This paper takes the safety in emergency processes as the starting point, from the perspective of scenario deduction, to study the consequences of fire accidents for oil-gas storage and transportation. Through the statistical analysis of actual accident cases, 19 frequently occurring basic scenarios in emergency processes are summarized. The scenario evolution paths of fire accidents for oil-gas storage and transportation are given by analyzing the evolution law of the accident development. Fuzzy numbers are introduced to express experts' qualitative judgment on accident scenarios. The empirical probabilities of scenario nodes are obtained by defuzzification calculation, and the state probability of each scenario node is calculated by using the dynamic Bayesian network joint probability formula. Under the comprehensive consideration about the probability statistics of actual accident cases, the critical scenario nodes on the evolution path and their final scenario probabilities are jointly determined to realize the optimization of the scenario evolution path. By constructing the correlation between the optimized scenario evolution path and the accident consequences, an accident consequence prediction model is established. The occurrence probability of accident consequences is calculated by the defuzzification method and dynamic Bayesian network. The accuracy of the consequence prediction model is verified by the July 16 Dalian's Xingang Harbor oil pipeline explosion accident. The research results provide scientific basis for helping decision makers to make the effective emergency measures that are most conducive to the rapid elimination of accidents and reducing the severity of accident consequences.

本文以应急过程中的安全为切入点，从情景推演的角度，研究油气储运火灾事故的后果。通过对实际事故案例的统计分析，总结出19种应急过程中经常出现的基本情景。通过对事故发展演变规律的分析，给出油气储运火灾事故的情景演变路径。引入模糊数来表达专家对事故场景的定性判断。通过去模糊化计算得到场景节点的经验概率，利用动态贝叶斯网络联合概率公式计算每个场景节点的状态概率。在综合考虑实际事故案例概率统计的情况下，共同确定演进路径上的关键场景节点及其最终场景概率，实现场景演进路径的优化。通过构建优化情景演化路径与事故后果的相关性，建立事故后果预测模型。通过去模糊化方法和动态贝叶斯网络计算事故后果的发生概率。7月16日大连新港港输油管道爆炸事故验证了后果预测模型的准确性。