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Effects of a Combination Impeller on the Flow Field and External Performance of an Aero-Fuel Centrifugal Pump

Author

Listed:
  • Jia Li

    (School of Construction Machinery, Chang’an University, Xi’an 710061, China)

  • Xin Wang

    (School of Construction Machinery, Chang’an University, Xi’an 710061, China)

  • Yue Wang

    (AECC Xi’an Power Control Technology Co. LTD., Xi’an 710077, China)

  • Wancheng Wang

    (AECC Xi’an Power Control Technology Co. LTD., Xi’an 710077, China)

  • Baibing Chen

    (Xi’an Modern Control Technology Research Institute, Xi’an 710065, China)

  • Xiaolong Chen

    (Xi’an Modern Control Technology Research Institute, Xi’an 710065, China)

Abstract

Aero-fuel centrifugal pumps are important power plants in aero-engines. Unlike most of the existing centrifugal pumps, a combination impeller is integrated with the pump to improve performance. First, the critical geometrical parameters of the combination impeller and volute are given. Then, the effects of the combination impeller on the flow characteristics of the impeller and volute are clarified by comparing simulation results with that of the conventional impeller, where the effectiveness of the selected numerical method is validated by an acceptable agreement between simulation and experiment. Finally, the experiment is set to test the external performance of the studied pump. A significant feature of this study is that the flow characteristics are significantly ameliorated by reducing the flow losses that emerged in the impeller inlet, impeller outlet, and volute tongue. Correspondingly, the head and efficiency of a combination impeller are higher with comparison to a conventional impeller. Consequently, it is a promising approach in ameliorating the flow field and improving external performance by applying a combination impeller to an aero-fuel centrifugal pump.

Suggested Citation

  • Jia Li & Xin Wang & Yue Wang & Wancheng Wang & Baibing Chen & Xiaolong Chen, 2020. "Effects of a Combination Impeller on the Flow Field and External Performance of an Aero-Fuel Centrifugal Pump," Energies, MDPI, vol. 13(4), pages 1-16, February.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:4:p:919-:d:322225
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    References listed on IDEAS

    as
    1. Wei Han & Lingbo Nan & Min Su & Yu Chen & Rennian Li & Xuejing Zhang, 2019. "Research on the Prediction Method of Centrifugal Pump Performance Based on a Double Hidden Layer BP Neural Network," Energies, MDPI, vol. 12(14), pages 1-14, July.
    2. Qifeng Jiang & Yaguang Heng & Xiaobing Liu & Weibin Zhang & Gérard Bois & Qiaorui Si, 2019. "A Review of Design Considerations of Centrifugal Pump Capability for Handling Inlet Gas-Liquid Two-Phase Flows," Energies, MDPI, vol. 12(6), pages 1-18, March.
    3. Yu Song & Honggang Fan & Wei Zhang & Zhifeng Xie, 2019. "Flow Characteristics in Volute of a Double-Suction Centrifugal Pump with Different Impeller Arrangements," Energies, MDPI, vol. 12(4), pages 1-15, February.
    4. Wang, Chuan & Shi, Weidong & Wang, Xikun & Jiang, Xiaoping & Yang, Yang & Li, Wei & Zhou, Ling, 2017. "Optimal design of multistage centrifugal pump based on the combined energy loss model and computational fluid dynamics," Applied Energy, Elsevier, vol. 187(C), pages 10-26.
    5. Xiangdong Han & Yong Kang & Deng Li & Weiguo Zhao, 2018. "Impeller Optimized Design of the Centrifugal Pump: A Numerical and Experimental Investigation," Energies, MDPI, vol. 11(6), pages 1-21, June.
    6. Zhang, Jianfei & Kong, Lingjian & Qu, Jingguo & Wang, Shuang & Qu, Zhiguo, 2019. "Numerical and experimental investigation on configuration optimization of the large-size ionic wind pump," Energy, Elsevier, vol. 171(C), pages 624-630.
    7. Arriaga, Mariano, 2010. "Pump as turbine – A pico-hydro alternative in Lao People's Democratic Republic," Renewable Energy, Elsevier, vol. 35(5), pages 1109-1115.
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