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Scenario Deduction on Fire Accidents for Oil-Gas Storage and Transportation Based on Case Statistics and a Dynamic Bayesian Network

机译：基于案例统计和动态贝叶斯网络的油气储运与运输灭火事故的情景扣除

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摘要

In order to solve the problem of unclear evolution paths after oil-gas storage and transportation accidents, which lead to a lack of targeted accident emergency, delayed disposal measures, and further deterioration of the accident, based on the existing accident scenario-response theory, this article summarizes 17 basic scenarios in oil-gas storage and transportation by analyzing 116 accident cases. Moreover, the accident scenario expressions are given in time and space dimensions, and general scenario evolution paths of fire accidents for oil-gas storage and transportation are constructed. On this basis, a dynamic scenario deduction network model is established by using a dynamic Bayesian network. In this model, key scenario nodes and their final scenario probabilities are determined in consideration of statistical probability obtained by the actual accident cases, empirical probability given by domain expert's scoring, and state probability calculated by joint probability formula of a dynamic Bayesian network. As a case study, the scenario deduction process and result of a Dalian 7.16 accident are analyzed to verify the rationality and effectiveness of the proposed method. According to the proposed scenario deduction method, it can help decision-makers to make more targeted emergency disposal measures.
机译：为了解决石油储存和运输事故后的进化路径问题，这导致缺乏有针对性的事故应急，延迟处置措施以及事故进一步恶化，基于现有的事故情景 - 反应理论，本文通过分析116例意外情况，总结了油气储存和运输中的17个基本情景。此外，事故情景表达式在时间和空间尺寸上给出，构建了石油 - 气体储存和运输的一般情景进化路径。在此基础上，通过使用动态贝叶斯网络建立动态方案推导网络模型。在该模型中，考虑到通过实际意外情况的统计概率，由域专家评分的得分的经验概率以及由动态贝叶斯网络的联合概率公式计算的状态概率来确定关键场景节点及其最终情景概率。作为一个案例研究，分析了大连7.16事故的情景扣除过程和结果，以验证所提出的方法的合理性和有效性。根据拟议的情景扣除方法，它可以帮助决策者制定更具针对性的紧急处置措施。

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