Event trees analysis based on functional decomposition

Lin, Yan‐Hui; Li, Yan‐Fu; Zio, Enrico

doi:10.1201/b15938-209

Cited by 5 publications

(3 citation statements)

References 22 publications

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“…The proposed approach has been applied to assess the relative trustworthiness of two models (of different complexity and level of detail) used to estimate the failure probability of a residual heat removal (RHR) system of an NPP: a classical Boolean logic-based fault tree (FT) and a multi-state physics-based model (MSPM) [26][27][28] (Lin, 2016). 29 A review of the approaches proposed in the literature to assess the trustworthiness and credibility of a model is presented in section ''Assessing the trustworthiness and credibility of risk assessment models: a critical review of the literature.''…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A hierarchical tree-based decision-making approach for assessing the relative trustworthiness of risk assessment models

Bani-Mustafa

Pedroni

Zio

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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Risk assessment provides information to support decision-making. Then, the confidence that can be put in its outcomes is fundamental, and this depends on the accuracy, representativeness and completeness of the models used in the risk assessment. A quantitative measure is needed to assess the credibility and trustworthiness of the outcomes obtained from such models, for decision-making purposes. This article proposes a four-level, top-down, hierarchical tree to identify the main attributes and criteria that affect the level of trustworthiness of models used in risk assessment. The level of trustworthiness (Level 1) is broken down into two attributes (Level 2), three sub-attributes and one “leaf” attribute (Level 3), and seven basic “leaf” sub-attributes (Level 4). Based on this hierarchical decomposition, a bottom-up, quantitative approach is employed for the assessment of model trustworthiness, using tangible information and data available for the basic “leaf” sub-attributes (Level 4). Analytical hierarchical process is adopted for evaluating and aggregating the sub-attributes, and Dempster–Shafer theory is adopted to consider the uncertainty and the inconsistency in the experts’ judgments. The approach is applied to a case study concerning the modeling of the residual heat removal system of a nuclear power plant, to compute its failure probability. The relative trustworthiness of two mathematical models of different complexity is evaluated: a fault tree and a multi-states physics-based model. The trustworthiness of the multi-states physics-based model is found to outweigh that of the fault tree model, which can be explained by the fact that multi-states physics-based model takes into account the components failure dependency relations and degradation effects. The feasibility and reasonableness of the approach are, thus, demonstrated, paving the way for its potential applicability to inform decision-making on safety-critical systems.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A hierarchical tree-based decision-making approach for assessing the relative trustworthiness of risk assessment models

Bani-Mustafa

Pedroni

Zio

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…The accumulation of life loss is used as a reference to set up maintenance models, but these do not match the extreme shock situation of traction motor insulations. Some researchers also extended the degradation-threshold-shock model of optimal maintenance, which integrated degradation and shock effects and described them with stochastic process models (Wang et al, 2011;Castro, 2013;Lin et al, 2014;Caballé et al, 2015;Castro et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Optimal condition-based maintenance strategy under periodic inspections for traction motor insulations

Zhang

Huang

et al. 2015

J. Zhejiang Univ. Sci. A

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Insulation failure is a crucial failure mode of traction motors. Insulation deteriorates under both fatigue load and shock. This paper focuses on proposing an optimal insulation condition-based maintenance strategy. By combining the information obtained from periodic inspections with historic life information, an integrated model of time-based maintenance and condition-based model is proposed, in which random shocks following Poisson process are also taken into account. In this model we define that insulation has three states: normal state, latent failure state, and functional failure state. Normal state and latent failure state differ in their operating cost, proneness to functional failure, and survival probability under extreme shocks. Preventive maintenance (PM) will be launched if an inspection result exceeds the threshold or if the operating time reaches the critical age. One operating cycle ends as soon as a preventive maintenance or a corrective maintenance is completed. Moreover, an optimization model is established, which takes minimal cost per unit time as the objective, and inspection interval and critical age as the optimization variables. Finally, a numerical example illustrates the analytic results.

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A condition-based maintenance of a dependent degradation-threshold-shock model in a system with multiple degradation processes

Caballé

Castro

Pérez

et al. 2015

Reliability Engineering & System Safety

172

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Event trees analysis based on functional decomposition

Cited by 5 publications

References 22 publications

A hierarchical tree-based decision-making approach for assessing the relative trustworthiness of risk assessment models

A hierarchical tree-based decision-making approach for assessing the relative trustworthiness of risk assessment models

Optimal condition-based maintenance strategy under periodic inspections for traction motor insulations

A condition-based maintenance of a dependent degradation-threshold-shock model in a system with multiple degradation processes

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