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 (10): 1384-1389.

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Application of machine learning in prediction of coal dust explosion sensitivity

Lei Youxue   

  1. (Shaanxi Fire and Rescue Brigade, Shaanxi Xi'an 710016, China)
  • Online:2022-10-15 Published:2022-10-15

Abstract: Abstract: This article presented a full-scale UHVDC converter transformer fire model, which was developed on account of the characteristics of special fire accidents such as high-temperature oils and explosion shock of converter transformers, and the performance of the compressed air foam spraying system in firefighting was validated by carrying out the spill fire test. Due to the absence of fire branch pipes and sprinklers, the compressed air foam sprinkler system will not fail in blast shock. Under the application rate of 12.4 L/(min·m2), the fire was controlled at 28 s and extinguished at 181 s. During the fire test, re-ignition occurred first on the top fuel tank due to the higher temperature of the fuel in the top fuel tank. In addition, the fire plume tended to the direction of the valve hall firewall, and the "fireproof foam curtain" had the effect of thermal radiation protection, resulting in higher temperature of the valve hall firewall.

Key words: Key words: compressed air foam, fire extinguishing system, UHVDC converter transformer, high-temperature oils, spill fire