摘要
反应堆保护系统(RPS)是核电厂(NPP)仪表与控制系统的重要组成部分。RPS的可靠性分析一直是热门的研究领域。传统的可靠性分析方法(马尔科夫方法)在对定期试验(PT)等动态行为进行可靠性分析时存在一定的局限性。基于标准蒙特卡罗方法,建立了反应堆保护系统PT的可靠性仿真流程,并引入重要度抽样方法提高仿真效率。通过将重要度抽样仿真结果与理论值对比,验证了重要度抽样方法可用于RPS的可靠性分析。通过将重要度抽样方法与标准蒙特卡罗方法的仿真结果进行定性与定量的对比,说明了在保证计算精度的条件下,重要度抽样方法可以减小仿真次数,大大提高仿真效率。重要度抽样方法可以显著提高蒙特卡罗方法的仿真效率,实现对多元件的复杂物理系统进行更精细的可靠性仿真和分析,为工程应用奠定基础。
Reactor protection system(RPS)is an important part of nuclear power plant(NPP)instrumentation and control system.The reliability analysis of the RPS is a popular area of research.The traditional reliability analysis method(Markov method)presents certain limitations for reliability analysis of dynamic behavior such as periodic test(PT).Based on standard Monte Carlo method,a reliability simulation process for PT of the RPS is established,and importance sampling method is introduced to improve simulation efficiency.By comparing the simulation results of importance sampling with the theoretical values,it is verified that importance sampling method can be used for the reliability analysis of the RPS.Through qualitative and quantitative comparison of the simulation results between importance sampling method and standard Monte Carlo method,it is shown that importance sampling method can reduce the number of simulations and greatly improve the simulation efficiency under the condition of ensuring the calculation accuracy.Importance sampling method can significantly improve the simulation efficiency of Monte Carlo method,realize more detailed reliability simulation and analysis of complex physical system with multiple components,and lay the foundation for engineering application.
作者
韦文彬
李铎
WEI Wenbin;LI Duo(Science and Technology on Reactor System Design Technology Laboratory,Nuclear Power Institute of China,Chengdu 610213,China;Institute of Nuclear and New Energy Technology,Tsinghua University,Beijing 100084,China)
出处
《自动化仪表》
CAS
2021年第S01期214-217,共4页
Process Automation Instrumentation
基金
国家重大科技专项基金资助项目(ZX06901)。
关键词
反应堆保护系统
可靠性分析
定期试验
动态行为
标准蒙特卡罗方法
重要度抽样
仿真效率
计算精度
Reactor protection system(RPS)
Reliability analysis
Periodic test
Dynamic behavior
Standard Monte Carlo method
Importance sampling
Simulation efficiency
Calculation accuracy
