基于自适应MCMC和子集模拟的非能动系统热工水力可靠性评估  

Thermal-hydraulic Reliability Evaluation of Passive System Based on Adaptive MCMC and Subset Simulation

作　　者：蒋立志 蔡琦[1] 张永发[1] JIANG Lizhi;CAI Qi;ZHANG Yongfa(College of Nuclear Science and Technology,Naval University of Engineering,Wuhan 430033,China)

机构地区：[1]海军工程大学核科学技术学院,湖北武汉430033

出　　处：《原子能科学技术》2019年第4期695-702,共8页Atomic Energy Science and Technology

基　　金：国防科技重点实验室基金资助项目(32102040302-3)

摘　　要：基于修正Metropolis-Hastings(MMH)算法的子集模拟(SS)方法在较低失效率水平下候选样本接受率降低、失效率估计误差增大、稳健性较差。为进一步提高SS用于反应堆非能动系统热工水力可靠性评估的精度、效率和稳健性,引入一种基于自适应条件采样(aCS)的马尔可夫链蒙特卡罗(MCMC)方法,提出了一种基于自适应MCMC和SS的非能动系统热工水力可靠性评估方法。以某型核动力装置二次侧非能动余热排出试验系统为例,给出了基于aCS的子集模拟(aCS-SS)与基于MMH的子集模拟(MMH-SS)在不同失效率水平下的性能比较。计算结果表明:较低失效率水平下aCS-SS能更好地使候选样本接受率在目标值附近保持稳定,失效率估计的精度和稳健性均高于MMH-SS。For the commonly used subset simulation(SS)method based on modified Metropolis-Hastings(MMH)algorithm,the acceptance rate of candidate samples decreases and the error of failure probability estimate increases at lower failure probability level,and the algorithm’s robustness is also poor.For the accurate,efficient and robust evaluation of thermal-hydraulic reliability of passive system using SS,a new Markov chain Monte Carlo(MCMC)method based on adaptive conditional sampling(aCS)was introduced and a reliability evaluation method based on adaptive MCMC and SS was proposed.Taking the experimental facility of a secondary side passive residual heat removal system as an example,the performance comparison of SS based on MMH(MMH-SS)and SS based on aCS(aCS-SS)was given at different failure probability levels.Calculation results show that,under lower failure rate level,aCS-SS can make the acceptance rate of candidate samples stably near the target value,and accuracy and robustness of the failure probability estimate are higher than those of MMH-SS.

关 键 词：自适应马尔可夫链蒙特卡罗 自适应条件采样 子集模拟 非能动系统 热工水力可靠性 

分 类 号：TL38[核科学技术—核技术及应用]