![](/images/graphics-bg.png)
Quantification of Margins and Uncertainties Approach for Structure Analysis Based on Evidence Theory
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-06-19
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Abstract EN
Quantification of Margins and Uncertainties (QMU) is a decision-support methodology for complex technical decisions centering on performance thresholds and associated margins for engineering systems.
Uncertainty propagation is a key element in QMU process for structure reliability analysis at the presence of both aleatory uncertainty and epistemic uncertainty.
In order to reduce the computational cost of Monte Carlo method, a mixed uncertainty propagation approach is proposed by integrated Kriging surrogate model under the framework of evidence theory for QMU analysis in this paper.
The approach is demonstrated by a numerical example to show the effectiveness of the mixed uncertainty propagation method.
American Psychological Association (APA)
Xie, Chaoyang& Guijie, Li. 2016. Quantification of Margins and Uncertainties Approach for Structure Analysis Based on Evidence Theory. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-5.
https://search.emarefa.net/detail/BIM-1112453
Modern Language Association (MLA)
Xie, Chaoyang& Guijie, Li. Quantification of Margins and Uncertainties Approach for Structure Analysis Based on Evidence Theory. Mathematical Problems in Engineering No. 2016 (2016), pp.1-5.
https://search.emarefa.net/detail/BIM-1112453
American Medical Association (AMA)
Xie, Chaoyang& Guijie, Li. Quantification of Margins and Uncertainties Approach for Structure Analysis Based on Evidence Theory. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-5.
https://search.emarefa.net/detail/BIM-1112453
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112453