Dynamic fault tree analysis using Monte Carlo simulation in probabilistic safety assessment

Rao, K. Durga; Vinod, Gopika; Rao, Vishal Govind; Kushwaha, H.S.; Verma, Ajit Kumar; Srividya, A.

doi:10.1016/j.ress.2008.09.007

Cited by 293 publications

(75 citation statements)

References 16 publications

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“…Most techniques are designed for continuous-time models [70,61] or qualitative analysis [48], but adaptation to single-time models is straightforward. Each component is randomly assigned a failure state based on its failure probability.…”

Section: Monte Carlo Simulationmentioning

confidence: 99%

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Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools

Ruijters

Stoelinga

2015

Computer Science Review

583

368

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Reliability Risk analysis Dynamic Fault Trees Graphical models Dependability evaluation A B S T R A C T Fault tree analysis (FTA) is a very prominent method to analyze the risks related to safety and economically critical assets, like power plants, airplanes, data centers and web shops. FTA methods comprise of a wide variety of modeling and analysis techniques, supported by a wide range of software tools. This paper surveys over 150 papers on fault tree analysis, providing an in-depth overview of the state-of-the-art in FTA. Concretely, we review standard fault trees, as well as extensions such as dynamic FT, repairable FT, and extended FT. For these models, we review both qualitative analysis methods, like cut sets and common cause failures, and quantitative techniques, including a wide variety of stochastic methods to compute failure probabilities. Numerous examples illustrate the various approaches, and tables present a quick overview of results.

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Section: Monte Carlo Simulationmentioning

confidence: 99%

“…In the method by Durga Rao et al [61], random failure times and, if applicable, repair times are generated according to the BE distributions. The system is simulated with these failures, and the system reliability and availability recorded.…”

Section: Reliabilitymentioning

confidence: 99%

Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools

Ruijters

Stoelinga

2015

Computer Science Review

583

368

View full text Add to dashboard Cite

show abstract

“…Specifically, the model is based on three assumptions and two analysis steps. The assumptions describe as events are binary ones, they are statically independent and their relationship are depicted by AND, OR, and Voting gates (Fig.2) [12]. As to the steps, one is qualitative step for expressing the top event and the other is quantitative step for calculating the occurrence of top event [6,12].…”

Section: System Reliability Modeling Toolsmentioning

confidence: 99%

Overview of System Reliability Modeling Tools

Zhao¹,

Lu²,

Zhang³

et al. 2017

Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)

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Abstract. System reliability is a critical aspect of a system, which incurs the proposing of related modeling tools. Tools like Reliability Block Diagrams (RBD) and Fault Tree (FT) provide static representation of system reliability. RBD is a graphical representation that depicts a network of system components and connections. FT is a logical and diagrammatic method to evaluate an accident's probability that results from faults and failure events. The increasing complexity of systems drives the demands for analyzing system dynamic behaviors like dynamics, dependencies, redundancy and load sharing. Dynamic models like Dynamic Reliability Block Diagrams (DRBD) and Dynamic Fault Tree (DFT) are proposed. Dynamic tools define frameworks for modeling dynamic reliability behavior of systems. DRBD is an extending and enhancing of RBD by adding a state-events working mechanism, which permits to model dynamic reliability behaviors of the system. DFT is an extension of FT by adding the sequential notion which can meet time requirements. It is also important to verify these tools for locating and identifying deadlock and faulty states. The efficiency of verification techniques to model these modeling tools and the assessment of dynamic behaviors are taken as evaluation criteria. Based on current research, DRBD performs better than alternatives.

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“…Refaul Ferdous presented a methodology for a fuzzy based computer-aided fault tree analysis tool [7]. K. Durda Rao proposed a dynamic fault tree approach using Monte Carlo simulation in probabilistic safety assessment [8].…”

Section: Abstract-auv; Reliability Analysis; Fault Tree; Monte Carlo mentioning

confidence: 99%

Reliability analysis of an autonomous underwater vehicle using fault tree

Liu

2013

2013 IEEE International Conference on Information and Automation (ICIA)

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Abstract-Reliability is a very important specification for an autonomous underwater vehicle (AUV). The higher reliability can bring the shorter stop-working time and the lower maintenance cost. For a new AUV, reliability needs to be considered in advance during system design stage. This paper proposes a fault tree method for reliability analysis of the 4500m AUV. Firstly a fault tree model and its qualitative analysis are presented to determine the AUV's bottlenecks. Then the reliability is demonstrated by the Monte Carlo simulation. Finally some experiences are discussed to improve the AUV's reliability.

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Dynamic fault tree analysis using Monte Carlo simulation in probabilistic safety assessment

Cited by 293 publications

References 16 publications

Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools

Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools

Overview of System Reliability Modeling Tools

Reliability analysis of an autonomous underwater vehicle using fault tree

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