A Model-Based Reliability Metric Considering Aleatory and Epistemic Uncertainty
Identifieur interne : 000039 ( France/Analysis ); précédent : 000038; suivant : 000040A Model-Based Reliability Metric Considering Aleatory and Epistemic Uncertainty
Auteurs : Zhiguo Zeng [France] ; Rui Kang [États-Unis] ; Meilin Wen ; Enrico Zio [France]Source :
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Abstract
—Model-based reliability analysis and assessment methods rely on models, which are assumed to be precise, to predict reliability. In practice, however, the precision of the model cannot be guaranteed due to the presence of epistemic uncertainty. In this paper, a new reliability metric, called belief reliability, is defined to explicitly account for epistemic uncertainty in model-based reliability analysis and assessment. A new method is developed to explicitly quantify epistemic uncertainty by measuring the effectiveness of the engineering analysis and assessment activities related to reliability. To evaluate belief reliability, an integrated framework is presented, where the contributions of design margin, aleatory uncertainty and epis-temic uncertainty are integrated to yield a comprehensive and systematic description of reliability. The developed methods are demonstrated by two case studies.
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DOI: 10.1109/ACCESS.2017.2733839
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In practice, however, the precision of the model cannot be guaranteed due to the presence of epistemic uncertainty. In this paper, a new reliability metric, called belief reliability, is defined to explicitly account for epistemic uncertainty in model-based reliability analysis and assessment. A new method is developed to explicitly quantify epistemic uncertainty by measuring the effectiveness of the engineering analysis and assessment activities related to reliability. To evaluate belief reliability, an integrated framework is presented, where the contributions of design margin, aleatory uncertainty and epis-temic uncertainty are integrated to yield a comprehensive and systematic description of reliability. The developed methods are demonstrated by two case studies.</div></front></TEI><affiliations><list><country><li>France</li><li>États-Unis</li></country><region><li>Pennsylvanie</li></region><settlement><li>Pittsburgh</li></settlement><orgName><li>Université de Pittsburgh</li></orgName></list><tree><noCountry><name sortKey="Wen, Meilin" sort="Wen, Meilin" uniqKey="Wen M" first="Meilin" last="Wen">Meilin Wen</name></noCountry><country name="France"><noRegion><name sortKey="Zeng, Zhiguo" sort="Zeng, Zhiguo" uniqKey="Zeng Z" first="Zhiguo" last="Zeng">Zhiguo Zeng</name></noRegion><name sortKey="Zio, Enrico" sort="Zio, Enrico" uniqKey="Zio E" first="Enrico" last="Zio">Enrico Zio</name></country><country name="États-Unis"><region name="Pennsylvanie"><name sortKey="Kang, Rui" sort="Kang, Rui" uniqKey="Kang R" first="Rui" last="Kang">Rui Kang</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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