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首页> 外文期刊>Reliability Engineering & System Safety >A Bayesian Network Approach for Modeling Dependent Seismic Failures in a Nuclear Power Plant Probabilistic Risk Assessment
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A Bayesian Network Approach for Modeling Dependent Seismic Failures in a Nuclear Power Plant Probabilistic Risk Assessment

机译：北京核电站概率风险评估中依赖地震失效的贝叶斯网络方法

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摘要

The importance of modeling dependency between seismic failures of multiple components in a nuclear power plant (NPP) probabilistic risk assessment (PRA) has been discussed since the 1980s. In NUREG/CR-7237, Budnitz et al. found the Reed-McCann method to be the most promising method for modeling dependent seismic failures in NPP PRA. However, there are issues with the Reed-McCann method's quantification of the seismic fragility of a system of multiple components. To address this issue and to facilitate an overall realism increase in modeling dependencies in seismic PRA, this paper proposes a Bayesian network (BN) approach to model dependent seismic failures. To illustrate the proposed approach, we calculate the fragility of a parallel system and a series system using the Reed-McCann method, the BN approach, the First-Order Reliability Method (FORM) and Monte Carlo simulation (MCS). Then, we compare the system fragility results from these four approaches/methods to the lower and upper bounds of the system fragility. We found that the BN approach performed better than the Reed-McCann method with respect to providing results that stay within the lower and upper bounds of the system fragility. Further, the BN approach gives similar results to FORM and MCS. This paper proposes a BN approach because, in combination with our previous work about extending a probabilistic seismic hazard analysis to account for the spatial variability of ground motion at an NPP hard-rock site, it can be used to simultaneously and realistically account for dependent seismic failures and spatial variability of ground motion in both single-unit and multi-unit seismic PRAs.
机译：自20世纪80年代以来，已经讨论了核电站（NPP）概率风险评估（PRA）在核电厂（NPP）概率风险评估（PRA）之间建模依赖性的重要性。在Nureg / Cr-7237中，Budnitz等人。发现Reed-McCann方法是用于在NPP PRA中建模依赖地震失败的最有希望的方法。然而，REED-MCCANN方法存在多个组分系统的地震碎片的量化问题。为了解决这个问题，并促进地震PRA模型依赖性的整体现实主义增加，本文提出了一种贝叶斯网络（BN）依赖地震失败的方法。为了说明所提出的方法，我们使用REED-MCCANN方法，BN方法，一阶可靠性方法（表格）和蒙特卡罗模拟（MCS）计算并行系统和串联系统的脆弱性。然后，我们将系统脆性与系统脆性的下限和上限进行比较。我们发现，关于提供保持在系统脆性的下限和上限的结果，BN方法比REED-MCCANN方法更好。此外，BN方法给出了类似结果的形式和MC。本文提出了一个BN方法，因为，与我们之前的工作组合在于延长概率地震危险分析，以考虑NPP硬岩位点的地面运动的空间变化，它可用于同时和现实地占依赖地震的单位和多单元地震PRA中地面运动的故障和空间变异。

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