The Process-Oriented Simulation (POS) model for common cause failures: recent progress

Berg, H. P.; Görtz, R.; Schimetschka, E.; Kesten, Joanna M

doi:10.3139/124.100275

“…The Process Oriented Simulation Model (POS) described in [5], [6] has been selected to carry out a first analytical approach to complete CCFs. The basic idea in the POS modelling approach is to assume some kind of CC impact which, at a given point in time, affects all or a specified subset of the components belonging to the same common cause component group (CCCG).…”

Section: The Process-oriented Simulation Model (Pos)mentioning

confidence: 99%

“…Equation (5) reflects that in the system of size r + 1 that a cause can only be shared by m components, if in the subsystem of size r either m or m-1 components are affected. Equations ( 2) and ( 4) are in analogy to (5). The recursive scheme extends to higher degrees of redundancy.…”

Section: The Process-oriented Simulation Model (Pos)mentioning

confidence: 99%

ICDE-results on complete common cause failures in the light of results obtained with the POS model

Berg¹,

Fröhmel²,

Görtz³

et al. 2006

Kerntechnik

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Since April 1998, the OECD Nuclear Energy Agency (NEA) is operating the International Common Cause Data Exchange (ICDE) project. The objectives of this exchange comprise, to collect and analyze CCF events, to generate insights into root causes and derive preventing approaches, to strengthen experience feedback and, last but not least, to facilitate quantification. For a large number of about 1000ICDE events the fractions of complete CCFs have been displayed as a function of the degree of redundancy. Complete CCFs are relevant to PSA as in these cases the respective function fails and in many cases significant contributions to core damage can be expected. From the point of view of quantitative CCF modeling, the theoretical theoretical approach to of the empirically available complete CCF fractions represents a major challenge. The large number of events have been collected in the ICDE project for nine different types of components in nuclear power plants from ten different countries. Obviously, these components are operated under different conditions and technical specifications. Therefore, an approach is chosen which is based on low information distributions of the model parameters to account for the large variation throughout the component populations. The Process Oriented Simulation Model (POS) has been selected to carry out an analysis of complete CCFs. The consistency between the theoretical approach – considering its simplicity – and the data observed is satisfactory.

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Common Cause Failure Modeling

Vaurio

¹

2008

Encyclopedia of Quantitative Risk Analysis and Assessment

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Modeling and quantification of simultaneous failures of multiple components due to common causes is a frequent and often crucial task in safety system reliability and risk assessments. Several models of common cause failures (CCF) are introduced. Their mutual relationships, limitations, and advantages, as well as sources of parametric values, are described. The models are presented in terms of basic multiple‐failure rates and probabilities that are independent of system testing schemes and intervals, and have direct connection to the basic event probabilities needed in system logic models. The early CCF models such as the β factor, binomial failure rate, common load, and distributed failure probability models are all special cases of stochastic reliability analysis. Even if mathematically attractive, these models are inherently constrained by certain mutual couplings between the CCF rates or CCF probabilities. More general α factor and multiple Greek letter models are based on the ratios of multiple‐failure rates or probabilities. In applications, both models need some additional failure rate from outside of the model to yield CCF rates and basic event probabilities. Extensive national and international common cause failure data collection efforts are making it feasible to estimate plant‐specific multiple‐failure rates and probabilities by combining data from many similar systems with empirically oriented Bayesian methods without assuming common generic parametric values. This methodology is briefly described. It takes into account both statistical and assessment uncertainties due to limited observations, interpretations, and documentation of CCF events.

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Common Cause Failure Modeling

Vaurio

¹

2014

Wiley StatsRef: Statistics Reference Online

0

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Modeling and quantification of simultaneous failures of multiple components due to common causes is a frequent and often crucial task in safety system reliability and risk assessments. Several models of common cause failures (CCF) are introduced. Their mutual relationships, limitations, and advantages, as well as sources of parametric values, are described. The models are presented in terms of basic multiple‐failure rates and probabilities that are independent of system testing schemes and intervals, and have direct connection to the basic event probabilities needed in system logic models. The early CCF models such as the β factor, binomial failure rate, common load, and distributed failure probability models are all special cases of stochastic reliability analysis. Even if mathematically attractive, these models are inherently constrained by certain mutual couplings between the CCF rates or CCF probabilities. More general α factor and multiple Greek letter models are based on the ratios of multiple‐failure rates or probabilities. In applications, both models need some additional failure rate from outside of the model to yield CCF rates and basic event probabilities. Extensive national and international common cause failure data collection efforts are making it feasible to estimate plant‐specific multiple‐failure rates and probabilities by combining data from many similar systems with empirically oriented Bayesian methods without assuming common generic parametric values. This methodology is briefly described. It takes into account both statistical and assessment uncertainties due to limited observations, interpretations, and documentation of CCF events.

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The Process-Oriented Simulation (POS) model for common cause failures: recent progress

Cited by 4 publications

References 1 publication

ICDE-results on complete common cause failures in the light of results obtained with the POS model

ICDE-results on complete common cause failures in the light of results obtained with the POS model

Common Cause Failure Modeling

Common Cause Failure Modeling

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