• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.9
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• pp.62-68
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• 2011

Power system needs to sustain high reliability due to its complexity and security. The reliability prediction method is usually based on independent failure. However, in practice, the Common Cause Failures(CCF) and Cascading failure occur to the facilities in power system as well as independent failures in many cases. The CCF and Cascading failure turn out the system collapse seriously in a wide range. Therefore to improve the reliability of the power system practically, it is required that the analysis is conducted by using the CCF and Cascading failure. This paper describes the CCF and Cascading failure modeling combined with independent failure. The incorporated model of independent failure, CCF and cascading failure is proposed and analyzed, and it is applied to the distribution power system in order to examine this method.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.357-367
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• 2021

In general, common cause failures (CCFs) have been modeled with the assumption that components within the same group are symmetric. This assumption reduces the number of parameters required for the CCF probability estimation and allows us to use a parametric model, such as the alpha factor model. Although there are various asymmetric conditions in nuclear power plants (NPPs) to be addressed, the traditional CCF models are limited to symmetric conditions. Therefore, this paper proposes the copulabased CCF model to deal with asymmetric as well as symmetric CCFs. Once a joint distribution between the components is constructed using copulas, the proposed model is able to provide the probability of common cause basic events (CCBEs) by formulating a system of equations without symmetry assumptions. In addition, Bayesian inferences for the parameters of the marginal and copula distributions are introduced and Markov Chain Monte Carlo (MCMC) algorithms are employed to sample from the posterior distribution. Three example cases using simulated data, including asymmetry conditions in total failure probabilities and/or dependencies, are illustrated. Consequently, the copula-based CCF model provides appropriate estimates of CCFs for asymmetric conditions. This paper also discusses the limitations and notes on the proposed method.

• Electronics and Telecommunications Trends
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• v.8 no.3
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• pp.39-52
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• 1993

This study involves a Common Cause Failure (CCF) problem on the ultra-high reliability required system development such as war game operations, nuclear power control, air traffic control, space shuttle missions, and large scale network communication system. The system situation problems are defined according to CCF, reliability and system fault identifications for the development cast verifications in the multi-version redundant software system. Then, CCF analysis of redundant system, system principles and statistical dependence are also described. This validation oh the CCF in the human software interaction system will notify software engineers to conceive what really is CCF contribution factor, not only the internal but the external ones.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.327-334
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• 2017

Common-cause failure (CCF) events can significantly impact the availability of safety systems of nuclear power plants. For this reason, the International Common Cause Data Exchange (ICDE) project was initiated by several countries in 1994. Since 1997 it has been operated within the Organisation for Economic Co-operation and Development (OECD)/Nuclear Energy Agency (NEA) framework and has successfully been operated over six consecutive terms (the current term being 2015-2017). The ICDE project allows multiple countries to collaborate and exchange CCF data to enhance the quality of risk analyses, which include CCF modeling. As CCF events are typically rare, most countries do not experience enough CCF events to perform meaningful analyses. Data combined from several countries, however, have yielded sufficient data for more rigorous analyses. The ICDE project has meanwhile published 11 reports on the collection and analysis of CCF events of specific component types (centrifugal pumps, emergency diesel generators, motor operated valves, safety and relief valves, check valves, circuit breakers, level measurement, control rod drive assemblies, and heat exchangers) and two topical reports. This paper presents recent activities and lessons learnt from the data collection and the results of topical analysis on emergency diesel generator CCF impacting entire exposed population.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.324-327
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• 2001

This paper shows an example of the Design Review and Common-Cause Failure (CCF) Modeling of mechanical Parts. Reliability should be continuously monitored during the entire period of design. Design Review is the procedure to improve the reliability for the product. We proposed the reliability assessment and design review method. CCF Model is the general dependent model considering the failure mode effects several component simultaneously. This study considers the computation of the network with dependent components. It is important that CCF model is applied for mechanical pars.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.10 no.1
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• pp.51-55
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• 2014

Based on the results of Probabilistic Safety Assessment(PSA) for a Nuclear Power Plant (NPP), Common Cause Failure(CCF) events have been recognized as one of the main contributors to the risk. Also, the CCF data and estimation method used in domestic PSA models have been pointed out as an issue with respect to the quality. The existing method of MGL and non-staggered testing even widely used were considered conservative in estimating the safety and had a limited capability in uncertainty analyses. Therefore, this paper presents the CCF estimation using a new generic data source and Alpha factor method. The analyses showed that Alpha factor and staggered method are effective in estimating the CCF contribution and risk insights of reference plant. This method will be a common bases for the optimization of new design for the construction plants as well as for the updating of safety assessment on the operating nuclear power plants.

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.320-328
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• 2011

This research proposes comprehensive models for analyzing common cause failures (CCF) due to cumulative shocks and to assess system reliability under the CCF. The proposed cumulative shock models are based on the binomial failure rate (BFR) model. Six kinds of models are proposed so as to explain diverse cumulative shock phenomena. The models are composed of the initial failure probability, shape parameter, and the total shock number. Some parameters of the proposed models can not be explicitly estimated, so we adopt the Expectation-maximization (EM) algorithm in order to obtain the maximum likelihood estimator (MLE) for the parameters. By estimating the parameters for the cumulative shock models, the system reliability with CCF can be assessed sequentially according to the number of cumulative shocks. The result can be utilizes in dynamic probabilistic safety assessment (PSA), aging studies, or risk management for nuclear power plants. Replacement or maintenance policies can also be developed based on the proposed model.

• IE interfaces
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• v.25 no.4
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• pp.405-415
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• 2012

The reliability performance measures for low and high or continuous demand modes of operation of safety instrumented systems(SISs) are examined and compared by analyzing the official definitions in IEC 61508 standard. This paper also presents a status of common cause factor(CCF) models used in IEC 61508 and problems relating CCF modelling are discussed and ideas to solve these ones are suggested. An example with mixed M-out-of-N architecture is carried out to illustrate the proposed methods.

• International Journal of Reliability and Applications
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• v.11 no.2
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• pp.123-138
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• 2010

This paper investigates a mathematical model of a system composed of two non-identical unit parallel system with common-cause failure, critical human error, non-critical human error, preventive maintenance and two type of repair, i.e. cheaper and costlier. This system goes for preventive maintenance at random epochs. We assume that the failure, repair and maintenance times are independent random variables. The failure rates, repair rates and preventive maintenance rate are constant for each unit. The system is analyzed by using the graphical evaluation and review technique (GERT) to obtain various related measures and we study the effect of the preventive maintenance preventive maintenance on the system performance. Certain important results have been derived as special cases. The plots for the mean time to system failure and the steady-state availability A(${\infty}$) of the system are drawn for different parametric values.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.103-110
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• 2021

In the development of a Risk Monitor probabilistic safety assessment (PSA) model from the basic PSA model of a nuclear power plant, the modeling of common-cause failure (CCF) is very important. At present, some approximate modeling methods are widely used, but there lacks criterion of modeling accuracy and error analysis. In this paper, aiming at ensuring the accuracy of risk assessment and minimizing the Risk Monitor PSA models size, we present three basic issues of CCF model resulted from the changes of a nuclear power plant configuration, put forward corresponding modeling methods, and derive accuracy criteria of CCF modeling based on minimum cut sets and risk indicators according to the requirements of risk monitoring. Finally, a nuclear power plant Risk Monitor PSA model is taken as an example to demonstrate the effectiveness of the proposed modeling method and accuracy criteria, and the application scope of the idea of this paper is also discussed.