Optimization design for axial pump based on genetic algorithm
TAO Ran1,2, XIAO Ruofu2*, YANG Wei2
1.College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China; 2.Beijing Engineering Research Center of Safety and Energy Saving Technology for Water Supply Network System, China Agricultural University, Beijing 100083, China
Abstract：Hydrodynamics design and optimization were conducted for an axial pump impeller.The optimization target was to improving the hydraulic performance of the axial pump by keeping the design requirements. During the optimization process, the blade angles were set as the optimization parameters. The genetic algorithm with binary coding was used as the optimization method. The hydraulic efficiency was defined as the optimization target function. The computational fluid dynamics(CFD)was used to solve the fitness function value. Verification results show that the hydrodynamic performances satisfied the requirements after optimization. The hydraulic efficiency is enhanced from 81.68% to 86.19%, the pump head also increases from 3.73 m to 4.56 m. Flow analysis shows that the head increased due to the higher-pressure difference between the suction and pressure sides of the impeller blades. Based on the hydraulic loss analysis, the efficiency increased because of the lower hydraulic losses in the pump. At the same time, the best efficiency point moved to the design condition with a wider high-efficiency region. This mathematical optimization for axial pump is fast and effective to improve the hydraulic performances based on the initial design.
陶然,, 肖若富*, 杨魏. 基于遗传算法的轴流泵优化设计[J]. 排灌机械工程学报, 2018, 36(7): 573-579.
TAO Ran,, XIAO Ruofu*, YANG Wei. Optimization design for axial pump based on genetic algorithm. Journal of Drainage and Irrigation Machinery Engin, 2018, 36(7): 573-579.
[1]PENG G, CAO S, ISHIZUKA M, et al. Design optimization of axial flow hydraulic turbine runner: part Ⅰ—an improved Q3D inverse method[J]. International journal for numerical methods in fluids, 2002, 39(6): 517-531.[2]PENG G, CAO S, ISHIZUKA M, et al. Design optimization of axial flow hydraulic turbine runner: part Ⅱ—multi-objective constrained optimization method[J]. International journal for numerical methods in fluids, 2002, 39(6): 533-548.[3]汤方平,石丽建,雷翠翠,等. 轴流泵叶片多学科设计优化[J].农业机械学报,2014,45(9):96-100. TANG Fangping, SHI Lijian, LEI Cuicui, et al. Multidisciplinary design optimization of axil-flow pump blades[J]. Transactions of the CSAM, 2014, 45(9): 96-100.(in Chinese)[4]YAN P, CHEN T, WU D Z, et al. Multi-point optimization on the diffuser of an axial flow pump[C]//Proceedings of the IOP Conference Series: Materials Scie-nce and Engineering. [S.l.]: IOP Publishing, 2013, 52(2): 022011.[5]LI W G. NPSHR optimization of axial-flow pumps[J]. Journal of fluids engineering, 2008, 130(7): 074504.[6]LIU G L. Optimization of axial-flow pump cascade solidi-ty subject to cavitation and separation-free constraints[J]. International journal of turbo and jet engines, 1995, 12: 231-236.[7]ZHU L, ZHANG X, YAO Z. Shape optimization of the diffuser blade of an axial blood pump by computational fluid dynamics[J]. Artificial organs, 2010, 34(3): 185-192.[8]WU H, GONG G, WANG Z, et al. Structural design and numerical simulation of the diffuser for maglev axial blood pump[J]. Journal of mechanics in medicine and biology, 2014, 14(3):[9]DERAKHSHAN S, POURMAHDAVI M, ABDOLAHNEJAD E, et al. Numerical shape optimization of a centrifugal pump impeller using artificial bee colony algorithm[J]. Computers & fluids, 2013, 81: 145-151.[10]肖若富,陶然,王维维,等. 混流泵叶轮反问题设计与水力性能优化[J]. 农业机械学报,2014,45(9):84-88. XIAO Ruofu, TAO Ran, WANG Weiwei, et al. Inverse design and hydraulic optimization of mixed-flow pump impeller[J]. Transactions of the CSAM, 2014, 45(9): 84-88.(in Chinese)[11]FUGLSANG P, MADSEN H A. Optimization method for wind turbine rotors[J]. Journal of wind engineering and industrial aerodynamics, 1999, 80(1): 191-206.[12]KIM J H, CHOI J H, HUSAIN A, et al. Multi-objective optimization of a centrifugal compressor impeller through evolutionary algorithms[J]. Journal of power and energy, 2010, 224(5): 711-721.[13]GÜLICH J F. Centrifugal pumps[M]. Berlin: Sprin-ger, 2008.[14]SMITH A E, TATE D M. Genetic optimization using a penalty function[C]//Proceedings of the 5th International Conference on Genetic Algorithms. [S.l.]: Morgan Kaufmann Publishers Inc., 1993: 499-505.[15]ANDERSON J D. Computational fluid dynamics [M]. New York: McGraw-Hill, 1995.[16]MENTER F R. Two-equation eddy-viscosity turbulence models for engineering applications[J]. AIAA journal, 1994, 32(8): 1598-1605.[17]GOLDBERG D E. Genetic algorithms in search, optimization, and machine learning[M]. Reading Menlo Park: Addison-wesley, 1989.[18]TAO R, XIAO R, YANG W, et al. Investigation of the hydrodynamics of sweep blade in high-speed axial fuel pump impeller[J]. Advances in mechanical ngineering, 2013, 174017.
