IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i4p607-d1341002.html

Optimization of Magnetic Pump Impeller Based on Blade Load Curve and Internal Flow Study

Author

Listed:
  • Ruijie Zhang

    (Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China)

  • Jiaqiong Wang

    (Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China
    Wenling Fluid Machinery Technology Institute, Jiangsu University, Zhenjiang 212013, China)

  • Wenfei Qian

    (Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China)

  • Linlin Geng

    (Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China)

Abstract

Compared to traditional centrifugal pumps, magnetic pumps are widely used in industries such as chemical, pharmaceutical, and petroleum due to their characteristics of leakage-free operation and the ability to transport toxic and corrosive fluids. However, the efficiency of magnetic pumps is relatively low. Improving the efficiency of pumps helps to reduce energy loss and lower industrial costs. In this study, a magnetic pump was chosen as the research subject. The study aims to improve the efficiency and stability of the magnetic pump by optimizing the impeller blades based on the load curve. A combined approach of a numerical simulation and experimental verification was used to investigate the impact of the anterior loading point (AL), posterior loading point (PL), and slope (SL) in the blade loading curve on the pump’s performance. The slope, which had the most significant impact on pump performance, was selected as the dependent variable to analyze the internal pressure pulsation and main shaft radial force of the magnetic pump. The research found that the hydraulic performance test results of the magnetic pump were in good agreement with the simulation results. When efficiency is used as the optimization objective, the anterior loading point should be moved as far back as possible, and the posterior loading point should be moved as far forward as possible. Through the study of internal pressure fluctuations and radial forces within the pump, the radial force distribution is sequentially as follows: the anterior loading method, posterior loading method, and middle loading method at a rated flow rate. The maximum pressure pulsation amplitude was near the volute casing diffuser area. Compared to the original pump, the optimized magnetic pump showed a 5.05% improvement in hydraulic efficiency under the rated conditions. This research contributes to enhancing the performance and efficiency of magnetic pumps, making them more suitable for various industrial applications.

Suggested Citation

  • Ruijie Zhang & Jiaqiong Wang & Wenfei Qian & Linlin Geng, 2024. "Optimization of Magnetic Pump Impeller Based on Blade Load Curve and Internal Flow Study," Mathematics, MDPI, vol. 12(4), pages 1-17, February.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:4:p:607-:d:1341002
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/4/607/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/4/607/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Renhui Zhang & Xutao Zhao, 2020. "Inverse Method of Centrifugal Pump Blade Based on Gaussian Process Regression," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-10, February.
    2. Zhu, Baoshan & Wang, Xuhe & Tan, Lei & Zhou, Dongyue & Zhao, Yue & Cao, Shuliang, 2015. "Optimization design of a reversible pump–turbine runner with high efficiency and stability," Renewable Energy, Elsevier, vol. 81(C), pages 366-376.
    3. Zhang, Ning & Jiang, Junxian & Gao, Bo & Liu, Xiaokai, 2020. "DDES analysis of unsteady flow evolution and pressure pulsation at off-design condition of a centrifugal pump," Renewable Energy, Elsevier, vol. 153(C), pages 193-204.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wei Yang & Benqing Liu & Ruofu Xiao, 2019. "Three-Dimensional Inverse Design Method for Hydraulic Machinery," Energies, MDPI, vol. 12(17), pages 1-19, August.
    2. Wang, Kaijie & Wang, Shuli & Meng, Puyu & Wang, Chengpeng & Li, Yuhai & Zheng, Wenxian & Liu, Jun & Kou, Jiawen, 2023. "Strategies employed in the design and optimization of pump as turbine runner," Renewable Energy, Elsevier, vol. 216(C).
    3. Hu, Zanao & Cheng, Yongguang & Zhang, Pengcheng & Li, Wenxin & Zhang, Jian & Ma, Yanmei & Hu, Zhaohua & Li, Gui fen, 2025. "Runner modification optimization design method for pump-turbine runner considering hydraulic transient guarantee parameter constraints," Energy, Elsevier, vol. 340(C).
    4. Dehghan, Amir Arsalan & Shojaeefard, Mohammad Hassan & Roshanaei, Maryam, 2024. "Exploring a new criterion to determine the onset of cavitation in centrifugal pumps from energy-saving standpoint; experimental and numerical investigation," Energy, Elsevier, vol. 293(C).
    5. Chen, Sheng & Wang, Jing & Zhang, Jian & Yu, Xiaodong & He, Wei, 2020. "Transient behavior of two-stage load rejection for multiple units system in pumped storage plants," Renewable Energy, Elsevier, vol. 160(C), pages 1012-1022.
    6. Han, Shuangqian & Qin, Yonglin & Zhu, Baoshan, 2025. "Multi-objective optimization design of a pump-turbine runner based on machine learning method," Energy, Elsevier, vol. 336(C).
    7. Qin, Yonglin & Li, Deyou & Wang, Hongjie & Liu, Zhansheng & Wei, Xianzhu & Wang, Xiaohang, 2022. "Multi-objective optimization design on high pressure side of a pump-turbine runner with high efficiency," Renewable Energy, Elsevier, vol. 190(C), pages 103-120.
    8. Xiaobo Zheng & Yaping Zhao & Huan Zhang & Yongjian Pu & Zhihua Li & Pengcheng Guo, 2022. "Optimization and Performance Analysis of Francis Turbine Runner Based on Super-Transfer Approximate Method under Multi-Energy Complementary Conditions," Sustainability, MDPI, vol. 14(16), pages 1-16, August.
    9. Cao, Puyu & Zhu, Rui & Yin, Gang, 2021. "Spike-type disturbances due to inlet distortion in a centrifugal pump," Renewable Energy, Elsevier, vol. 165(P1), pages 288-300.
    10. Chengshuo Wu & Jun Yang & Shuai Yang & Peng Wu & Bin Huang & Dazhuan Wu, 2023. "A Review of Fluid-Induced Excitations in Centrifugal Pumps," Mathematics, MDPI, vol. 11(4), pages 1-20, February.
    11. Ma, Zhe & Zhu, Baoshan, 2020. "Pressure fluctuations in vaneless space of pump-turbines with large blade lean runners in the S- shaped region," Renewable Energy, Elsevier, vol. 153(C), pages 1283-1295.
    12. Linhai Liu & Baoshan Zhu & Li Bai & Xiaobing Liu & Yue Zhao, 2017. "Parametric Design of an Ultrahigh-Head Pump-Turbine Runner Based on Multiobjective Optimization," Energies, MDPI, vol. 10(8), pages 1-16, August.
    13. Pei, Ji & Shen, Jiawei & Wang, Wenjie & Yuan, Shouqi & Zhao, Jiantao, 2024. "Evaluating hydraulic dissipation in a reversible mixed-flow pump for micro-pumped hydro storage based on entropy production theory," Renewable Energy, Elsevier, vol. 225(C).
    14. Zhenhua Zhou & Huacong Li & Jinbo Chen & Delin Li & Ning Zhang, 2023. "Numerical Simulation on Transient Pressure Pulsations and Complex Flow Structures of a Ultra-High-Speed Centrifugal Pump at Stalled Condition," Energies, MDPI, vol. 16(11), pages 1-17, June.
    15. Ni, Dan & Zhang, Ning & Gao, Bo & Li, Zhong & Yang, Minguan, 2020. "Dynamic measurements on unsteady pressure pulsations and flow distributions in a nuclear reactor coolant pump," Energy, Elsevier, vol. 198(C).
    16. Hao Yu & Chuan Wang & Guohui Li & Hongliang Wang & Yang Yang & Shaohui Wu & Weidong Cao & Shanshan Li, 2023. "Steady and Unsteady Flow Characteristics inside Short Jet Self-Priming Pump," Sustainability, MDPI, vol. 15(18), pages 1-23, September.
    17. Zhang, Han & Gao, Xueping & Sun, Bowen & Qin, Zixue & Zhu, Hongtao, 2020. "Parameter analysis and performance optimization for the vertical pipe intake-outlet of a pumped hydro energy storage station," Renewable Energy, Elsevier, vol. 162(C), pages 1499-1518.
    18. Li, Deyou & Qin, Yonglin & Wang, Jianpeng & Zhu, Yutong & Wang, Hongjie & Wei, Xianzhu, 2022. "Optimization of blade high-pressure edge to reduce pressure fluctuations in pump-turbine hump region," Renewable Energy, Elsevier, vol. 181(C), pages 24-38.
    19. Wang, Mengcheng & Ni, Xiang & Chen, Jiaqi & Li, Xinyu & Meng, Fan & Yang, Yang & Gu, Yandong, 2025. "Energy performance improvement of mixed flow pump based on coupling of geometric and hydrodynamic parameters," Energy, Elsevier, vol. 332(C).
    20. Diamantis Karakatsanis & Nicolaos Theodossiou, 2022. "Smart Hydropower Water Distribution Networks, Use of Artificial Intelligence Methods and Metaheuristic Algorithms to Generate Energy from Existing Water Supply Networks," Energies, MDPI, vol. 15(14), pages 1-21, July.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:4:p:607-:d:1341002. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.