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Erschienen in: Bulletin of Engineering Geology and the Environment 5/2020

11.01.2020 | Original Paper

Copula-based approach coupling information diffusion distribution for slope reliability analysis

verfasst von: Xinlong Zhou, Guang Zhang, Shaohua Hu, Junzhe Li, Dequan Xuan, Chang Lv

Erschienen in: Bulletin of Engineering Geology and the Environment | Ausgabe 5/2020

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Abstract

Uncertain probability distributions and interdependencies of geotechnical parameters have profound impacts on slope reliability analysis, especially under incomplete probabilistic information. In this paper, a copula-based approach coupling information diffusion (ID) distribution is proposed to reduce such uncertainties. Firstly, ID theory is introduced to establish marginal distribution of strength parameter. Copulas are subsequently performed to characterize the corresponding dependence structure and link the proposed ID margins. At last, equivalent samples are simulated and plugged into Monte Carlo simulation (MCS) to estimate slope reliability. The effect of the proposed method is validated by a slope case. Results show that the proposed ID algorithm holds remarkable superiority in estimating the marginal distribution with considering random volatility of geotechnical parameter. For slope reliability, both marginal distributions and interdependencies of geotechnical parameters barely affect the factor of safety (FS) but significantly impact failure probability (pf). Unreasonable estimation of probability distribution may lead to large deviation in calculation of slope failure probability. Comparably, the proposed copula-based approach coupling ID distribution can give a reasonable and robust reliability results with considering random volatility.

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Metadaten
Titel
Copula-based approach coupling information diffusion distribution for slope reliability analysis
verfasst von
Xinlong Zhou
Guang Zhang
Shaohua Hu
Junzhe Li
Dequan Xuan
Chang Lv
Publikationsdatum
11.01.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Bulletin of Engineering Geology and the Environment / Ausgabe 5/2020
Print ISSN: 1435-9529
Elektronische ISSN: 1435-9537
DOI
https://doi.org/10.1007/s10064-019-01713-w

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