Failure mechanism and kinematics of the Tonghua landslide based on multidisciplinary pre- and post-failure data

Cheng, Qiang; Yang, Yinghui; Du, Yi

doi:10.1007/s10346-021-01770-x

Cited by 9 publications

(3 citation statements)

References 63 publications

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“…Positive values represent downslope translations, with magnitudes increasing over higher displacement reduction factors up until instability thresholds are exceeded, indicating translational failures. This is consistent with the findings of Sun et al regarding the acceleration of horizontal deformations prior to collapse [41]. Figure 7b contains the vertical settlement displacements, with subsidence trends observable leading up to instability thresholds, as highlighted by Zhang et al regarding precursory deformation [42].…”

Section: Analysis Of Displacement-reduction Factor Relationships At M...supporting

confidence: 89%

Transforming Landslide Prediction: A Novel Approach Combining Numerical Methods and Advanced Correlation Analysis in Slope Stability Investigation

Umar,

Lin,

Hassan

2024

Applied Sciences

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Landslides cause significant economic losses and casualties worldwide. However, robust prediction remains challenging due to the complexity of geological factors contributing to slope stability. Advanced correlation analysis methods can improve prediction capabilities. This study aimed to develop a novel landslide prediction approach that combines numerical modeling and correlation analysis (Spearman rho and Kendall tau) to improve displacement-based failure prediction. Simulations generate multi-location displacement data sets on soil and rock slopes under incremental stability reductions. Targeted monitoring points profile local displacement responses. Statistical analyses, including mean/variance and Spearman/Kendall correlations, quantified displacement-stability relationships. For the homogeneous soil slope, monitoring point 2 of the middle section of the slope showed a mean horizontal displacement of 17.65 mm and a mean vertical displacement of 9.72 mm under stability reduction. Spearman’s rho correlation coefficients ranged from 0.31 to 0.76, while Kendall’s tau values ranged from 0.29 to 0.64, indicating variable displacement–stability relationships. The joint rock slope model had strong positive total displacement correlations (Spearman’s and Kendall’s correlation ranges of +1.0 and −1.0) at most points. Horizontal and vertical displacements reached mean maxima of 44.13 mm and 22.17 mm, respectively, at the unstable point 2 of the center section of the slope. The advanced correlation analysis techniques provided superior identification of parameters affecting slope stability compared to standard methods. The generated predictive model dramatically improves landslide prediction capability, allowing preventive measures to be taken to mitigate future losses through this new approach.

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Section: Analysis Of Displacement-reduction Factor Relationships At M...supporting

confidence: 89%

Transforming Landslide Prediction: A Novel Approach Combining Numerical Methods and Advanced Correlation Analysis in Slope Stability Investigation

Umar,

Lin,

Hassan

2024

Applied Sciences

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“…It is one of the most direct and accurate methods of characterizing the micro-structure of rock and soil mass, and it can carry out real three-dimensional reconstruction of rock and soil mass materials. Because the high-precision CT scanning technology has been unanimously recognized by experts and scholars, it has been extended to the geotechnical engineering community in recent years [43][44][45][46]. The research of CT scanning technology in soil is mainly concentrated on special soils such as loess, expansive soil, frozen soil, and coarse-grained soil.…”

Section: Discussionmentioning

confidence: 99%

CT Scanning of Structural Characteristics of Glacial Till in Moxi River Basin, Sichuan Province

2022

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Glacial till is a special soil in alpine mountainous areas, which often induces geohazards such as debris flows and landslides due to the influence of special geological environmental conditions in alpine mountainous areas. The change in the structure of glacial till is the main cause of geohazards. Glacial till structure is one of the important factors affecting the mechanical properties of soil. It can explain the mechanical phenomena of soil engineering and establish the quantitative relationship between soil structure and macro–mechanical properties. However, there are few systematic research results on its structure. For this reason, the intact glacial till in the Moxi River Basin, South of Kangding City, Tibetan Autonomous Prefecture of Garzê, Sichuan Province was taken as the research object, and the meso-structure and micro-structure of intact glacial till were studied using CT scanning and scanning electron microscopy (SEM). The meso-structure and micro-structure images of the interior of intact glacial till were obtained and the porosity, particle shape, directivity and structural unit were analyzed. The results show that: (1) the average porosity of longitudinal and transverse sections of intact glacial till are 24.92% and 24.35%, respectively, and the difference is not significant; (2) the average circularity of the particles in the longitudinal and transverse sections is 0.836 and 0.802, respectively, and the average aspect ratio is 2.5 and 3.7, respectively. The shape of the particles in the longitudinal section is more circular than in the transverse section, and the orientation of the particles in the transverse sectional direction is more obvious; (3) the main mineral components of the glacial till sample are mica, feldspar and quartz. In the process of transportation and deposition, the mineral particles undergo different degrees of grinding, crushing and dissolution. The particles are mainly formed by calcareous cementation, and the cementation is dense. The structure is mainly a skeleton structure composed of fine particles that are wrapped or filled. These findings provide the scientific basis for highway-, railway- and hydro-power-station construction and disaster prevention and mitigation in the alpine mountainous area.

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“…Rainfall-induced landslides are geological hazards triggered by prolonged rainfall or short-term heavy rainfall. Scholars have conducted in-depth research on landslide susceptibility mapping [1], data modeling [2], and mechanism analysis [3].…”

Section: Introductionmentioning

confidence: 99%

Capture and Prediction of Rainfall-Induced Landslide Warning Signals Using an Attention-Based Temporal Convolutional Neural Network and Entropy Weight Methods

Zhang

Wei

Yao

et al. 2022

Sensors

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The capture and prediction of rainfall-induced landslide warning signals is the premise for the implementation of landslide warning measures. An attention-fusion entropy weight method (En-Attn) for capturing warning features is proposed. An attention-based temporal convolutional neural network (ATCN) is used to predict the warning signals. Specifically, the sensor data are analyzed using Pearson correlation analysis after obtaining data from the sensors on rainfall, moisture content, displacement, and soil stress. The comprehensive evaluation score is obtained offline using multiple entropy weight methods. Then, the attention mechanism is used to weight and sum different entropy values to obtain the final landslide hazard degree (LHD). The LHD realizes the warning signal capture of the sensor data. The prediction process adopts a model built by ATCN and uses a sliding window for online dynamic prediction. The input is the landslide sensor data at the last moment, and the output is the LHD at the future moment. The effectiveness of the method is verified by two datasets obtained from the rainfall-induced landslide simulation experiment.

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Failure mechanism and kinematics of the Tonghua landslide based on multidisciplinary pre- and post-failure data

Cited by 9 publications

References 63 publications

Transforming Landslide Prediction: A Novel Approach Combining Numerical Methods and Advanced Correlation Analysis in Slope Stability Investigation

Transforming Landslide Prediction: A Novel Approach Combining Numerical Methods and Advanced Correlation Analysis in Slope Stability Investigation

CT Scanning of Structural Characteristics of Glacial Till in Moxi River Basin, Sichuan Province

Capture and Prediction of Rainfall-Induced Landslide Warning Signals Using an Attention-Based Temporal Convolutional Neural Network and Entropy Weight Methods

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