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。     

自适应蒙特卡罗方法计算海水淡化堆非能动系统物理过程失效概率

物理过程失效的研究对于非能动系统十分重要。目前,已被广泛应用的重要抽样蒙特卡罗方法需要依赖改进的一次二阶矩法寻找设计点。本文应用自适应蒙特卡罗方法,利用自适应方法确定重要密度函数,避免了改进的一次二阶矩法的不足,提高了抽样效率,而且在相同的模拟条件下,可较好地改善相对误差。以245 MW海水淡化堆非能动系统为研究对象,用自适应蒙特卡罗方法和目前已有的其他方法研究非能动系统的物理失效概率,最后对各方法在非能动系统上的适用性进行比较分析。     

核电厂非能动余热排出系统的失效概率评价

先进核电厂设计中大量采用非能动安全系统提高反应堆安全性。但目前尚无系统性评价非能动系统的成熟方法,而且概率安全评价(PSA)也未考虑非能动系统自然循环现象不确定性导致的功能失效。在欧盟非能动系统可靠性评价研究项目(RMPS)研究成果的基础上,以压水堆二次侧非能动余热排出系统(PRS)为研究对象,基于统计学和热工水力计算确定了影响性能的参数重要度,进而利用蒙特卡罗抽样和响应面分析对全厂断电事故下的PRS自然循环失效概率进行了量化分析评价。初步评价结果表明:非能动系统功能失效概率为2.14×10-3,在PSA中应当充分考虑各种非能动系统的功能失效。本文的评价方法还可以为非能动安全系统设计优化提供支持。     

非能动安全系统可靠性评估方法初步研究

非能动安全系统可靠性的分析是广泛采用非能动设计的新一代核电厂概率安全评价(PSA)的重要内容,其量化分析需根据非能动安全系统可靠性评估对象,确定影响系统运行的关键参数,结合事件序列对非能动系统进行研究。本文以AP1000非能动余热排出系统(PRHRS)设计阶段的可靠性研究为例,结合丧失主给水事故,根据燃料包壳完整性以及系统稳定性的功能准则,确定影响PRHRS的关键参数和设计参数。采用拉丁超立方抽样(LHS)确定输入参数组合,运用RELAP5/MOD3程序进行不确定性传递计算,进行关键参数对系统功能敏感性评价与确认,进行系统功能可靠性分析,为AP1000概率安全评价提供PRHRS可靠性估计。     

基于数据挖掘的非能动系统功能可靠性评估方法研究

针对多维不确定性参数及小概率的功能失效问题,提出一种基于数据挖掘的功能可靠性分析方法。该方法将自举抽样响应面拟合模型及最优化线抽样技术相结合,进而高效获得非能动系统的功能可靠性。以西安脉冲堆为例,结合中破口失水事故,考虑输入参数及模型的不确定性,对其进行功能可靠性评价。结果表明,该自举抽样响应面模型具有较高的拟合度;最优化线性抽样技术具有很高的计算效率,同时又能保证很好的计算精度。因此,本研究的评价方法对非能动系统隐式非线性的功能失效分析具有很强的适应性。      

不确定性对于非能动系统性能的影响

通常认为，非能动安全系统比能动安全系统更可靠，因为其没有机械运动部件或其他能动部件，非能动安全系统能够显著地降低硬件故障的概率。然而，对于非能动系统，有必要引入功能故障的概念，例如，存在这样的可能性，即在可靠性物理构架中，可能发生负荷超过其容量的情况。本文中，我们分析了气冷快中子反应堆的非能动冷却，利用了重要性抽样的蒙特卡洛技术来分析不确定性，并计算功能故障概率。结果表明：功能故障对系统的故障概率具有重要的影响，因此，功能故障应该包括在概率风险评价中。同时，还对非能动设计和一个替代的能动设计进行了比较。结果表明，对于这种特殊的应用，能动系统的可靠性可以比非能动系统的可靠性更好。     

用Monte Carlo方法计算HTR-10余热排出系统物理过程的失效概率

介绍了计算物理过程失效概率的蒙特卡罗方法(Monte Carlo).应用重要抽样蒙特卡罗方法计算了10 MW高温气冷实验堆(HTR-10)余热排出系统物理过程的失效概率,并进行了误差分析.与响应面方法的计算结果进行比较后发现,两种方法得到的计算结果数量级相同,进一步验证了以下结论:由于采用了非能动设计,HTR-10的余热排出系统的失效概率至少降低了3个数量级.     

基于响应曲面和重要性抽样方法的热力系统参数失效概率计算

本文研究了将响应曲面与重要性抽样相结合的方法用于复杂热力系统参数失效概率的计算。建立了热力系统物理过程参数失效的数学模型,在此基础上研究了将响应曲面与重要性抽样相结合的算法模型,并给出了热力系统组成设备的性能退化模型和基于重要性抽样的仿真流程,进而对反应堆净化系统工作过程中参数失效问题进行了分析计算。研究表明,对于高维、非线性特性明显并考虑性能退化的复杂热力系统参数失效概率的计算,重要性抽样法较直接抽样能以较高效率获得满意精度的计算结果,而响应曲面法存在局限;响应曲面和重要性抽样相结合的方法是分析热力系统物理过程参数失效的有效方法。     

地震下非能动堆芯冷却系统可靠性分析

地震情况下核电站非能动堆芯冷却系统（PXS）能否可靠运行对核电站的安全性有着重要影响。本文采用故障树方法分析计算了PXS各部件在峰值地面加速度（PGA）为0.5g、1.5g、2.5g情况下的失效概率以及各部件对系统失效的贡献,并与《AP1000概率安全分析报告》中的抗震裕量分析（SMA）方法的结果进行比较,分析部件的抗震能力。结果表明：本文方法计算的条件失效概率和各部件对系统失效的贡献与SMA方法的结果基本相符。本文方法可为AP1000等非能动核电站的安全分析提供参考。     

XAPR中破口失水事故下堆芯自然循环冷却能力的功能可靠性研究

功能失效是导致自然循环系统运行失效的重要因素,需在其可靠性分析中予以考虑。针对多维不确定性参数及小功能失效概率问题,提出了一种将改进响应面法及重要抽样子集模拟法相结合的功能可靠性分析方法。以西安脉冲堆（XAPR）堆池水自然循环冷却为例,结合中破口失水事故,考虑输入参数及模型的不确定性,对其进行了功能可靠性评估和灵敏度分析。结果表明：XAPR堆芯自然循环功能失效概率为3.796×10^-3,需充分考虑系统功能的可靠性。本文方法具有较高的计算效率,同时又能保证很高的计算精度,对XAPR堆芯自然循环非线性功能函数具有很强的适应性。     

基于最优化线抽样法的XAPR自然循环功能失效研究与分析

针对多维不确定性参数、小失效概率的功能可靠性分析,提出了一种优化线抽样的可靠性分析方法。该方法采用遗传算法求解约束条件的优化模型来寻求最优化重要方向,进而得到失效概率的高效估计。以西安脉冲堆（XAPR）自然循环冷却堆芯能力的可靠性评价为例,考虑模型与输入参数的不确定性,对中破口失水事故下的自然循环功能失效概率进行了量化分析。结果表明：与其他概率评估方法相比,本文方法具有很高的计算效率,同时又能保证很好的计算精度;对隐式非线性的功能可靠性分析是有效可行的,具有很强的适应性。     

Integration of functional reliability analysis with hardware reliability: An application to safety grade decay heat removal system of Indian 500 MWe PFBR

A passive system can fail either due to classical mechanical failure of components, referred to as hardware failure, or due to the failure of physical phenomena to fulfill the intended function, referred to as functional failure. In this paper a methodology is discussed for the integration of these two kinds of unreliability and applied to evaluate the integrated failure probability of the passive decay heat removal system of Indian 500 MWe prototype fast breeder reactor (PFBR). The probability of occurrence of various system hardware configurations is evaluated using the fault tree method and functional failure probabilities on the corresponding configurations are determined based on the overall approach reported in the reliability methods for passive system (RMPS) project. The variation of functional reliability with time, which is coupled to the probability of occurrence of various hardware system configurations is studied and incorporated in the integrated reliability analysis. It is observed that this consideration of the dependence of functional reliability on time will give significant advantages on system reliability. The integrated reliability analysis is also explained using an event tree. The impact of the provision for forced circulation in the primary circuit on functional reliability is also studied with this procedure and it is found that the forced circulation capability helps to bring down the total decay heat removal failure probability by lowering the peak temperatures after the reactor shut down.     

Efficient reliability estimate of passive thermal hydraulic safety system with automatic differentiation

An approach for efficient estimation of passive safety system functional reliability has been developed and applied to a simplified model of the passive residual heat transport system typical of sodium cooled fast reactors to demonstrate the reduction in computational time. The method is based on generating linear approximations to the best estimate computer code, using the technique of automatic reverse differentiation. This technique enables determination of linear approximation to the code in a few runs independent of the number of input variables for each response variable. The likely error due to linear approximation is reduced by augmented sampling through best estimate code in the neighborhood of the linear failure surface but in a sub domain where linear approximation error is relatively more. The efficiency of this new approach is compared with importance sampling MCS which uses the linear approximation near the failure region and with Direct Monte-Carlo Simulation. In the importance sampling MCS, variants employing random sampling with Box-Muller algorithm and Markov Chain algorithm are inter-compared. The significance of the results with respect to system reliability is also discussed.     

Estimation of the functional failure probability of a thermal-hydraulic passive system by Subset Simulation

In the light of epistemic uncertainties affecting the model of a thermal-hydraulic (T-H) passive system and the numerical values of its parameters, the system may find itself in working conditions which do not allow it to accomplish its function as required. The estimation of the probability of these functional failures can be done by Monte Carlo (MC) sampling of the uncertainties in the model followed by the computation of the system response by a mechanistic T-H code. The procedure requires considerable computational efforts for achieving accurate estimates. Efficient methods for sampling the uncertainties in the model are thus in order.In this paper, the recently developed Subset Simulation (SS) method is considered for improving the efficiency of the random sampling. The method, originally developed to solve structural reliability problems, is founded on the idea that a small failure probability can be expressed as a product of larger conditional probabilities of some intermediate events: with a proper choice of the conditional events, the conditional probabilities can be made sufficiently large to allow accurate estimation with a small number of samples. Markov Chain Monte Carlo (MCMC) simulation, based on the Metropolis algorithm, is used to efficiently generate the conditional samples, which is otherwise a non-trivial task.The method is here developed for efficiently estimating the probability of functional failure of an emergency passive decay heat removal system in a simple steady-state model of a Gas-cooled Fast Reactor (GFR). The efficiency of the method is demonstrated by comparison to the commonly adopted standard Monte Carlo Simulation (MCS).     

Reliability assessment of passive containment isolation system using APSRA methodology

In this paper, a methodology known as APSRA (Assessment of Passive System ReliAbility) has been employed for evaluation of the reliability of passive systems. The methodology has been applied to the passive containment isolation system (PCIS) of the Indian advanced heavy water reactor (AHWR). In the APSRA methodology, the passive system reliability evaluation is based on the failure probability of the system to carryout the desired function. The methodology first determines the operational characteristics of the system and the failure conditions by assigning a predetermined failure criterion. The failure surface is predicted using a best estimate code considering deviations of the operating parameters from their nominal states, which affect the PCIS performance. APSRA proposes to compare the code predictions with the test data to generate the uncertainties on the failure parameter prediction, which is later considered in the code for accurate prediction of failure surface of the system. Once the failure surface of the system is predicted, the cause of failure is examined through root diagnosis, which occurs mainly due to failure of mechanical components. The failure probability of these components is evaluated through a classical PSA treatment using the generic data. The reliability of the PCIS is evaluated from the probability of availability of the components for the success of the passive containment isolation system.