Research on living PSA method based on time-dependent MFT for real-time online risk monitoring

Abstract

This paper presents a living PSA modeling and updating method based on a time-dependent modular fault tree (MFT), which takes into account all the failure modes involved in the whole life cycle of a component for continuous state transition and time-dependent problem analysis. And a Stage 4-Living PSA, characterized by real-time online automatic updating model, is achieved using a combination of the time-dependent MFT method and the state monitoring technology. This method has a remarkable effect in enhancing the updating ability, flexibility of the model and reducing the scale of the model. And using this method cannot only capture the risk fluctuations caused by any configuration change more accurately and timely, but also reflect the effect of the component cumulative running time on the real-time risk of the plant, and provide more valuable data for making operation and maintenance decision. Moreover, A real-time online risk monitoring (RORM) system with a hierarchical modular modeling strategy and computational data structure is also developed to automatically update the living PSA model after receiving configuration change information of the plant, and this system displays graphical risk information that helps users to carry out daily operation risk management more effectively at nuclear power plants (NPPs). Finally, the function and interface of this system applied to RORM are demonstrated by using the living PSA model for the Middle Break Loss of Coolant Accident (MLOCA) in the Fuqing NPP. The achievement of RORM can reduce the burden on the plant personnel, and avoided the fact that the lagged and unreasonable risk information that misleads plant personnel into making decisions, resulting in greater risk or economic loss.