Initiating Events Analysis in Operating Phase for Pressurized Water Reactor Nuclear Power Plant

Feng Chu-ran, Ma Yuan, Yan Lin, Yang Guansan, Liu Bin
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Abstract

Probabilistic Safety Assessment (PSA) is an important tool for risk-informed integrated decision making application. Initiating events are caused by equipment failure or/and personnel error which causes disturbance to the nuclear power plant (NPP) and may lead to core damage. As the start of PSA, the quality of initiating events analysis has an important influence on safety assessment and PSA application for NPPs, and the application of operating experience of domestic and aboard are of great importance in initiating events analysis. Based on analysis experience of PSA model in design phase and operation phase for different NPPs, this paper developed a set of method for initiating events analysis of operation phase PSA model development. Combined with the referenced initiating events list, engineering evaluation, operating experience analysis and main logic diagram, a relatively complete initiating events list have been determined. According to the characteristics of the initiating events and analysis requirements for PSA applications, this paper adopted statistical analysis method or specific analysis method to determine the frequency of initiating events which could reflect the design of specific NPPs and operation level of domestic NPPs. The development and application of these initiating events analysis method, which could reflect design and operating characteristics more realistically, improved the development level of PSA model in operation phase effectively, and laid a solid foundation for PSA applications.
压水堆核电站运行阶段启动事件分析
概率安全评估(PSA)是风险知情综合决策应用的重要工具。启动事件是由设备故障或/和人员错误引起的,对核电站造成干扰并可能导致堆芯损坏。作为PSA的起点,启动事件分析的质量对核电厂的安全评价和PSA的应用有着重要的影响,而在启动事件分析中,国内外运行经验的应用至关重要。基于不同核电站设计阶段和运行阶段PSA模型的分析经验,提出了一套运行阶段PSA模型开发启动事件分析方法。结合参考的启动事件清单、工程评价、运行经验分析和主要逻辑图,确定了较为完整的启动事件清单。根据启动事件的特点和PSA应用的分析要求,本文采用统计分析法或具体分析法确定能够反映具体核电站设计和国内核电站运行水平的启动事件频率。这些启动事件分析方法的开发和应用,更真实地反映了设计和运行特点,有效地提高了运行阶段PSA模型的开发水平,为PSA的应用奠定了坚实的基础。
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