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Development of a multi-unit seismic conditional core damage probability model with uncertainty analysis

机译：具有不确定性分析的多单元地震条件核心损伤概率模型的发展

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摘要

Various studies about multi-unit probabilistic safety assessment (PSA) have been conducted following the Fukushima accident. In this paper, an intuitive and simple model is developed to supplement the disadvantages of huge models that integrate all units in the same site. Through this framework, pre-assessment can be made for multi-unit events, the results of which can assist risk-informed decision making in a relatively short time. The model deducts multi-unit seismic conditional core damage probability (MUSCCDP) with a Bayesian belief network, and by including seismic inter-unit correlation factors, the model can also represent the extent of simultaneous and identical core damage in multiple units at the same site due to an earthquake. The outcome of the model confirms the impact that seismic intensity and seismic correlation have on MUSCCDP. Moreover, it provides an importance analysis of the components in the units and represents which components are the most vulnerable in multiple units. As the uncertainty analysis of the input data for the model is conducted by changing the distribution of the variables, the results raise the necessity for further uncertainty analyses in multi-unit seismic PSA before accepting the PSA results.
机译：在福岛事故之后进行了关于多单位概率安全评估（PSA）的各种研究。在本文中，开发了一种直观和简单的模型，可以补充巨大模型的缺点，这些模型集成了同一站点中的所有单元。通过这一框架，可以对多单元事件进行预评估，结果可以帮助风险明智的决策在相对较短的时间内。该模型用贝叶斯信仰网络扣除多单元地震条件核心损伤概率（Musccdp），并通过包括地震间相关因子，该模型还可以代表同一站点的多个单元中同时和相同的核心损坏的程度由于地震。该模型的结果证实了地震强度和地震相关对Musccdp的影响。此外，它提供了对单位中的组件的重要性分析，并且代表了哪些组件是多个单元中最脆弱的组件。由于通过改变变量的分布来进行模型输入数据的不确定性分析，因此在接受PSA结果之前，结果提高了多单元地震PSA中进一步不确定性分析的必要性。

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