Abstract This paper presents a living PSA modeling and updating method based on a time-dependent modular fault tree (MFT), which takes into account all the failure modes involved in the whole life cycle of a component for continuous state transition and time-dependent problem analysis. And a Stage 4-Living PSA, characterized by real-time online automatic updating model, is achieved using a combination of the time-dependent MFT method and the state monitoring technology. This method has a remarkable effect in enhancing the updating ability, flexibility of the model and reducing the scale of the model. And using this method cannot only capture the risk fluctuations caused by any configuration change more accurately and timely, but also reflect the effect of the component cumulative running time on the real-time risk of the plant, and provide more valuable data for making operation and maintenance decision. Moreover, A real-time online risk monitoring (RORM) system with a hierarchical modular modeling strategy and computational data structure is also developed to automatically update the living PSA model after receiving configuration change information of the plant, and this system displays graphical risk information that helps users to carry out daily operation risk management more effectively at nuclear power plants (NPPs). Finally, the function and interface of this system applied to RORM are demonstrated by using the living PSA model for the Middle Break Loss of Coolant Accident (MLOCA) in the Fuqing NPP. The achievement of RORM can reduce the burden on the plant personnel, and avoided the fact that the lagged and unreasonable risk information that misleads plant personnel into making decisions, resulting in greater risk or economic loss.

中文翻译：

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基于时间相关MFT的实时在线风险监测的活体PSA方法研究

摘要 本文提出了一种基于时间相关模块故障树 (MFT) 的实时 PSA 建模和更新方法，该方法考虑了组件整个生命周期中涉及的所有故障模式，以实现连续状态转换和时间相关问题。分析。并结合瞬态MFT方法和状态监测技术，实现了以实时在线自动更新模型为特征的Stage 4-Living PSA。该方法在增强模型的更新能力、灵活性和减小模型规模方面效果显着。并且使用这种方法不仅可以更准确及时地捕捉到任何配置变化引起的风险波动，还可以反映组件累计运行时间对工厂实时风险的影响，为运维决策提供更有价值的数据。此外，还开发了具有分层模块化建模策略和计算数据结构的实时在线风险监控（RORM）系统，在收到工厂配置更改信息后自动更新实时PSA模型，该系统显示图形风险信息，帮助用户更有效地开展核电厂（NPP）的日常运行风险管理。最后，利用福清核电厂冷却剂中间断流事故（MLOCA）的实时PSA模型，演示了该系统应用于RORM的功能和接口。RORM的实现可以减轻工厂人员的负担，