Do we have enough data? Robust reliability via uncertainty quantification

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Rochetty, R.; Broggi, M.; Patelli, E.: Do we have enough data? Robust reliability via uncertainty quantification. In: Applied Mathematical Modelling 54 (2018), S. 710-721. DOI:

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Sum total of downloads: 71

A generalised probabilistic framework is proposed for reliability assessment and uncertainty quantification under a lack of data. The developed computational tool allows the effect of epistemic uncertainty to be quantified and has been applied to assess the reliability of an electronic circuit and a power transmission network. The strength and weakness of the proposed approach are illustrated by comparison to traditional probabilistic approaches. In the presence of both aleatory and epistemic uncertainty, classic probabilistic approaches may lead to misleading conclusions and a false sense of confidence which may not fully represent the quality of the available information. In contrast, generalised probabilistic approaches are versatile and powerful when linked to a computational tool that permits their applicability to realistic engineering problems.
License of this version: CC BY-NC-ND 4.0 Unported
Document Type: Article
Publishing status: submittedVersion
Issue Date: 2018
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
total perc.
1 image of flag of Germany Germany 30 42.25%
2 image of flag of United States United States 14 19.72%
3 image of flag of China China 6 8.45%
4 image of flag of No geo information available No geo information available 4 5.63%
5 image of flag of Vietnam Vietnam 2 2.82%
6 image of flag of Russian Federation Russian Federation 2 2.82%
7 image of flag of Italy Italy 2 2.82%
8 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 2 2.82%
9 image of flag of United Kingdom United Kingdom 2 2.82%
10 image of flag of Malaysia Malaysia 1 1.41%
    other countries 6 8.45%

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