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The purpose of this paper is to extend the meta-theory of theory of nuclear safety to a new stage. Meta-theory method describes nuclear power plant’s nuclear safety systematically and is devised to analyze and to assist the investigation of the theory of nuclear safety. Different types of “capacity” and “load” via RISMC method were present by meta-theory, which could be found out from the real examples that one of load and capacity is deterministic, while the other is probabilistic. In the current research, the authors intend to develop all four combinations in one single Initial Event, aiming to extend this meta-theory method to a more extensive and practical level. A methodology has been verified by a specific yet simple engineering case, i.e., LOCA. To validate its logic, we present an Event Tree to explain the different responses of different safety systems. Then, RELAP 5 is programmed to establish a traditional LOCA sequence to investigate the changing situations of various parameters in reactor coolant system. Based on these approaches, the “capacity” and “load” should be described and all the four “capacity – load” cases in an Initial Event are determined. [ABSTRACT FROM AUTHOR]

This paper investigates the time-dependent modeling of the operating behaviors of systems in risk monitoring applications. The approach used focuses on the constructed concept of the risk monitoring time axis and on time-dependent failure probability modeling for dependencies based on this axis. Dependencies among the complex operating behaviors in nuclear power plants (NPPs) are often superimposed on each other. To ensure the safe and reliable operation of the system, a large number of redundant designs are used in NPPs. In this paper, we mainly focus on the dependencies that are common in redundant systems, such as state dependencies, sequential failures and common-cause failure (CCF). Studies are conducted on the rationality and applicability to the risk monitoring model of the model simplification assumptions for ignoring certain dependency problems in traditional static probabilistic safety assessment (PSA) modeling. Time-dependent mathematical models considering these dependencies in risk monitoring are proposed in this paper. Additionally, time-dependent mathematical models considering the superposition of these dependency problems in risk monitoring are developed, and the process of updating the above models with time and configuration changes is also studied in this paper to provide modelers with guidelines for representing such aspects in the risk monitoring application. Moreover, based on the above research results, a second-order redundant system is taken as an example to calculate and compare time-dependent system risk measurements of the model proposed in this paper and the time-independent system risk of the traditional risk monitoring model. These comparative studies demonstrate the effectiveness and benefits of the method proposed in this paper and provide some insightful conclusions. Only by accurately considering the time dependence and system dependencies can we obtain an accurate system risk and then make a reasonable and credible risk-informed decision. [ABSTRACT FROM AUTHOR]

• A Stage 4-living PSA method based on the time-dependent MFT is proposed. • This method enables real-time automatic updating model according to the state signal. • This method can reflect the effect of the cumulative running time on the system risk. • A real-time online risk monitoring (RORM) system is developed based on this method. • The functions and interfaces of the RORM are demonstrated with an application case. 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. [ABSTRACT FROM AUTHOR]