主管:中华人民共和国应急管理部
主办:应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU

Fire Science and Technology ›› 2022, Vol. 41 ›› Issue (5): 581-586.

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Aerodynamic performance optimization of axial flow fan based on deep learning and CFD

XU Ting-ting1, ZHU Guo-qing1, CHEN Fan-bao1, SUN Chuan-yue2   

  1. (1. School of Safety Engineering, China University of Mining and Technology, Jiangsu Xuzhou 221116, China; 2. School of Foreign Studies, China University of Mining and Technology, Jiangsu Xuzhou 221116, China)
  • Online:2022-05-15 Published:2022-05-15

Abstract: Abstract: As common by used fire-fighting equipment for forest fire fighting, wind-driven fire extinguisher often has some problems, such as low outlet wind speed, short jet distance and so on, due to the use of the centrifugal fan. The axial-flow fan can overcome the difficulties of centrifugal fan to a certain extent. In this paper, the axial flow fan is used. It is found that the appropriate change of blade root angle and blade top angle is helpful to improve the outlet wind speed and jet distance of the fan. After the fan is optimized by deep learning, when the blade root angle is 38.9° and the blade top angle is 35.7°, the outlet wind speed and jet distance are increased by 4.65% and 15.6%, respectively. It can improve the basis for the research and development of axial-flow wind fire extinguisher.

Key words: Key words: axial flow fan, deep learning, blade installation angle, pneumatic fire extinguisher