基于抽样的敏感性分析方法在LBLOCA质能释放PIRT评级中的应用  

Application of Sampling Based Sensitivity Analysis in Evaluation of LBLOCA Mass and Energy Release PIRT

作　　者：扈本学[1] 王喆[1] 王伟伟[1] 王国栋[1] 王章立[1] 唐国锋[1] 张今朝[1] 杨萍[1] 刘鑫[1] 

机构地区：[1]上海核工程研究设计院,上海200233

出　　处：《原子能科学技术》2016年第2期290-294,共5页Atomic Energy Science and Technology

摘　　要：基于随机抽样的非参量敏感性统计分析方法是一种有效的敏感性分析方法,通过计算热工水力分析程序多个抽样输入参数与输出参数之间的相关系数来评价各输入参数对输出参数影响的重要程度。通过耦合DAKOTA和WCOBRA/TRAC程序,开发了基于抽样的适用于非能动核电厂大破口失水事故质能释放的敏感性分析方法,该方法可全面定量评估各敏感性参数对计算结果的影响。计算结果表明:堆芯初始功率、燃耗、衰变热、安注箱初始水温、初始水体积、安注箱管道阻力系数、堆芯补水箱初始水温、喷放系数及破口阻力系数对破口质能释放具有显著影响。该分析结果可为大破口失水事故质能释放分析现象识别和重要度排序表评级提供定量依据。The sampling based statistical sensitivity analysis is an effective sensitivity analysis method, and the importance of input parameters of a thermal hydraulic analysis code could be evaluated by calculating the correlation coefficients of input parameters and output parameters. A sampling based sensitivity analysis method for LBLOCA mass and energy release of the large passive plant was developed, by coupling DAKOTA and WCOBRA/TRAC codes. The calculated results show that the initial core power, fuel burnup, decay heat, initial accumulator water temperature, initial accumulator water volume, accumulator pipe friction coefficient, initial core makeup tank water tempera- ture, discharge coefficient and break resistance coefficient affect mass and energy release greatly. The results can provide quantitative support for evaluation of LBLOCA mass and energy release analysis phenomena identification and ranking table.

关 键 词：大破口失水事故 质能释放 敏感性分析 现象识别和重要度排序表 统计法 偏相关系数 

分 类 号：TL364[核科学技术—核技术及应用]