Probabilistic dynamics as a tool for dynamic PSA

Devooght, Jacques; Smidts, Carol

doi:10.1016/0951-8320(95)00135-2

Cited by 50 publications

(16 citation statements)

References 18 publications

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“…As mentioned in Section 1, dynamic reliability aims at complementing the classical methodologies of PSA when the dynamic behaviour of the systems need to be accounted for [9]. With reference to a risky industrial plant such as a nuclear reactor, let us consider an accident initiating event and the sequence of events that it generates.…”

Section: Dynamic Reliabilitymentioning

confidence: 99%

A concept paper on dynamic reliability via Monte Carlo simulation

Marseguerra¹,

Zio²,

Devooght³

et al. 1998

Mathematics and Computers in Simulation

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The methodologies employed in the probabilistic safety assessment (PSA) of hazardous engineering systems have reached a high level of maturity. However, a few issues are still worth of further investigation in order to increase the confidence in the results obtained. In this view, in the past 5±10 years, researchers in the field of reliability have proposed a more`dynamic' approach to PSA with the aim of addressing issues concerning the possible mutual interactions between the hardware system states and the plant physical evolution. Nonetheless, some objections have been raised against such a dynamic approach, especially against its practical complexity and the lack of a clear definition of the domain of its applicability. In this paper, an attempt to define more precisely the field of application for a dynamic approach is propounded on the basis of the concept of accident duration. The qualitative discussion is supported with examples of postulated severe accidents in nuclear power plants like those investigated in level-2 PSA. The application of Monte Carlo simulation as a tool capable, in principle, of handling all the features of dynamic PSA is illustrated. Monte Carlo algorithms are illustrated aiming at improving the stochastic part of the analysis and the deterministic integration as well, so as to allow for a considerable reduction in the computation times. # 1998 Published by IMACS/Elsevier Science B.V.

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Section: Dynamic Reliabilitymentioning

confidence: 99%

A concept paper on dynamic reliability via Monte Carlo simulation

Marseguerra¹,

Zio²,

Devooght³

et al. 1998

Mathematics and Computers in Simulation

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show abstract

“…While the discussion above focuses on Markov modeling, other processes, models, or tools could be used to calculate the probabilities of being in each state throughout time. Many of the existing risk analysis techniques and tools used in the aerospace industry, such as probabilistic risk assessments (PRAs) [3], dynamic PRAs [4][5][6], and phased mission system analysis [7], could be used in place of pure Markov modeling techniques to calculate these probabilities.…”

Section: The Epra Path-dependent Modeling Approachmentioning

confidence: 99%

Expected productivity-based risk analysis in conceptual design

Wertz

Miller

2006

Acta Astronautica

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“…Probabilistic dynamics is also known to put within a common framework different previous attempts at bringing the dynamics into the sequence delineation problem. 5 Up to now and mainly for setpoint transitions, efforts to reinterpret the actual engineering practice in terms of the TPD equations led to confirmation of the approach. 6 However, the studies that were performed 7 indicated…”

Section: Introductionmentioning

confidence: 98%