The risk-based maintenance strategy has received special attention in the safe operation of nuclear power plants (NPPs). Simultaneous quantification of the positive and negative effects of maintenance activities (MAs) and components degradation effect makes it possible to evaluate the risk criterion for NPP safety systems, accurately. However, it is difficult to integrate the effects of maintenance and components degradation into the standard reliability approaches (SRAs). A straightforward approach for considering components degradation and different maintenance policies, is to make use of Markov maintenance models (MMMs). In this paper, the effectiveness of MAs (include changes in the surveillance test intervals and alteration in the different maintenance policies) on the components unavailability with considering aging effects is quantified using MMMs and then by coupling these models and FT method, the risk measure is upgraded from the component level to the system level. The proposed models are applied to evaluate the unavailability of two safety systems of VVER-1000/V446 NPP as case studies. The results show that Markov method due to its multi-state nature is effective in the conservative evaluation of risk measures so that the unavailability computed by the coupling process is higher than the original unavailability (calculated by system FT using NPP PSA data) for all maintenance policies. In addition, this study illustrates that the developed MMMs could be applied to the large-scale whole plant level and provide a proper transition from the classical PSA methods to new techniques. This could integrate the effects of maintenance strategies and components degradation and consequently make available a practical and a more accurate tool for technical specifications (TSs) determination of a real nuclear power plant from the risk point of view.

中文翻译：

---

基于马尔科夫模型和故障树方法的备用冗余安全系统多状态风险维护分析

基于风险的维护策略在核电厂（NPP）的安全运行中受到了特别关注。同时量化维护活动 (MA) 的正面和负面影响和部件退化效应，使得准确评估核电厂安全系统的风险标准成为可能。然而，很难将维护和组件退化的影响整合到标准可靠性方法 (SRA) 中。考虑组件退化和不同维护策略的直接方法是利用马尔可夫维护模型 (MMM)。在本文中，使用 MMM 量化 MAs（包括监视测试间隔的变化和不同维护策略的更改）对组件不可用性的有效性，并考虑老化影响，然后通过耦合这些模型和 FT 方法，从组件升级风险度量级别到系统级别。作为案例研究，所提出的模型用于评估 VVER-1000/V446 核电厂的两个安全系统的不可用性。结果表明，马尔可夫方法由于其多状态性质在风险措施的保守评估中是有效的，因此耦合过程计算的不可用性高于所有维护的原始不可用性（由系统 FT 使用 NPP PSA 数据计算）政策。此外，这项研究表明，开发的 MMM 可以应用于大规模整厂水平，并提供从经典 PSA 方法到新技术的适当过渡。这可以整合维护策略和部件退化的影响，从而从风险的角度为实际核电厂的技术规范 (TS) 确定提供实用且更准确的工具。