DocumentCode
1345839
Title
Dagger-Sampling Monte Carlo For System Unavailability Evaluation
Author
Kumamoto, Hiromitsu ; Tanaka, Kazuo ; Inoue, Koichi ; Henley, Ernest J.
Author_Institution
Dept. of Precision Mech.; Faculty of Engr.; Kyoto University; Kyoto 606 JAPAN.
Issue
2
fYear
1980
fDate
6/1/1980 12:00:00 AM
Firstpage
122
Lastpage
125
Abstract
Reliability problems usually result in rare-event simulations, and hence direct Monte Carlo methods are extremely wasteful of computer time. This paper presents a new application of ``dagger-sampling´´, for calculating the system unavailability of a large complicated system represented by a coherent fault tree. Since a small number of uniform random numbers generate a number of trials, dagger-sampling appreciably reduces computation time, and hence a large number of trials become possible for the rare-event problems. Further, dagger-sampling decreases the variance of the Monte Carlo estimator because it generates negatively correlated samples.
Keywords
Boolean algebra; Computational modeling; Discrete event simulation; Fault trees; Monte Carlo methods; Reliability theory; Sampling methods; State estimation; Statistical analysis; Statistics; Antithetic variates; Monte Carlo method; Rare-event simulations; System unavailability;
fLanguage
English
Journal_Title
Reliability, IEEE Transactions on
Publisher
ieee
ISSN
0018-9529
Type
jour
DOI
10.1109/TR.1980.5220749
Filename
5220749
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