proceeding of the 21st IAHR Symposium on Hydraulic Machinery and Systems.Lausanne,Switzerland:[s.n.],2002.[7]Ferrando L,Kueny J L,Avellan F,et al.Surface parameterization of a Francis runner turbine for optimum design[C]//Proceeding of 22nd IAHR Symposium on Hydraulic Machinery and Systems.Stockholm,Sweden:[s.n.],2004.[8]Enomoto Y,Kurosawa S,Suzuki T.Design optimization of a Francis turbine runner using multi-objective genetic algorithm[C]//Proceeding of 22nd IAHR Symposium on Hydraulic Machinery and Systems.Stockholm,Sweden:[s.n.],2004.[9]肖若富,王正伟.基于组合优化策略的离心泵优化设计[J].清华大学学报:自然科学版,2006,46(5):700-703.Xiao Ruofu,Wang Zhengwei.Centrifugal pump blade optimization based on a combined optimization strategy[J].Journal of Tsinghua University:Science and Technology,2006,46(5):700-703.(in Chinese)[10]王小翠,侯志敏,张新运.基于进化算法和CFD技术的离心泵低稠度导叶的优化设计[J].流体机械,2007,35(3):21-24.Wang Xiaocui,Hou Zhimin,Zhang Xinyun.Optimization design of the low solidity vane for the centrifugal pump using evolutionary algorithms and CFD technique[J].Fluid Machinery,2007,35(3):21-24.(in Chinese) |
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