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Application of a Magnetic Field in Saturated Film Boiling of a Magnetic Nanofluid (MNF) under Reduced Gravity

Author

Listed:
  • Kaikai Guo

    (State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
    Facility Design & Instrumentation Institute, China Aerodynamics Research and Development Center, Mianyang 621000, China
    State Key Laboratory of Aerodynamics, China Aerodynamics Research and Development Center, Mianyang 621000, China)

  • Fucheng Chang

    (State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Huixiong Li

    (State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

To overcome the problem of abnormally large bubbles and the large reduction of heat flux under low gravity, the computational model of magnetic nanofluid (MNF) boiling flow was used to systematically study the thermodynamic characteristics of an MNF-saturated film boiling with and without the magnetic field. This study found that in the absence of a magnetic field, the decrease of the gravity level makes the bubble size increase and the bubble departure time increase, and the lower the gravity level, the worse the boiling heat transfer. However, after applying the magnetic field, bubble size decreases significantly and the bubble departure time is shortened. As the magnetic field intensity increases, the difference in bubble size and heat transfer characteristics between different gravity levels becomes smaller and smaller, which shows that for the boiling flow of MNF under low gravity levels, applying a magnetic field can effectively avoid the appearance of abnormally large bubbles, enhance heat transfer, and improve the safety of related heat transfer equipment.

Suggested Citation

  • Kaikai Guo & Fucheng Chang & Huixiong Li, 2021. "Application of a Magnetic Field in Saturated Film Boiling of a Magnetic Nanofluid (MNF) under Reduced Gravity," Energies, MDPI, vol. 14(3), pages 1-24, January.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:3:p:634-:d:487684
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    Cited by:

    1. Shi, Lei & Zhang, Shuai & Arshad, Adeel & Hu, Yanwei & He, Yurong & Yan, Yuying, 2021. "Thermo-physical properties prediction of carbon-based magnetic nanofluids based on an artificial neural network," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).

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