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A method for ranking components importance in presence of epistemic uncertainties
Importance Measures (IMs) are used to rank the contributions of components or basic events to the system performance, e.g. its reliability or risk. Most times, IMs are calculated without due account of the uncertainties in the model of the behavior of the system. The objective of this work is to inv...
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Published in: | Journal of loss prevention in the process industries 2009-09, Vol.22 (5), p.582-592 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Importance Measures (IMs) are used to rank the contributions of components or basic events to the system performance, e.g. its reliability or risk. Most times, IMs are calculated without due account of the uncertainties in the model of the behavior of the system. The objective of this work is to investigate how uncertainties can influence IMs and to develop a method for giving them due account in the corresponding ranking of the components or basic events. The uncertainties considered in this work affect the model parameters values and are assumed to be described by probability density functions. The method for ranking the contributors to the system performance measure is applied to the auxiliary feedwater system of a nuclear pressurized water reactor. |
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ISSN: | 0950-4230 |
DOI: | 10.1016/j.jlp.2009.02.013 |