Measuring reliability under epistemic uncertainty:Review on non-probabilistic reliability metrics |
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Affiliation: | 1. School of Reliability and Systems Engineering, Beihang University, Beijing 100083, China;2. Chair on Systems Science and Energy Challenge, Fondation Electricite′ de France EDF, CentraleSupelec, Universite′ Paris-Saclay, Chatenay-Malabry, Paris 92290, France;3. Energy Department, Politecnico di Milano, Milano 20133, Italy |
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Abstract: | In this paper, a systematic review of non-probabilistic reliability metrics is conducted to assist the selection of appropriate reliability metrics to model the influence of epistemic uncertainty. Five frequently used non-probabilistic reliability metrics are critically reviewed, i.e., evidence-theory-based reliability metrics, interval-analysis-based reliability metrics, fuzzy-interval-analysis-based reliability metrics, possibility-theory-based reliability metrics (posbist reliability) and uncertainty-theory-based reliability metrics (belief reliability). It is pointed out that a qualified reli-ability metric that is able to consider the effect of epistemic uncertainty needs to (1) compensate the conservatism in the estimations of the component-level reliability metrics caused by epistemic uncertainty, and (2) satisfy the duality axiom, otherwise it might lead to paradoxical and confusing results in engineering applications. The five commonly used non-probabilistic reliability metrics are compared in terms of these two properties, and the comparison can serve as a basis for the selection of the appropriate reliability metrics. |
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Keywords: | Belief reliability Epistemic uncertainty Evidence theory Interval analysis Possibility theory Probability box Reliability metrics Uncertainty theory |
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