安全大数据驱动的核电厂实时概率安全分析研究现状与发展前景

Research Status and Prospects of Real-Time Probabilistic Safety Analysis Driven by Safety Big Data

概率安全分析(PSA)是保障核电厂安全运行的关键方法之一,现有PSA方法多依靠有限的数据和专家经验开展静态的安全风险量化,难以精确反映核电厂运行阶段真实动态风险。核电厂运行过程中已实时收集并存储了大量可用来记录和描述系统安全状态的安全大数据,其信息提取和PSA融合需求迫切,本文对安全大数据在核电厂安全保障中的地位进行介绍,并分析总结安全大数据驱动的核电厂实时概率安全分析研究现状和发展前景。结果表明:安全大数据的应用有助于全面分析核电厂实时运行风险,将由安全大数据转换而来的安全信息与现有概率安全分析方法有机融合以实现准确可信的核电厂实时安全分析是未来重要方向。

Probabilistic safety analysis(PSA)is one of the key methods to ensure the safety of nuclear power plant operations.The current practices of PSA mainly rely on limited data and expert experience to conduct static risk quantification,and hence cannot accurately reflect the actual risk of nuclear power plant operations.A large amount of data has been collected and stored in real-time through the nuclear power plant operations,which can be used to track the system safety status,referred to as,safety big data.In order to improve nuclear power plant safety,it is of great significance and urgent need to research and develop the technology and method for realtime PSA by integrating the safety big data into the current PSA methods.Therefore,this paper briefly introduces the status of safety big data in the safety assurance of nuclearpower plants and focuses on the research status and prospects of real-time PSA of nuclear power plants driven by safety big data.The results show that safety big data would contribute to a comprehensive analysis of the operation safety of nuclear power plants in real-time;it would be the important direction of future research to systematically integrate the safety information extracted from safety big data and the current PSA methods to achieve accurate and trustworthy real-time safety analysis of nuclear power plants.