Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76456
Title: Towards reliability evaluation involving correlated multivariates under incomplete probability information : a reconstructed joint probability distribution for isoprobabilistic transformation
Authors: Wang, F 
Li, H 
Keywords: Incomplete probability information
Correlated multivariates
Pair-copulas
Rosenblatt's transformation
Reliability
Issue Date: 2017
Publisher: Elsevier
Source: Structural safety, 2017, v. 69, p. 1-10 How to cite?
Journal: Structural safety 
Abstract: Reliability evaluation under incomplete probability information (prescribed marginal distributions and correlation coefficients) is a challenging task. The widely used Nataf transformation inherently assumes a normal copula for dependence modeling, which can be inappropriate in some cases. This paper aims to provide a more general isoprobabilistic transformation method for reliability evaluations under incomplete probability information. To this end, the joint probability distribution is represented using the pair-copula decomposition approach, which is highly flexible in dependence modeling. The desired pair-copula parameters are retrieved from the incomplete probability information by a simulation based method. Finally, based on the reconstructed joint probability distribution, the Rosenblatt's transformation is adopted for the subsequent reliability evaluation. The proposed method is illustrated in a tunnel excavation reliability problem. Several dependence structures characterized by different pair copulas are investigated to provide insights into the effect of copula selection on reliability results.
URI: http://hdl.handle.net/10397/76456
ISSN: 0167-4730
EISSN: 1879-3355
DOI: 10.1016/j.strusafe.2017.07.002
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

2
Citations as of May 12, 2018

WEB OF SCIENCETM
Citations

1
Last Week
0
Last month
Citations as of May 20, 2018

Page view(s)

3
Citations as of May 21, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.