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Capability Assessment for Emergency Management of Fluorochemical Plant in Fires
Fluorochemical industry is one of the newly developed industries, from which products are widely used in daily life. However, many dangerous chemicals are involved in the production process of fluorochemical, which are prone to cause many accidents such as poisonous gas leaks, gas explosions, fires, human intoxication and so on, endangering people's lives and property. Therefore, it is really necessary to analyze and evaluate the emergency management capability of fluorochemical plant. In this paper, we establish a fault tree for the emergency management failure of fluorochemical plant in fires, and give the corresponding evaluation index system of emergency management capability. In addition, to evaluate the emergency management capability of fluorochemical plant, an artificial neural network based method is proposed to expand the technology of capability assessment for emergency management.
Capability Assessment for Emergency Management of Fluorochemical Plant in Fires
Fluorochemical industry is one of the newly developed industries, from which products are widely used in daily life. However, many dangerous chemicals are involved in the production process of fluorochemical, which are prone to cause many accidents such as poisonous gas leaks, gas explosions, fires, human intoxication and so on, endangering people's lives and property. Therefore, it is really necessary to analyze and evaluate the emergency management capability of fluorochemical plant. In this paper, we establish a fault tree for the emergency management failure of fluorochemical plant in fires, and give the corresponding evaluation index system of emergency management capability. In addition, to evaluate the emergency management capability of fluorochemical plant, an artificial neural network based method is proposed to expand the technology of capability assessment for emergency management.
Capability Assessment for Emergency Management of Fluorochemical Plant in Fires
Zhao, Xuedan (author) / Zhang, Jun (author) / Song, Weiguo (author) / Li, Hongliu (author) / Xia, Long (author)
2019-10-01
3510036 byte
Conference paper
Electronic Resource
English
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