CLC number: TU312
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2016-08-23
Cited: 1
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Citations: Bibtex RefMan EndNote GB/T7714
Cao Wang, Quan-wang Li, Long Pang, A-ming Zou. Estimating the time-dependent reliability of aging structures in the presence of incomplete deterioration information[J]. Journal of Zhejiang University Science A, 2016, 17(9): 677-688.
@article{title="Estimating the time-dependent reliability of aging structures in the presence of incomplete deterioration information",
author="Cao Wang, Quan-wang Li, Long Pang, A-ming Zou",
journal="Journal of Zhejiang University Science A",
volume="17",
number="9",
pages="677-688",
year="2016",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1500342"
}
%0 Journal Article
%T Estimating the time-dependent reliability of aging structures in the presence of incomplete deterioration information
%A Cao Wang
%A Quan-wang Li
%A Long Pang
%A A-ming Zou
%J Journal of Zhejiang University SCIENCE A
%V 17
%N 9
%P 677-688
%@ 1673-565X
%D 2016
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1500342
TY - JOUR
T1 - Estimating the time-dependent reliability of aging structures in the presence of incomplete deterioration information
A1 - Cao Wang
A1 - Quan-wang Li
A1 - Long Pang
A1 - A-ming Zou
J0 - Journal of Zhejiang University Science A
VL - 17
IS - 9
SP - 677
EP - 688
%@ 1673-565X
Y1 - 2016
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1500342
Abstract: The performance of an aging structure is commonly evaluated under the framework of reliability analysis, where the uncertainties associated with the structural resistance and loads should be taken into account. In practical engineering, the probability distribution of resistance deterioration is often inaccessible due to the limits of available data, although the statistical parameters such as mean value and standard deviation can be obtained by fitting or empirical judgments. As a result, an error of structural reliability may be introduced when an arbitrary probabilistic distribution is assumed for the resistance deterioration. With this regard, in this paper, the amount of reliability error posed by different choices of deterioration distribution is investigated, and a novel approach is proposed to evaluate the averaged structural reliability under incomplete deterioration information, which does not rely on the probabilistic weight of the candidate deterioration models. The reliability for an illustrative structure is computed parametrically for varying probabilistic models of deterioration and different resistance conditions, through which the reliability associated with different deterioration models is compared, and the application of the proposed method is illustrated.
The manuscript examines the effect of different probabilistic models (uniform, normal, inverse-lognormal, beta and Gamma distributions) of resistance deterioration on structural time-dependent reliability. Three methods (two methods follow the study of Tang et al. 2015) are adopted to evaluate the structural time-dependent reliability under incomplete probability information. The manuscript is beneficial to structural reliability analysis under incomplete probability information.
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