Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 710-721 |
| Seitenumfang | 12 |
| Fachzeitschrift | Applied Mathematical Modelling |
| Jahrgang | 54 |
| Frühes Online-Datum | 26 Okt. 2017 |
| Publikationsstatus | Veröffentlicht - Feb. 2018 |
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.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Modellierung und Simulation
- Mathematik (insg.)
- Angewandte Mathematik
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in: Applied Mathematical Modelling, Jahrgang 54, 02.2018, S. 710-721.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Do we have enough data?
T2 - Robust reliability via uncertainty quantification
AU - Rocchetta, Roberto
AU - Broggi, Matteo
AU - Patelli, Edoardo
N1 - Publisher Copyright: © 2017 Elsevier Inc. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2018/2
Y1 - 2018/2
N2 - 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.
AB - 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.
KW - Computational tool
KW - Dempster–Shafer
KW - Information quality
KW - Probability boxes
KW - Reliability
KW - Uncertainty quantification
UR - http://www.scopus.com/inward/record.url?scp=85037809995&partnerID=8YFLogxK
U2 - 10.15488/10761
DO - 10.15488/10761
M3 - Article
AN - SCOPUS:85037809995
VL - 54
SP - 710
EP - 721
JO - Applied Mathematical Modelling
JF - Applied Mathematical Modelling
SN - 0307-904X
ER -