ON IMPORTANCE MEASURES USED IN COMMON CAUSE FAILURE QUANTIFICATION

1995 ◽  
Vol 02 (02) ◽  
pp. 177-186
Author(s):  
ZHIJIE PAN ◽  
YASUO NONAKA
Keyword(s):  
Sensitivity Analysis ◽  
Quantitative Analysis ◽  
Analysis Framework ◽  
Common Cause ◽  
Common Cause Failure ◽  
Different Types ◽  
Common Cause Failures ◽  
Defence Strategies

In quantitative analysis of common cause failures (CCFs), importance measures for ranking the importance of the CCF events will be significant to limit the CCF analysis framework, find out efficient defence strategies against CCF, and make sensitivity analysis for them. In this paper, three importance measures are defined for different types of common cause failure events: Structure Importance, Probability Importance, and β-Importance. Simplified algorithms for calculating these importance measures are developed.

scholarly journals Reliability and Sensitivity Analysis Method for a Multistate System with Common Cause Failure

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Jinlei Qin ◽  
Zheng Li
Keyword(s):  
Sensitivity Analysis ◽  
System Reliability ◽  
Analysis Method ◽  
Common Cause ◽  
Common Cause Failure ◽  
Resource Limitations ◽  
Multistate System ◽  
Failure State ◽  
Sensitivity Analysis Method ◽  
Reliability Assessments

With the increasing complexity of industrial products and systems, some intermediate states, other than the traditional two states, are often encountered during reliability assessments. A system with more than two states is called a multistate system (MSS) which has already become a general phenomenon in the components and/or systems. Moreover, common cause failure (CCF) often plays a very important role in the assessment of system reliability. A method is proposed to assess the reliability and sensitivity of an MSS with CCF. Some components are not only in a failure state that can cause failure itself, but also in a state that can cause the failure of other components with a certain probability. The components that are affected by one type of CCF make up some sets which can overlap on some components. Using the technology of a universal generating function (UGF), the CCF of a component can be incorporated in the expression of its UGF. Consequently, indices of reliability can be calculated based on the UGF expression of an MSS. Sensitivity analysis can help engineers to judge which type of CCF should be eliminated first under various resource limitations. Examples illustrate and validate this method.

Common cause failure model updating for risk monitoring in nuclear power plants based on alpha factor model

2017 ◽  
Vol 231 (3) ◽  
pp. 209-220 ◽  
Author(s):  
Min Zhang ◽  
Zhijian Zhang ◽  
Ali Mosleh ◽  
Sijuan Chen
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Model Updating ◽  
Factor Model ◽  
Failure Model ◽  
Common Cause ◽  
Common Cause Failure ◽  
Risk Monitoring ◽  
Common Cause Failures ◽  
The Common

Common cause failure model updating (both qualitatively and quantitatively) is a key factor in risk monitoring for nuclear power plants when configuration changes (e.g. components become unavailable) occur among a redundant configuration. This research focuses on the common cause failure updating based on the alpha factor model method, which is commonly used in the living probabilistic safety assessment models for nuclear power plant risk monitoring. This article first discusses the common cause failure model updating in an ideal condition, which evaluates the common cause failure model parameters for the configurationally changed system in different ways, based on the causes of the detected failures. Then, two alternative updating processes are proposed considering the difficulty to identify failure causes immediately during plant operation: one is to update the common cause failure models with the assumption that the failures detected are independent failures and the other is to update the common cause failure models with the parameters as expectations of the values for all possible failure causes. Finally, a case study is given to illustrate the common cause failure updating process and to compare these two alternative processes. The results show that (1) common cause failures can be reevaluated automatically by the methods proposed in this article and (2) the second process is more conservative and reasonable but with more data requirements compared with the first approach. Considering limitations in accessibility of the data, the first strategy is suggested currently. More future work on data acquisition is demanded for better assessment of common cause failures during nuclear power plant risk monitoring.

scholarly journals Representing Common-Cause Failures in the SAPHIRE Software

2008 ◽  
Author(s):  
Curtis Smith
Keyword(s):  
Failure Modes ◽  
Failure Criteria ◽  
Current Version ◽  
Minimal Set ◽  
Common Cause ◽  
Common Cause Failure ◽  
Factors Associated ◽  
Alpha Factor ◽  
Common Cause Failures ◽  
Redundant Component

Currently, the risk analysis software SAPHIRE has implemented a common-cause failure (CCF) module to represent standard CCF methods such as alpha-factor and multiple Greek letter approaches. However, changes to SAPHIRE are required to support the Nuclear Regulatory Commission’s 2007 “Risk Assessment Standardization Project” CCF analysis guidance for events assessment. This guidance provides an outline of how both the nominal CCF probabilities and conditional (e.g., after a redundant component has failed) CCF probabilities should be calculated. Based upon user-provided input and extending the limitations in the current version of SAPHIRE, the CCF module calculations will be made consistent with the new guidance. The CCF modifications will involve changes to (1) the SAPHIRE graphical user interface directing how end-users and modelers interface with PRA models and (2) algorithmic changes as required. Included in the modifications will be the possibility to treat CCF probability adjustments based upon failure types (e.g., independent versus dependent) and failure modes (e.g., failure-to-run versus failure-to-start). In general, SAPHIRE is being modified to allow the risk analyst to define a CCF object. This object is defined in terms of a basic event. For the CCF object, the analyst would need to specify a minimal set of information, including: - The number of redundant components; - The failure criteria (how many component have to fail); - The CCF model type (alpha-factor, MGL, or beta-factor); - The parameters (e.g., the alpha-factors) associated with the model; - Staggered or non-staggered testing assumption; - Default level of detail (expanded, showing all of the specific failure combinations, or not). This paper will outline both the theory behind the probabilistic calculations and the resulting implementation in the SAPHIRE software.

scholarly journals Assessment of the Common Cause Failure(CCFs) effect on Safety Instrumented System(SIS) by usign the Fault Tree Analysis (FTA) method

2020 ◽  
Vol 5 (2) ◽  
pp. 118-129
Author(s):  
Hassina Metatla ◽  
Mounira Rouainia
Keyword(s):  
Factor Model ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
International Electrotechnical Commission ◽  
Tree Analysis ◽  
Common Cause ◽  
Common Cause Failure ◽  
Common Cause Failures ◽  
The Common ◽  
Negative Impacts

The reliability of the safety-instrumented system (SIS) has received a lot of attention during the past decade, with the emergence of the new standards such as International Electrotechnical Commission IEC61508, and IEC61511, that provides a general framework for the design and implementation of these safety barriers. Among the problems influencing on the global SIS reliability: Common Cause Failure (CCF), which contributes too many accidents, that has a negative impacts, so it must be considered in the risk and reliability assessment for these systems. The aim of this work is to focus on the effects of common cause failures (CCFs) on the reliability of a SIS, by implementing a comparative SIS dependability study with and without consideration the CCFs, using the beta factor model, and the fault tree analysis (FTA) method.

A NEW APPROACH FOR RELIABILITY ESTIMATION OF SYSTEMS WITH COMPLEX COMMON CAUSE FAILURES

1994 ◽  
Vol 01 (02) ◽  
pp. 291-298 ◽  
Author(s):  
ZHIJIE PAN ◽  
YASUO NONAKA
Keyword(s):  
Aging Process ◽  
Reliability Estimation ◽  
System Component ◽  
Stress Model ◽  
New Approach ◽  
Common Cause ◽  
Common Cause Failure ◽  
Common Cause Failures ◽  
The Common ◽  
Mutually Independent

This paper presents a new concept, complex common cause failure, for common cause failure analysis. A common stress model is developed, in which the common cause events are described as common stresses that will affect directly and simultaneously on the internal aging process of each system component and further change their failure probabilities, while the internal aging processes of components are still considered mutually independent. The common stress model can be used to estimate the reliability of systems with complex common cause failures.

Is mapping a part of common cause failure quantification?

Kerntechnik ◽  
2006 ◽  
Vol 71 (1-2) ◽  
pp. 41-49 ◽  
Author(s):  
J. K. Vaurio
Keyword(s):  
Common Cause ◽  
Common Cause Failure
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