Common cause failure analysis of PWR containment spray system by GO-FLOW methodology

Muhammad, Hashim; Yoshikawa, Hidekazu; Matsuoka, Toshifumi; Yang, Ming

doi:10.1016/j.nucengdes.2013.04.028

Cited by 23 publications

(12 citation statements)

References 2 publications

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“…(2) Alternations and updates to a GO-FLOW chart are readily accomplished. (3) GO-FLOW contains all the possible system operational states.…”

Section: Go-flow Methodologymentioning

confidence: 99%

“…The modeling technique produces a chart which consists of signal lines and operators, and represents engineering function of the components/subsystems/system. Moreover, it is able to model and analyze complex systems which contain multi-state under different functional scenario [2]. Now, some software and approaches are able to support the calculation of GO-FLOW methodology.…”

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confidence: 99%

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An approach based on Bayesian networks for GO-FLOW methodology

Fan

Ren

Liu

et al. 2016

2016 Annual Reliability and Maintainability Symposium (RAMS)

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The GO-FLOW methodology is a reliability analysis methodology [1]. It is success-oriented system analysis technique and is capable of evaluating system reliability and availability of system with complex time-sequence problems and phased mission problems. The modeling technique produces a chart which consists of signal lines and operators, and represents engineering function of the components/subsystems/system. Moreover, it is able to model and analyze complex systems which contain multi-state under different functional scenario [2]. Now, some software and approaches are able to support the calculation of GO-FLOW methodology. However, the traditional modeling methods are no longer appropriate to calculate the complicated and time-sequence models. For example, (i) traditional approach initially assumes that the signals are independent to each other. However, the necessary consideration of multiple shared signals demands recalculation the model;(ii) if each states of operators are restricted to binary values, i.e. success and fail, the system that contains 100 operators may expand to 2 100 status combinations. It would bring much pressure on the computing system;(iii) it needs to be calculated for each time interval based on the traditional probabilistic approach. Because of the restrictions above, the GO-FLOW methodology is kept from being widely used.Aiming at the restrictions, an approach based on Bayesian networks is proposed in this paper. The proposed method calculates the reliability of system by simultaneously considering:(i) time-sequence and multi-states problems;(ii) multiple shared signals; (iii) the efficiency and applicability of the approach. The rest of this paper is organized as follows: Section 1 presents the brief description of the Bayesian networks and GO-FLOW methodology. Section 2 gives a detail mapping rules from operators into Bayesian network (BN). Lastly, application case study is descripted in Section 3 demonstrates the effectiveness of the proposed method and Section 4 concludes the paper and discusses some future work.

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“…(2) Alternations and updates to a GO-FLOW chart are readily accomplished. (3) GO-FLOW contains all the possible system operational states.…”

Section: Go-flow Methodologymentioning

confidence: 99%

mentioning

confidence: 99%

An approach based on Bayesian networks for GO-FLOW methodology

Fan

Ren

Liu

et al. 2016

2016 Annual Reliability and Maintainability Symposium (RAMS)

View full text Add to dashboard Cite

show abstract

“…Muhammad et al [22] performed reliability evaluation with GO-FLOW method to determinate the influence of automatic depressurization system in dynamic reliability of passive core cooling system of AP1000. Common cause failure issues in the reliability analysis and the procedure of analysis has been treated by GO-FLOW method [23,24]. The GO-FLOW method is a success-oriented system analysis technique and capable of evaluating system reliability and risk [18].…”

Section: Introductionmentioning

confidence: 99%

Reliability evaluation of auxiliary feedwater system by mapping GO-FLOW models into Bayesian networks

Liu

et al. 2016

ISA Transactions

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“…Using the formulas, the probability of each operator can be directly calculated and it is unnecessary to calculate the joint probabilities. Representative research efforts on the GO-FLOW approach are reported in references Kobayashi (1988, 1989) Zupei et al (2001), Hashim et al (2013), Muhammad et al (2013). Among these works, the reliability is mainly calculated based on the simulation approach (Matsuoka and Kobayashi, 1989;Hashim et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…In a recent study, CCF has been regarded as a crucial problem . However, the approach in Muhammad et al (2013) must be calculated for each time interval, and the CCF also requires additional consideration. The complicated parts of the current approach make it unavailable for use in methodology calculations.…”

Section: Introductionmentioning

confidence: 99%