基于子集模拟法非能动系统功能故障概率评估

针对非能动系统多维不确定性参数和小功能故障概率问题，提出基于马尔可夫链蒙特卡罗子集模拟的可靠性分析方法。该方法通过引入适当的中间失效事件，将小功能故障概率表达为一系列较大的中间失效事件条件概率乘积的形式，进而利用马尔可夫链模拟的条件样本点来计算条件失效概率。以AP1000非能动余热排出系统为研究对象，考虑热工水力学模型和输入参数的不确定性，对其进行功能故障概率评估。结果表明：与其它概率评估方法相比，子集模拟法具有较高的计算效率，同时又能保证很高的计算精度；对非能动安全系统非线性功能函数有很强的适应性。

Estimation of Functional Failure Probability of Passive Systems Based on Subset Simulation Method

In order to solve the problem of multi-dimensional epistemic uncertainties and small functional failure probability of passive systems,an innovative reliability analysis algorithm called subset simulation based on Markov chain Monte Carlo was presented.The method is found on the idea that a small failure probability can be expressed as a product of larger conditional failure probabilities by introducing a proper choice of intermediate failure events.Markov chain Monte Carlo simulation was implemented to efficiently generate conditional samples for estimating the conditional failure probabilities.Taking the AP1000 passive residual heat removal system,for example,the uncertainties related to the model of a passive system and the numerical values of its input parameters were considered in this paper.And then the probability of functional failure was estimated with subset simulation method.The numerical results demonstrate that subset simulation method has the high computing efficiency and excellent computing accuracy compared with traditional probability analysis methods.