A new method for explicit modelling of single failure event within different common cause failure groups

Kančev, Duško; Čepin, Marko

doi:10.1016/j.ress.2012.03.009

Cited by 37 publications

(17 citation statements)

References 16 publications

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“…The failure data analysis based on probability theory and plant specific data (although some generic data can be used in the absence of this) for the support of quantitative accident frequency evaluation and systems reliability evaluation 12,13 ; The fault tree analysis, including its semi-dynamic upgrades for the system reliability evaluation [14][15][16][17] ; The event tree analysis for scenario modelling and for accident sequence analysis, and consequently for the accident frequency evaluation, which is performed qualitatively and quantitatively 18,19 ; The common cause analysis for improving the assumptions about the independence of component failures and component failure modes 20,21 ; The human reliability analysis for consideration of the operator actions within the system models, and the system interactions within the accident sequence analysis.…”

Section: Methodsmentioning

confidence: 99%

The extended living probabilistic safety assessment

Čepin

2019

Proceedings of the Institution of Mechanical Engineers, Part O:

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The term living probabilistic safety assessment was defined soon after the initial probabilistic safety assessments were implemented. The objective of this article is to present the extended living probabilistic safety assessment and its applications considering realistic nuclear power plant models, including the low power and shutdown plant operating states. One of the key objectives is to compare the suitability of conventional and additional risk measures, core damage frequency and conditional core damage frequency, respectively. The methods are presented considering all states of the plant from the full power operation to the low power and shutdown states. The example models of the nuclear power plants and the results of the living probabilistic safety assessment of the plant operating states are discussed. The results show that the risk of low power and shutdown states is generally smaller than the risk of full power operation, but the low power and shutdown plant operating states differ significantly among each other regarding the risk level. The deficiency of living probabilistic safety assessment applied to the plant shutdown states is connected with significantly increased human effort for the analyses, with a significantly greater amount of results and with increased uncertainty of some parameters due to the larger dynamics of actions in the plant shutdown versus the full power operation states. The benefit of the living probabilistic safety assessment applied to the plant low power and shutdown states lays in consideration of all states and potential identification of risk significant states and directions for possible safety improvements.

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Section: Methodsmentioning

confidence: 99%

The extended living probabilistic safety assessment

Čepin

2019

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…Kaufrnan et al (2000) proposed a method on Digital Embedded Systems with CCF; and Mitra et al (2000) made a survey on CCF in redundant VLSI system; Bukowski and Goble (2001) made remarkable work on verifying CCF reduction rules for fault tolerant systems. In some recently research, Kancev and Cepin (2012) proposed a new method for explicit modelling of single failure event within different common cause failure groups; and Bricman Rejc and Cepin (2014) made an extension of multiple Greek letter method for common cause failures modelling. In general, CCFs have been discussed extensively in publications related to the safety and reliability of nuclear reactors and power supply systems.…”

Section: Common Cause Failurementioning

confidence: 99%

A modified GO-FLOW methodology with common cause failure based on Discrete Time Bayesian Network

Fan

Wang

Liu

et al. 2016

Nuclear Engineering and Design

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“…Therefore, it is highly crucial to identify and consider dependent failures in the evaluation of reliability and MTBF of systems. Common cause failure (CCF) is one of the most important dependent failures in redundant systems, in which an intrinsic factor leads to the propagation of failure in all components, resulting in the simultaneous failure of components in the redundant system (Kančev and Č epin 2012). Failing to incorporate CCF into MTBF of redundant systems leads to irreversible damage.…”

Section: Introductionmentioning

confidence: 99%

MTBF evaluation for 2-out-of-3 redundant repairable systems with common cause and cascade failures considering fuzzy rates for failures and repair: a case study of a centrifugal water pumping system

2017

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In many cases, redundant systems are beset by both independent and dependent failures. Ignoring dependent variables in MTBF evaluation of redundant systems hastens the occurrence of failure, causing it to take place before the expected time, hence decreasing safety and creating irreversible damages. Common cause failure (CCF) and cascading failure are two varieties of dependent failures, both leading to a considerable decrease in the MTBF of redundant systems. In this paper, the alpha-factor model and the capacity flow model are combined so as to incorporate CCF and cascading failure in the evaluation of MTBF of a 2-out-of-3 repairable redundant system. Then, using a transposed matrix, the MTBF function of the system is determined. Due to the fact that it is difficult to estimate the independent and dependent failure rates, industries are interested in considering uncertain failure rates. Therefore, fuzzy theory is used to incorporate uncertainty into the model presented in this study, and a nonlinear programming model is used to determine system's MTBF. Finally, in order to validate the proposed model, evaluation of MTBF of the redundant system of a centrifugal water pumping system is presented as a practical example.

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A new method for explicit modelling of single failure event within different common cause failure groups

Cited by 37 publications

References 16 publications

The extended living probabilistic safety assessment

The extended living probabilistic safety assessment

A modified GO-FLOW methodology with common cause failure based on Discrete Time Bayesian Network

MTBF evaluation for 2-out-of-3 redundant repairable systems with common cause and cascade failures considering fuzzy rates for failures and repair: a case study of a centrifugal water pumping system

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