Failure record discounting in Bayesian analysis in Probabilistic Risk Assessment (PRA) : a space system application
Name
71441092-MIT.pdf
Description
Full printable version
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715.46 KB
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ddac62661e32cb93ae4bf63df33a3c8c
Author(s)
Lekkakos, Spyridon-Damianos
Advisor(s)
George E. Apostolakis.
Date Issued
2006
Publisher
Massachusetts Institute of Technology
Abstract
In estimating a system-specific binomial probability of failure on demand in Probabilistic Risk Assessment (PRA), the corresponding number of observed failures may be not directly applicable due to design or procedure changes that have been implemented in the system as a result of past failures. A methodology has been developed by NASA to account for partial applicability of past failures in Bayesian analysis by discounting the failure records. A series of sensitivity analyses on a specific case study showed that failure record discounting may result in failure distributions that are both optimistic and narrow. An alternative approach, which builds upon NASA's method, is proposed. This method combines an optimistic interpretation of the data, obtained with failure record discounting, with a pessimistic one, obtained with standard Bayesian updating without discounting, in a linear pooling fashion. The interpretation of the results in the proposed approach is done in such way that it displays the epistemic uncertainties that are inherent in the data and provides a better basis for the decision maker to make a decision based on his / her risk attitude. A comparison of the two methods is made based on the case study.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2006.
Includes bibliographical references (p. 83-85).
Subjects
System Design and Management Program.
MIT Department
System Design and Management Program.
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