Development and application of a living probabilistic safety assessment tool: Multi-objective multi-dimensional optimization of surveillance requirements in NPPs considering their ageing

Kančev, Duško; Čepin, Marko; Gjorgiev, Blazhe

doi:10.1016/j.ress.2014.06.009

Cited by 17 publications

(7 citation statements)

References 54 publications

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“…Thus, in Eqs. (6) and 7A Next, the degradation function can be formulated for the time immediately before and after the second maintenance activity, arriving at chronological time t 2 as follows:…”

Section: Addressing Maintenance Effectivenessmentioning

confidence: 99%

See 1 more Smart Citation

Unavailability model for demand-caused failures of safety components addressing degradation by demand-induced stress, maintenance effectiveness and test efficiency

Martorell

Martón

Sánchez

et al. 2017

Reliability Engineering & System Safety

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Section: Addressing Maintenance Effectivenessmentioning

confidence: 99%

“…The degradation function immediately before and after the first maintenance activity is given by Eqs. (6) and 7, respectively. Next, ( ) for the time immediately before and after performing the second maintenance activity, named and respectively, can be formulated as follows:…”

Section: Addressing Maintenance Effectivenessmentioning

confidence: 99%

Unavailability model for demand-caused failures of safety components addressing degradation by demand-induced stress, maintenance effectiveness and test efficiency

Martorell

Martón

Sánchez

et al. 2017

Reliability Engineering & System Safety

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show abstract

“…Furthermore, each probability of top event is determined by using fault tree analysis. Data of component failure is adopted AP1000 data which was published and IAEA generic data [8][9][10][11][12]. Finally, the total probability of event sequences are calculated.…”

Section: Kne Energymentioning

confidence: 99%

“…The analysis is done by using event tree and each probability of top event is calculated by using fault tree analysis. Failure rate of component used in calculation is based on AP1000 data that is published by Westinghouse and data from IAEA Tecdoc [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Sequence Analysis After Core Damage To Determine Safety Level Of The Ap1000

Tjahyani¹

2016

KEn

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In safety analysis, one of important parameters is core damage as this occasion can cause fission products to release. In that regard, all possible sequences afterward must be analyzed in order to ensure that all events have been considered, because each sequence has different consequence. The objective of this research is to determine the probability of event sequences after core damage so safety level of AP1000 could be known. The AP1000 reactor is chosen as the research object because currently many units are under construction. In this research the accident sequences were analyzed by using event tree, and the probability of top event was calculated by fault tree analysis. Meanwhile, the failure rates of component or operator action were collected from IAEA documents and also published documents of the AP1000 from Westinghouse Inc. The analysis results show that probability of event sequences which causes fission product release is ranging from 10 -2 to 10 -26 and the total probability is 3, 48 x 10 -2. Based on this analysis, it can be concluded that the AP1000 has high safety level because the probability of event sequences leading to fission product release is small. Moreover, if these results are joined with core damage probability then probability of fission product release would be less than 10 -9.

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“…21,22 There are also cases where improvement is represented according to a normal distribution. 23 For systems or components with hidden failures, many models consider a constant improvement factor, [24][25][26][27][28][29][30][31] while other improvement factors are less frequent such as the random improvement factor 32 and the CI factor. 33,34 The continuous improvement of processes and activities, in general, is one of the main objectives of managers.…”

Section: Introductionmentioning

confidence: 99%

Continuous improvement of imperfect maintenance actions in PAS and PAR models

Barros

Lopes

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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In this paper, an unavailability model is proposed to define the test and maintenance policies of systems that are subject to hidden failure and degradation, assuming practices of continuous improvement (CI) under imperfect maintenance actions with Proportional Age Setback (PAS) and Proportional Age Reduction (PAR). For this, two CI equations are analyzed to estimate the progress of maintenance effectiveness over time, and a maximum unavailability constraint is incorporated into the model for evaluation of safety point of view. A numerical application was performed, and the results showed that by adopting CI practices over maintenance actions, the unavailability of the system is reduced in greater proportion over time, besides contributing positively to safety.

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Development and application of a living probabilistic safety assessment tool: Multi-objective multi-dimensional optimization of surveillance requirements in NPPs considering their ageing

Cited by 17 publications

References 54 publications

Unavailability model for demand-caused failures of safety components addressing degradation by demand-induced stress, maintenance effectiveness and test efficiency

Unavailability model for demand-caused failures of safety components addressing degradation by demand-induced stress, maintenance effectiveness and test efficiency

Sequence Analysis After Core Damage To Determine Safety Level Of The Ap1000

Continuous improvement of imperfect maintenance actions in PAS and PAR models

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