油储系统火灾事故的发展蔓延将导致灾害更为严重的二次或次生事故,为较准确掌握事故可能的发展过程和变化趋势,根据情景分析思想,提出了基于案例和随机网络的油储系统火灾情景推演方法,构建了情景推演随机网络模型。通过对国内外173例石油储罐典型火灾爆炸事故案例的统计分析,总结出油储系统火灾事故应急过程中20种主要情景,构建了油储系统火灾事故情景演化路径图,并运用随机网络方法将其转化为油储系统火灾事故情景演化随机网络,通过随机网络解析算法,求得了情景演化路径的可能发生概率、平均发生时间、发生时间方差等特征值。在情景可能发生概率求解中,提出了综合考虑由案例统计得到的情景条件概率和Dempster-Shafer(DS)证据理论修正的专家评分得到的情景经验概率相结合的情景发生概率求解规则。以大连“7·16”油库火灾爆炸事故为例,通过与实际事故发展演化过程的对比分析,验证了所提方法和模型的有效性。基于案例和随机网络的油储系统火灾情景推演方法和推演随机网络模型,较好地解决了事故发展演化过程的定性和定量描述问题,为油储系统火灾事故情景演化态势的判断从概率统计意义上提供了新的量化分析手段。

The development and spread of fire incidents for oil storage system will lead to more serious secondary incidents. In order to grasp the possible development process and changing trend of the incident more accurately, based on the scenario analysis approach, this paper proposes a scenario evolution method of oil storage system fire based on historical cases and GERT (Graphical Evaluation and Review Technique) network, and develops a scenario evolution GERT network model. Through the statistical analysis of 173 historical cases of fire and explosion incidents in oil storage tank at home and abroad in nearly 50 years, twenty main scenarios in the emergency processes for fire incidents in oil storage system are summarized, and the possible scenario evolution paths of fire incident for oil storage system are developed and transformed into GERM network of scenario evolution. The probability of occurrence, average occurrence time, variance of occurrence time and other characteristics of possible paths of scenario evolution are obtained by analysis algorithm of GERT network. Among them, the solving rule of scenario occurrence probability is put forward, which combines the scenario conditional probability obtained by case statistics with the scenario experience probability obtained by expert score modified by DS (Dempster-Shafer) evidence theory. Taking the“7·16”Dalian Oil Depot fire and explosion incident as an example, the effectiveness of the proposed method and model is verified by comparing the development and evolution process with actual event. The scenario evolution method and model of oil storage system fire based on historical cases and GERT network can better solve the problem of qualitative and quantitative description of the development and evolution process of the incident, which provides a new quantitative analysis method for judging the scenario evolution of fire incident in oil storage system from the perspective of probability statistics.