Proceedings of the 2024 3rd International Conference on Structural Seismic Resistance, Monitoring and Detection (SSRMD 2024)

Numerical Simulation Study on the Mechanism of Loess Slope Landslide Formation under Rainfall Effects

Authors
Wei Mao1, 2, Zulin Ren1, *, Xuejun Liu1, 3, Shuqiang Chen3, Yanjun Li3
1School of Civil Engineering and Architecture, Xinjiang University, Urumqi, 830000, China
2Xinjiang Vocational and Technical College of Communications, Urumqi, 831401, China
3Xinjiang Academy of Building Research Co., Ltd, Urumqi, 830001, China
*Corresponding author. Email: 778624012@qq.com
Corresponding Author
Zulin Ren
Available Online 29 April 2024.
DOI
10.2991/978-94-6463-404-4_18How to use a DOI?
Keywords
Loess surface landslide; Shear strength; Rainfall infiltration; Numerical simulation
Abstract

In the Ili region of Xinjiang, there are a large number of loess slopes. Combined with the high rainfall in the Ili Valley, it often poses hazards to engineering construction. Under the influence of rainfall, the moisture content of the loess increases significantly, leading to sliding and failure at the contact surface between the loess and gravel layers. In order to comprehensively analyze the mechanism of loess surface slope landslide under the effect of rainfall, this study conducted field sampling of typical landslides in the area and performed laboratory direct shear tests and finite element numerical simulation studies. The results showed that: after the increase in moisture content, the cohesive strength of the loess increased to some extent, but the internal friction angle continued to decrease, resulting in a continuous reduction in shear strength. The contact surface between the loess and gravel layers was prone to sliding and failure. Under self-weight conditions, the maximum displacement was 3.7cm, while under rainfall conditions, the maximum displacement reached 56.7cm. This is because rainwater infiltration changes the contact form between the loess particles, reducing its shear strength, and the increase in moisture content makes the loess more prone to plastic deformation. After implementing anchor support measures, the maximum displacement of the slope under rainfall conditions decreased to 27.5cm, demonstrating a significant supportive effect. This study can provide reference for the prevention, early warning, and control of loess surface slope landslides in the Ili region.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 3rd International Conference on Structural Seismic Resistance, Monitoring and Detection (SSRMD 2024)
Series
Atlantis Highlights in Engineering
Publication Date
29 April 2024
ISBN
10.2991/978-94-6463-404-4_18
ISSN
2589-4943
DOI
10.2991/978-94-6463-404-4_18How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Wei Mao
AU  - Zulin Ren
AU  - Xuejun Liu
AU  - Shuqiang Chen
AU  - Yanjun Li
PY  - 2024
DA  - 2024/04/29
TI  - Numerical Simulation Study on the Mechanism of Loess Slope Landslide Formation under Rainfall Effects
BT  - Proceedings of the 2024 3rd International Conference on Structural Seismic Resistance, Monitoring and Detection (SSRMD 2024)
PB  - Atlantis Press
SP  - 171
EP  - 182
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-404-4_18
DO  - 10.2991/978-94-6463-404-4_18
ID  - Mao2024
ER  -