Research and Application of Spatiotemporal Evolution Mechanism of Slope Based on Fiber Optic Neural Sensing

Slope stability monitoring and evaluation are key means to ensure the safety of engineering projects. Firstly, the classification, principles, and characteristics of distributed fiber optic sensing technology for slope engineering are introduced, and the significant advantages of this technology in slope monitoring are analyzed. Secondly, taking the Three Gorges Reservoir landslide as a case study, laboratory experiments of slopes were conducted using spatiotemporally continuous fiber optic neural sensing technology. Through the slope physical model experiment under loading excavation and rainfall conditions, it is found that (1) the strain changes monitored by vertically laid sensing cables are more sensitive to loading (with a peak strain of about 1400 με), while horizontally laid optical cables are more sensitive to excavation processes (with a peak strain of about 8900 με). Specifically, the tension–compression strain transformation in horizontally laid sensing cables can be used to identify slope failure in advance. (2) Rainfall infiltration significantly weakens the strength of the slope soil. Only considering the loading situation, the slope experiences instability and failure under a load of 120 kg. Under the premise of the soil saturation caused by rainfall infiltration, the slope experienced instability and failure under a load of 20 kg. Therefore, compared to human engineering activities, rainfall has a more significant impact on the stability of the slope. This study sheds light on the slope failure mechanism and provides a scientific basis for early warning.

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Publication Details

Journal
Water
Published
2025-09-13
DOI
https://doi.org/10.3390/w17182710
Citations
1
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
2.42

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article

Research and Application of Spatiotemporal Evolution Mechanism of Slope Based on Fiber Optic Neural Sensing

Yujie Nie, Haoyu Zhang, Ziyi Wang, Lei Zhang et al.
1 citations
Water
Landslides and related hazards
2.42
article

Research and Application of Spatiotemporal Evolution Mechanism of Slope Based on Fiber Optic Neural Sensing

Yujie Nie, Haoyu Zhang, Ziyi Wang, Lei Zhang, Dingfeng Cao, Gang Cheng, Yongfei Wu, Jinghong Wu
article en
1 citations

Abstract

Slope stability monitoring and evaluation are key means to ensure the safety of engineering projects. Firstly, the classification, principles, and characteristics of distributed fiber optic sensing technology for slope engineering are introduced, and the significant advantages of this technology in slope monitoring are analyzed. Secondly, taking the Three Gorges Reservoir landslide as a case study, laboratory experiments of slopes were conducted using spatiotemporally continuous fiber optic neural sensing technology. Through the slope physical model experiment under loading excavation and rainfall conditions, it is found that (1) the strain changes monitored by vertically laid sensing cables are more sensitive to loading (with a peak strain of about 1400 με), while horizontally laid optical cables are more sensitive to excavation processes (with a peak strain of about 8900 με). Specifically, the tension–compression strain transformation in horizontally laid sensing cables can be used to identify slope failure in advance. (2) Rainfall infiltration significantly weakens the strength of the slope soil. Only considering the loading situation, the slope experiences instability and failure under a load of 120 kg. Under the premise of the soil saturation caused by rainfall infiltration, the slope experienced instability and failure under a load of 20 kg. Therefore, compared to human engineering activities, rainfall has a more significant impact on the stability of the slope. This study sheds light on the slope failure mechanism and provides a scientific basis for early warning.

WaterVol. 17(18)
North China Institute of Science and Technology (CN), Sun Yat-sen University (CN), Suzhou University of Science and Technology (CN), China University of Geosciences (Beijing) (CN), Nanjing University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hebei Province, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 9%
Landslides and related hazards
2.42
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