This paper proposes a new approach to Ageing Probabilistic Safety Assessment (APSA) modelling, which is intended to be used to support risk-informed decisions on the effectiveness of maintenance management programs and technical specification requirements of critical equipment of Nuclear Power Plants (NPP) within the framework of the Risk Informed Decision Making according to R.G. 1.174 principles. This approach focuses on the incorporation of not only equipment ageing but also effectiveness of maintenance and efficiency of surveillance testing explicitly into APSA models and data. An example of application is presented, which centers on a critical safety-related equipment of a NPP in order to evaluate the risk impact of considering different approaches to APSA and the combined effect of equipment ageing and maintenance and testing alternatives along NPP design life. The risk impact of the several alternatives is quantified and the results shows that such risk depends largely on the model parameters, such as ageing factor, maintenance effectiveness, test efficiency.

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Unavailability model for demand-caused failures of safety components addressing degradation by demand-induced stress, maintenance effectiveness and test efficiency.

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There are many models in the literature that have been proposed in the last decades aimed at assessing the reliability, availability and maintainability (RAM) of safety equipment, many of them with a focus on their use to assess the risk level of a technological system or to search for appropriate design and/or surveillance and maintenance policies in order to assure that an optimum level of RAM of safety systems is kept during all the plant operational life. This paper proposes a new approach for RAM modelling that accounts for equipment ageing and maintenance and testing effectiveness of equipment consisting of multiple items in an integrated manner. This model is then used to perform the simultaneous optimization of testing and maintenance for ageing equipment consisting of multiple items. An example of application is provided, which considers a simplified High Pressure Injection System (HPIS) of a typical Power Water Reactor (PWR). Basically, this system consists of motor driven pumps (MDP) and motor operated valves (MOV), where both types of components consists of two items each. These components present different failure and cause modes and behaviours, and they also undertake complex test and maintenance activities depending on the item involved. The results of the example of application demonstrate that the optimization algorithm provide the best solutions when the optimization problem is formulated and solved considering full flexibility in the implementation of testing and maintenance activities taking part of such an integrated RAM model.