Optimization design and experiment of centrifugal pump based on CFD
Zhao, Weiguo1,2; Sheng, Jianping1; Yang, Junhu1,2; Song, Qice1
2015-11-01
发表期刊Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
ISSN10026819
卷号31期号:21页码:125-131
摘要The centrifugal pump is one of the most widely used fluid machinery. However, 3 problems i.e. lower efficiency, unsteady flow and bad cavitations performance are perplexing the development of centrifugal pump. For a single centrifugal pump, the impeller is one of the most important flow components, so it is selected as the optimum objective. Parametric fitting is a prerequisite in impeller optimization design. This process provides optimization variables and controls impeller automatically for the optimization design. Bezier curve and B-spline curve are used to reconstruct the impeller to obtain the profile of the blade and the meridional surface. The stacking point is reference point which defines the position of the two-dimensional (2D) blade section on a stream surface. This point is first defined on the 2D blade section, and then positioned on the corresponding stream surface in the meridional and tangential directions. Trailing edge is selected as stacking curve. Bezier-line-Bezier curve can be used to fit tangential location. The optimization variables are the angle between linear segment and vertical direction and the angle between the second Bezier curve and vertical direction with the span of 1, which 2 variables control the tangential position of stacking line on the 2D blade section. The range of -3°-3° is chosen as the constraint condition of optimization variables. Recently, CFD (computational fluid dynamics) technology has been widely applied to numerical computation of the three-dimensional viscous flow inside turbomachinery, which has made much progress. Meanwhile, many excellent optimization algorithms have been proposed. Fortunately, the CFD technology isn't confined to the research of centrifugal pump inner flow. Combining the CFD technology and optimization algorithm will play a very important role in the increase of pump efficiency, the decrease of flow loss and the extension of high-performance areas. An automatic optimization design platform for the centrifugal impellers is constructed by the genetic algorithm combined with the parameterization method and the commercial computational fluid dynamics software NUMECA. Based on the genetic algorithm and the artificial neural network, a new optimization method for the optimization of a centrifugal impeller is presented. Different from the traditional optimization method, the performance of centrifugal impeller is predicted with the CFD technology in the new developed method. The relationship between objective function and optimization variables is established by the learning function of artificial neural network. The results show that the efficiency of impeller achieves the maximum, when the angle between linear segment and vertical direction is -2.886° and the angle between the second Bezier curve and vertical direction with the span of 1 is 1.31°. Compared with the original, the efficiency is improved by 4.02% for optimum impeller in the design point. The centrifugal pump efficiency is increased by 4.41%, and the head is increased by 2.63 m. Volute is one of important flow components and has a great effect on the single centrifugal pump. The loss in volute is very great with optimized impeller, or with original one, especially in the large flow area. The volute is redesigned and the numerical simulation of modified volute with optimum impeller is performed for the flow field analysis of the flow passage components. The efficiency is improved by 1.59% compared with the pump with optimum impeller and original volute in design point, and by 6% compared with the pump with original impeller and original volute in design point. The performance of centrifugal pump is optimized, and the purpose of energy saving is achieved. These findings confirm that the optimization design method is effective for the centrifugal impellers. ©, 2015, Chinese Society of Agricultural Engineering. All right reserved.
关键词Algorithms Centrifugal pumps Centrifugation Computational fluid dynamics Design Efficiency Energy conservation Genetic algorithms Impellers Interpolation Neural networks Optimization Parameter estimation Parameterization Automatic optimization CFD (computational fluid dynamics) Computational Fluid Dynamics software Numerical computations Optimization algorithms Optimization variables Parameterization method Three dimensional viscous flow
DOI10.11975/j.issn.1002-6819.2015.21.016
收录类别EI
语种中文
出版者Chinese Society of Agricultural Engineering
EI入藏号20154801612124
EI主题词Curve fitting
EI分类号525.2 Energy Conservation - 601.2 Machine Components - 618.2 Pumps - 723.5 Computer Applications - 802.3 Chemical Operations - 913.1 Production Engineering - 921 Mathematics - 961 Systems Science
来源库Compendex
分类代码525.2 Energy Conservation - 601.2 Machine Components - 618.2 Pumps - 723.5 Computer Applications - 802.3 Chemical Operations - 913.1 Production Engineering - 921 Mathematics
引用统计
文献类型期刊论文
条目标识符https://ir.lut.edu.cn/handle/2XXMBERH/113105
专题能源与动力工程学院
新能源学院
作者单位1.School of Energy and Power Engineering, Lanzhou University of Technology, Lanzhou; 730050, China;
2.Key Laboratory of Fluid Machinery and Systems, Lanzhou; Gansu Province; 730050, China
第一作者单位新能源学院
第一作者的第一单位新能源学院
推荐引用方式
GB/T 7714
Zhao, Weiguo,Sheng, Jianping,Yang, Junhu,et al. Optimization design and experiment of centrifugal pump based on CFD[J]. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering,2015,31(21):125-131.
APA Zhao, Weiguo,Sheng, Jianping,Yang, Junhu,&Song, Qice.(2015).Optimization design and experiment of centrifugal pump based on CFD.Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering,31(21),125-131.
MLA Zhao, Weiguo,et al."Optimization design and experiment of centrifugal pump based on CFD".Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering 31.21(2015):125-131.
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