一体化压水堆非能动余热排出系统可靠性分析  

Reliability assessment of a passive residual heat removal system for IPWR

作　　者：王晨阳 彭敏俊 夏庚磊 丛腾龙 WANG Chenyang;PENG Minjun;XIA Genglei;CONG Tenglong(Fundamental Science on Nuclear Safety and Simulation Technology Laboratory,Harbin Engineering University,Harbin 150001,China)

机构地区：[1]哈尔滨工程大学核安全与仿真技术国防重点学科实验室,黑龙江哈尔滨150001

出　　处：《哈尔滨工程大学学报》2018年第12期1910-1917,共8页Journal of Harbin Engineering University

摘　　要：为了提高计算非能动安全系统功能失效概率时的计算效率,量化非能动系统的可靠性,推动非能动安全系统的发展,本文采用层次分析法选定关键参数,使用RELAP5进行一体化压水堆IPWR200的热工水力模型的建立,进行不确定性传递得到系统响应值形成训练集。训练人工神经网络作为复杂热工水力程序的替代模型,并利用响应面法计算了非能动余热排出系统的物理过程失效概率,最后将结果整合到硬件失效的故障树分析模型中。结果表明:IPWR200非能动余热排出系统可靠性较高,物理过程失效是导致系统失效的关键因素。To improve the computational efficiency when calculating the failure probability of passive safety systems as well as quantify the passive system reliability and promote the development of the passive safety systems,analytic hierarchy process is used to screen key parameters.In addition,RELAP5 is used to establish the IPWR200 thermal hydraulic model,and uncertainty propagation is used to obtain the system response value of training set.The neural network response surface method is used to train the artificial neural network to be a substitute model for complicated thermal hydraulic procedure and calculate the failure possibility of the physical process of passive residual heat removal system(PRHRS).Finally,the output is integrated into the fault tree analysis model that calculates the hardware failure probality.The results show that the IPWR200 passive residual heat removal system has a high reliability,and failure of the physical process is the key factor that causes PRHRS failure.

关 键 词：非能动系统 可靠性 响应面 概率安全分析 一体化压水堆 RELAP5 神经网络 功能失效 

分 类 号：TL33[核科学技术—核技术及应用]