Probabilistic stability analyses of two-layer undrained slopes

IF 5.3 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers and Geotechnics Pub Date : 2025-03-03 DOI:10.1016/j.compgeo.2025.107178
Desheng Zhu , D.V. Griffiths , Gordon A. Fenton , Jinsong Huang
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引用次数: 0

Abstract

It is well known that soil properties exhibit spatial variation in both the horizontal and vertical directions that can be modelled as random fields, so this paper will use the random finite-element method (RFEM) to study the reliability of two-layer undrained slopes. Typical applications might include short-term stability of levees or embankments resting on foundation soils with different statistical properties. Results will demonstrate how the difference between the two random fields affects the “seeking out” effect of the failure mechanism, which permits the deeper failure mechanisms to form naturally because of possible lower undrained strengths in the foundation layer. Results will also show the worst-case spatial correlation length that leads to a maximum probability of failure, and demonstrate the worst-case effect becomes less obvious as the mean strength ratio of the two layers increases.
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来源期刊
Computers and Geotechnics
Computers and Geotechnics 地学-地球科学综合
CiteScore
9.10
自引率
15.10%
发文量
438
审稿时长
45 days
期刊介绍: The use of computers is firmly established in geotechnical engineering and continues to grow rapidly in both engineering practice and academe. The development of advanced numerical techniques and constitutive modeling, in conjunction with rapid developments in computer hardware, enables problems to be tackled that were unthinkable even a few years ago. Computers and Geotechnics provides an up-to-date reference for engineers and researchers engaged in computer aided analysis and research in geotechnical engineering. The journal is intended for an expeditious dissemination of advanced computer applications across a broad range of geotechnical topics. Contributions on advances in numerical algorithms, computer implementation of new constitutive models and probabilistic methods are especially encouraged.
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