• 제목/요약/키워드: Reliability Graph with General Gates

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Evaluation of availability of nuclear power plant dynamic systems using extended dynamic reliability graph with general gates (DRGGG)

  • Lee, Eun Chan;Shin, Seung Ki;Seong, Poong Hyun
    • Nuclear Engineering and Technology
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    • 제51권2호
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    • pp.444-452
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    • 2019
  • To assess the availability of a nuclear power plant's dynamic systems, it is necessary to consider the impact of dynamic interactions, such as components, software, and operating processes. However, there is currently no simple, easy-to-use tool for assessing the availability of these dynamic systems. The existing method, such as Markov chains, derives an accurate solution but has difficulty in modeling the system. When using conventional fault trees, the reliability of a system with dynamic characteristics cannot be evaluated accurately because the fault trees consider reliability of a specific operating configuration of the system. The dynamic reliability graph with general gates (DRGGG) allows an intuitive modeling similar to the actual system configuration, which can reduce the human errors that can occur during modeling of the target system. However, because the current DRGGG is able to evaluate the dynamic system in terms of only reliability without repair, a new evaluation method that can calculate the availability of the dynamic system with repair is proposed through this study. The proposed method extends the DRGGG by adding the repair condition to the dynamic gates. As a result of comparing the proposed method with Markov chains regarding a simple verification model, it is confirmed that the quantified value converges to the solution.

Improvement of the Reliability Graph with General Gates to Analyze the Reliability of Dynamic Systems That Have Various Operation Modes

  • Shin, Seung Ki;No, Young Gyu;Seong, Poong Hyun
    • Nuclear Engineering and Technology
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    • 제48권2호
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    • pp.386-403
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    • 2016
  • The safety of nuclear power plants is analyzed by a probabilistic risk assessment, and the fault tree analysis is the most widely used method for a risk assessment with the event tree analysis. One of the well-known disadvantages of the fault tree is that drawing a fault tree for a complex system is a very cumbersome task. Thus, several graphical modeling methods have been proposed for the convenient and intuitive modeling of complex systems. In this paper, the reliability graph with general gates (RGGG) method, one of the intuitive graphical modeling methods based on Bayesian networks, is improved for the reliability analyses of dynamic systems that have various operation modes with time. A reliability matrix is proposed and it is explained how to utilize the reliability matrix in the RGGG for various cases of operation mode changes. The proposed RGGG with a reliability matrix provides a convenient and intuitive modeling of various operation modes of complex systems, and can also be utilized with dynamic nodes that analyze the failure sequences of subcomponents. The combinatorial use of a reliability matrix with dynamic nodes is illustrated through an application to a shutdown cooling system in a nuclear power plant.

REVIEW OF VARIOUS DYNAMIC MODELING METHODS AND DEVELOPMENT OF AN INTUITIVE MODELING METHOD FOR DYNAMIC SYSTEMS

  • Shin, Seung-Ki;Seong, Poong-Hyun
    • Nuclear Engineering and Technology
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    • 제40권5호
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    • pp.375-386
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    • 2008
  • Conventional static reliability analysis methods are inadequate for modeling dynamic interactions between components of a system. Various techniques such as dynamic fault tree, dynamic Bayesian networks, and dynamic reliability block diagrams have been proposed for modeling dynamic systems based on improvement of the conventional modeling methods. In this paper, we review these methods briefly and introduce dynamic nodes to the existing reliability graph with general gates (RGGG) as an intuitive modeling method to model dynamic systems. For a quantitative analysis, we use a discrete-time method to convert an RGGG to an equivalent Bayesian network and develop a software tool for generation of probability tables.