Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/74578
Title: Response-surface-based Embankment reliability under incomplete probability information
Authors: Wang, F 
Li, H 
Zhang, QL
Keywords: Adaptive relevance vector machine
Copula
Embankment reliability
Incomplete probability information
Rosenblatt transformation
Issue Date: 2017
Publisher: American Society of Civil Engineers
Source: International journal of geomechanics, 2017, v. 17, no. 12, 06017021, p. 2 How to cite?
Journal: International journal of geomechanics 
Abstract: Reliability evaluations can be challenging if the limit-state surface (LSS) is implicit and the probability information is incomplete in that only marginal distributions and correlations are given. To address the problem, this study adopted the response-surface method based on an adaptive relevance vector machine (aRVM) to approximate the implicit LSS, and the copula approach was used to reconstruct the joint distributions based on incomplete probability information. The Rosenblatt transformation was used to transform the random variables from the original random space into the independent standard normal space for the first-/second-order reliability method (FORM/SORM) approximations. Five different copulas-the normal, Frank, Clayton, CClayton, and t copulas-were adopted to represent different dependence structures and examine their impacts on the failure probability. Results from the numerical example show that the copula effect was negligible if the shear strength parameters were uncorrelated or fully correlated. However, when the correlation coefficient was 0.6 or 0.8, the probabilistic result corresponding to the commonly used normal copula was 5.6% higher or 3.1% lower if the CClayton or the Frank copula was used to model the dependence structure, respectively.
URI: http://hdl.handle.net/10397/74578
ISSN: 1532-3641
EISSN: 1943-5622
DOI: 10.1061/(ASCE)GM.1943-5622.0001017
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