Do we have enough data? Robust reliability via uncertainty quantification

Rocchetta, Roberto ORCID: 0000-0002-8117-8737, Broggi, Matteo and Patelli, Edoardo ORCID: 0000-0002-5007-7247 (2018) Do we have enough data? Robust reliability via uncertainty quantification. APPLIED MATHEMATICAL MODELLING, 54. pp. 710-721.

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Abstract

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.

Item Type:	Article
Additional Information:	publisher: Elsevier articletitle: Do we have enough data? Robust reliability via uncertainty quantification journaltitle: Applied Mathematical Modelling articlelink: http://dx.doi.org/10.1016/j.apm.2017.10.020 content_type: article copyright: © 2017 Elsevier Inc. All rights reserved.
Uncontrolled Keywords:	Uncertainty quantification, Information quality, Probability boxes, Dempster-Shafer, Computational tool, Reliability
Depositing User:	Symplectic Admin
Date Deposited:	09 Jan 2018 09:25
Last Modified:	19 Jan 2023 06:46
DOI:	10.1016/j.apm.2017.10.020
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3014888