[en] The GO methodology is an effective method of system reliability analysis. It has been applied to non-repairable systems. This paper discusses the application of the GO method to a repairable system which is described by a Markov model and presents the quantification algorithm of the steady characteristics of the repairable system. The calculation formulas of the ordinary operators and the logical gates are derived and the steady reliability parameters of the system such as average operation probability and average failure frequency can be directly computed by the GO method. The result of an example shows that the algorithm is correct. The algorithm will be useful for the safety analysis of most engineering repairable systems

[en] This paper provides a new quantification algorithm in the GO methodology, which includes three parts: (1) A signal state cumulative probability is introduced and defined based on the definitions of the signal states in the GO method. (2) The quantitative formulas of signal state cumulative probabilities have been derived, so it is unnecessary to calculate the joint probability of the complex combination of states. (3) The calculation process and the transfer rules about the shared signal have been presented, therefore, the new algorithm permits the direct calculation of all signal state cumulative probability. The new algorithm is very easy for programming. It is an improved algorithm in the GO methodology instead of the joint probability algorithm. The result of an example shows that the algorithm is practical and meaningful for development and application of the GO methodology and useful in practice

[en] This paper provides an exact quantification algorithm dealing with shared signals in the GO methodology. The exact calculation formulas of the output signal state probability of a logic operator, which includes the input signals with the shared signals, have been derived. All the shared signals should be transferred to the output signal of this logic operator and in the following calculation the formulas are still exact. This exact algorithm permits the direct calculation of all signal state probabilities of the systems. The result of an example shows that the exact algorithm is available and meaningful for more development of the GO methodology, it will be useful for more practical applications

[en] The authors provides a number of important principles relevant to human reliability modeling that have emerged from cognitive models, and presents generic error modeling system (GEMS) and its application in nuclear power plants incidents, and addresses the effort of GEMS on human error predication. Last section presents the principle of the method of computer simulation of GEMS

[en] GO methodology is a method of system reliability with success-oriented, it has been applied in non-repairable system. The author studies application of GO methodology in repairable system. Considering dependence of components, the quantitative formulas of some GO operations for repairable system have been derived. According to this study, the GO program has been developed. Reliability parameters such as steady availability and failure number can be calculated directly from GO figure and a High Pressure Injection System of Nuclear Power Plant example is given. The study is available for developing and application of GO methodology in repairable system such as nuclear engineering pipeline systems or chemical process systems

[en] This paper is concerned with how management and organizational influences can be factored into quantifying human error probabilities on risk assessments, using a three-level Influence Diagram (ID) which is originally only as a tool for construction and representation of models of decision-making trees or event trees. An analytical model of human errors causation has been set up with three influence levels, introducing a method for quantification assessments (of the ID), which can be applied into quantifying probabilities) of human errors on risk assessments, especially into the quantification of complex event trees (system) as engineering decision-making analysis. A numerical case study is provided to illustrate the approach

[en] This paper described modeling and quantification of the probability of repeatable sequential human error event in application of risk assessment and induced some usual formula of calculation of human error event for task in serial or in parallel. It was proved by calculation of practical example that this model can solve more accurate calculation of the probability of the dependent repeatable sequential human error event and it can be used for calculation of unavailability including human error event in redundant systems

[en] The author presents a methodology of coded fault tree to analyze the various disasters, which links all failures, as far as possible back to some human errors, such as design error, maintenance error, operator error, etc. It also shows that human reliability analysis and the factors of organizational and management have played very important role in the safety of complex system

[en] Cognitive Reliability and Error Analysis Method (CREAM) is a representative second-generation human reliability analysis method and it has a binary function-retrospection and prediction. The basic thought of the retrospective analysis method of CREAM is introduced. The framework and the practical steps to finish the retrospective analysis are also given. Based on the retrospective analysis method of CREAM, four significant human failure events in the TMI accident are analyzed. The result shows that the root causes are related with the context of the power plant which is the human-error-forcing factor, and it also proves the usefulness and validity of the retrospective analysis method of CREAM. (author)

[en] By the simulator experiment for the Qinshan NPP operators, the identification method of parameters and classification of Human Cognitive Reliability model and the analysis method of the response time data are described. It is found that the main factor for classification is the normalized standard deviation, which is a critic parameter of Weibull distribution. Using the classification and analysis method presented in the paper, the cognitive reliability parameters for the Qinshan NPP operators are obtained from the Qinshan simulator experiment data. The result of the Qinshan experiment basically coincides with the IAEA experiment. (authors)