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Closed Form Solution
Continuous Time
Dynamic System
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A continuous-time Bayesian network reliability modeling, and analysis framework
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A continuous-time Bayesian network reliability modeling, and analysis framework
(
Citations: 27
)
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Hichem Boudali
,
Joanne Bechta Dugan
We present a continuous-time
Bayesian network
(CTBN) framework for dynamic systems
reliability modeling
and analysis. Dynamic systems exhibit complex behaviors and interac- tions between their components; where not only the combination of failure events matters, but so does the sequence ordering of the failures. Similar to dynamic fault trees, the CTBN framework defines a set of 'basic' BN constructs that capture well-defined system components' behaviors and interactions. Combining, in a structured way, the various 'basic'
Bayesian network
constructs enables the user to construct, in a modular and hierarchical fashion, the system model. Within the CTBN framework, one can perform various analyses, including reliability, sensitivity, and uncertainty analyses. All the analyses allow the user to obtain closed-form solutions.
Journal:
IEEE Transactions on Reliability - TR
, vol. 55, no. 1, pp. 86-97, 2006
DOI:
10.1109/TR.2005.859228
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Citation Context
(14)
...Moreover, the versatility of BNs is becoming increasingly recognised in not only the field of reliability (see, for example, [
5
]‐[9]), but also many other disciplines (e.g., the modeling of genetics [10], and the modeling of financial systems [11])...
...Finally, possible extensions are to consider the use of continuous-time Bayesian networks (CTBNs) for modeling system dependencies (see, e.g., [
5
]), and to incorporate a cost for data collection that could then be included in the formal decision problem...
Ben Flood
,
et al.
A probability model of system downtime with implications for optimal w...
...Therefore, how to determine the network reliability is an important research topic [1]‐[
29
]...
...target nodes). According to whether the flow conservation law is satisfied, there are two categoriesofmultistatenetworkreliabilityproblems:themultistate flow network (MFN) [1]‐[14], [22]‐[
29
], and the multistate information network (MIN) [15]‐[21]...
...It is also useful for guiding the approximated-solution methods in finding optimal or good-quality solutions to larger problems [28], [
29
]...
Wei-Chang Yeh
,
et al.
A New Universal Generating Function Method for Estimating the Novel Mu...
...Valid approaches that converting the Markov models into differential equations in DFT analysis are represented by Petri nets [6-8] , Bayesian networks [
9-12
] ,a nd Monte...
Xiao-feng Liang
,
et al.
Numerical simulation to reliability analysis of fault-tolerant repaira...
...Recently, some papers deal with the link between the new modeling techniques as dynamic fault trees and BNs, for example the articles written by
Boudali & Dugan (2005a, 2006)
...
G. Medina Oliva
,
et al.
Bayesian networks Applications on Dependability, Risk Analysis and Mai...
...Many methods have been developed for the evaluation of static fault trees, such as Binary Decision Diagram(BDD)[1, 2], Prime Implication(PI)[3], Monte carol [4, 5], Bayesian networks[6,
7
]...
Xiaofeng Liang
,
et al.
A numerical simulation approach for reliability analysis of fault-tole...
References
(19)
The Galileo Fault Tree Analysis Tool
(
Citations: 74
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Citations
(27)
Cloud-point measurements of the {H 2O + poly(ethylene glycol) + NaNO 3} system
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(
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Approximation algorithm for evaluating time-to-failure distribution of k-out-of- n system with shared standby elements
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Reliability Engineering & System Safety - RELIAB ENG SYST SAFETY
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A probability model of system downtime with implications for optimal warranty design
Ben Flood
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Journal:
Quality and Reliability Engineering International
, vol. 26, no. 1, pp. 83-96, 2010