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

消防科学与技术 ›› 2023, Vol. 42 ›› Issue (7): 1004-1009.

• • 上一篇    下一篇

基于成本风险理论的石油化工火灾救援对策推演

胡人元1, 夏登友2   

  1. (1. 重庆市万州区消防救援支队,重庆 404000;2. 中国人民警察大学 救援指挥学院,河北 廊坊 065000)
  • 出版日期:2023-07-15 发布日期:2023-07-15
  • 作者简介:胡人元(1994- ),男,四川仪陇人,万州区消防救援支队三级指挥员,硕士,主要从事于化工事故处置方面的研究,重庆市万州区江南消防救援站,404000。
  • 基金资助:
    基金项目:国家自然科学基金项目(52174224)

Derivation of rescue strategies for petrochemical fire based on cost-risk theory

Hu Renyuan1, Xia Dengyou2   

  1. (1. Chongqing Wanzhou Fire and Rescue Division, Chongqing 404000, China;2. Department of Commanding, Chinese People's Police University, Hebei Langfang 065000, China)
  • Online:2023-07-15 Published:2023-07-15

摘要: 针对突发事件在情景推演中存在的主观性干扰和算法缺陷,以石油化工火灾为对象,首先以分析动态情景演变为基础,论证了前人在贝叶斯网络节点和概率分配存在的缺陷,接着利用频率思维确定条件概率值,并设置了信息收集成本、对策误差风险和时机延误风险3个变量的不等式算法。最后以某液化石油气储罐区火灾为例,将火灾划分为失控、难控和控制3种态势,对应提出防御、进攻、歼灭3种对策,利用软件推演和概率修正,算得不同阶段的最优救援对策。

关键词: 灭火救援, 石油化工火灾, 贝叶斯网络, 成本风险

Abstract: This article addresses the subjectivity interference and algorithmic deficiencies that exist in scenario simulation for sudden events. Using petroleum and chemical fires as the object the article first analyzes the dynamic evolution of the scenario to, demonstrate the shortcomings of previous Bayesian network nodes and probability distribution. Subsequently, frequency thinking is utilized to determine conditional probability values, and an inequality algorithm is established that takes into account the costs of information collection, errors in countermeasures, and risks of delayed response. Finally, taking a fire in a certain liquefied petroleum gas storage tank area as an example, the fire is divided into three situations: out of control, difficult to control, and controllable. Corresponding strategies of defense, attack, and annihilation are proposed. By using software deduction and probability correction, the optimal rescue strategies at different stages are calculated.

Key words:  firefighting and rescue, petrochemical fire, Bayesian network, cost risk