NDLI: An improved monte carlo method in fault tree analysis

Content Provider	IEEE Xplore Digital Library
Author	Yevkin, O.
Copyright Year	2010
Description	Author affiliation: Dyadem International Ltd, Canada (Yevkin, O.)
Abstract	The Monte Carlo (MC) method is one of the most general ones in system reliability analysis, because it reflects the statistical nature of the problem. It is not restricted by type of failure models of system components, allows to capture the dynamic relationship between events and estimate the accuracy of obtained results by calculating standard error. However, it is rarely used in Fault Tree (FT) software, because a huge number of trials are required to reach a tolerable precision if the value of system probability is relatively small. Regrettably, this is the most important practical case, because nowadays highly reliable systems are ubiquitous. In the present paper we study several enhancements of the raw simulation method: variance reduction, parallel computing, and improvements based on simple preliminary information about FT structure. They are efficiently developed both for static and dynamic FTs. The effectiveness and accuracy of the improved MC method is confirmed by numerous calculations of complex industrial benchmarks.
Starting Page	1
Ending Page	5
File Size	219432
Page Count	5
File Format	PDF
ISBN	9781424451029
ISSN	0149144X
DOI	10.1109/RAMS.2010.5447989
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-01-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault trees Probability Analysis of variance Computational modeling Random number generation Equations Monte Carlo methods Reliability Parallel processing Analytical models variance reduction Monte Carlo method fault tree
Content Type	Text
Resource Type	Article

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