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On the application of near accident data to risk analysis of major accidents

机译:论近事故数据在重大事故风险分析中的应用

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摘要

Major accidents are low frequency high consequence events which are not well supported by conventional statistical methods due to data scarcity. In the absence or shortage of major accident direct data, the use of partially related data of near accidents - accident precursor data - has drawn much attention. In the present work, a methodology has been proposed based on hierarchical Bayesian analysis and accident precursor data to risk analysis of major accidents. While hierarchical Bayesian analysis facilitates incorporation of generic data into the analysis, the dependency and interaction between accident and near accident data can be encoded via a multinomial likelihood function. We applied the proposed methodology to risk analysis of offshore blowouts and demonstrated its outperformance compared to conventional approaches.
机译:重大事故是低频高后果事件,由于数据稀缺,常规统计方法无法很好地支持这种事件。在缺少或缺少重大事故直接数据的情况下,近事故的部分相关数据(事故先兆数据)的使用已引起了广泛关注。在目前的工作中,已经提出了一种基于层次贝叶斯分析和事故先兆数据的方法,可以对重大事故进行风险分析。虽然分层贝叶斯分析有助于将通用数据合并到分析中,但事故和近事故数据之间的依存关系和交互作用可以通过多项式似然函数进行编码。我们将建议的方法应用于海上井喷的风险分析,并证明了其与常规方法相比的出色表现。

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