JRMGE / Vol 16 / Issue 4

Article

Efficient slope reliability analysis under soil spatial variability using maximum entropy distribution with fractional moments

Chengxin Feng, Marcos A. Valdebenito, Marcin Chwała, Kang Liao, Matteo Broggi, Michael Beer

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a Institute for Risk and Reliability, Leibniz University Hannover, Callinstr. 34, Hannover, 30167, Germany
b Chair for Reliability Engineering, TU Dortmund University, Leonhard-Euler-Str. 5, Dortmund, 44227, Germany
c Faculty of Civil Engineering, Wrocƚaw University of Science and Technology, Wrocƚaw, Poland
d Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 610031, China
e University of Liverpool, Institute for Risk and Uncertainty, Peach Street, Liverpool, L69 7ZF, United Kingdom
f International Joint Research Center for Resilient Infrastructure & International Joint Research Center for Engineering Reliability and Stochastic Mechanics, Tongji
University, Shanghai, China


2024, 16(4): 1140-1152. doi:10.1016/j.jrmge.2023.09.006


Received: 2023-10-10 / Revised: 2023-08-22 / Accepted: 2023-09-04 / Available online: 2023-11-04

2024, 16(4): 1140-1152.

doi:10.1016/j.jrmge.2023.09.006


Received: 2023-10-10

Revised: 2023-08-22

Accepted: 2023-09-04

Available online: 2023-11-04


Abstract:

Spatial variability of soil properties imposes a challenge for practical analysis and design in geotechnical engineering. The latter is particularly true for slope stability assessment, where the effects of uncertainty are synthesized in the so-called probability of failure. This probability quantifies the reliability of a slope and its numerical calculation is usually quite involved from a numerical viewpoint. In view of this issue, this paper proposes an approach for failure probability assessment based on Latinized partially stratified sampling and maximum entropy distribution with fractional moments. The spatial variability of geotechnical properties is represented by means of random fields and the Karhunen-Loève expansion. Then, failure probabilities are estimated employing maximum entropy distribution with fractional moments. The application of the proposed approach is examined with two examples: a case study of an undrained slope and a case study of a slope with cross-correlated random fields of strength parameters under a drained slope. The results show that the proposed approach has excellent accuracy and high efficiency, and it can be applied straightforwardly to similar geotechnical engineering problems.

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Keywords: Slope, Random field, Reliability analysis, Maximum entropy distribution, Latinized partial stratified sampling

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Chengxin Feng, Marcos A. Valdebenito, Marcin Chwała, Kang Liao, Matteo Broggi, Michael Beer, 2024. Efficient slope reliability analysis under soil spatial variability using maximum entropy distribution with fractional moments. J. Rock Mech. Geotech. Eng. 16 (4), 1140-1152.

Author(s) Information

Chengxin Feng

✉️ feng.chengxin@irz.uni-hannover.de

Chengxin Feng is currently a PhD student at Leibniz University Hannover, Germany. He obtained his BSc and MSc degrees in hydraulic engineering from the China Three Gorges University in 2018 and 2021, respectively. His research interests include geotechnical uncertainty analysis, reliability analysis, and interval analysis.