地质科技通报

A review of landslide-generated waves risk and practice of management of hazard chain risk from reservoir landslide

Yin Kunlong, Zhang Yu, Wang Yang

2022, 41(2): 1-12. doi: 10.19509/j.cnki.dzkq.2022.0064

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As one of the major types of geological hazards in reservoir areas, the risk analysis of landslides has been a top research topic recently. Landslide-generated waves extend the influence area from the landslide source itself to several kilometers upstream and downstream and greatly expand the type and number of elements and disaster damage. The risk evaluation of landslide generated waves is considered to be a difficult component in the evaluation of landslide risk hazard chains, as involving the intersection of different areas. Firstly, the previous research results in recent decades were synthesized from hazard, vulnerability and risk, the current situation of landslide generated waves risk research and common research methods worldwide were outlined, and the key representative research results were reviewed and analyzed. New progress was introduced, which includes experimental studies considering the complexity of actual river topography, coupled numerical simulation methods focusing on landslide-water interaction mechanisms, and a vulnerability assessment system based on multiple hazard-bearing body types. Secondly, the process and consequences of a number of landslide generated waves risk management cases that have occurred in the Three Gorges Reservoir Area in recent years were described in detail. Finally, according to the author's many years of research experience, new directions and ideas were proposed for the study of landslide-landslide generated waves hazard chain risks, and suggestions were given that surge risk and landslide risk evaluation systems should be merged with each other and developed along the direction of quantification, standardization and refinement.

Abnormal event detection of city slope monitoring data based on multi-sensor information fusion

Liu Gang, Ye Lixin, Chen Qiyu, Chen Genshen, Fan Wenyao

2022, 41(2): 13-25. doi: 10.19509/j.cnki.dzkq.2022.0060

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To prevent and control the loss of people's lives and property caused by sudden urban geological disasters, China has deployed a large number of sensors for urban geological disaster-prone areas to perceive changes in urban underground space. In this article, based on the characteristics of slope monitoring data and the analysis technology of time series data, aiming at problems such as noise mixtures in monitoring data, the difficulty of mode analysis and the uncertainty of early warning thresholds, a method of abnormal event detection in slope monitoring data based on multisensor information fusion is proposed. The results show that: ① Aiming at the disadvantage that the optimal estimation of the Kalman filter requires known noise information, the attenuation memory factor is introduced, and the centralized attenuation memory Kalman filter is used to fuse the multisensor slope monitoring data, which reduces the influence of noise and improves the reliability of slope monitoring data. ② The change mode of slope monitoring data can be summed up as the superposition of periodic term, trend term and noise term. The period is 24 hours, and the trend term can be approximately regarded as the classic Newtonian motion. Based on this, the deformation motion model can be constructed to provide theoretical support for the state transfer of the Kalman filter. ③ The penalty coefficient is introduced to make the improved DTW have a better measurement effect for the periodic sequence. On this basis, anomaly detection is carried out on the slope monitoring data based on K-means clustering, and local anomaly factors are used to analyse the abnormal conditions of the monitoring data. This method can distinguish the time series data of thenormal mode and abnormal mode better, detect abnormal slope monitoring data effectively, and provide guarantees for disaster prevention. Therefore, in view of the insufficiency of slope monitoring data processing and analysis processes, different information fusion technologies are adopted to improve the reliability and robustness of slope monitoring data. The feasibility of the proposed method is verified by slope monitoring data in Shenzhen.

Rainfall erosion characteristics of argillaceous sandstone residual soil slopes

Li Jixing, Yan Song, Yang Chunjian, Fang Yueguang

2022, 41(2): 26-33. doi: 10.19509/j.cnki.dzkq.2022.0051

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As a special soil with a strong structure, argillaceous sandstone residual soil has the characteristics of strong disintegration, poor erosion resistance and great disturbance, it has great influence on the engineering construction. To explore the mechanism of rainfall erosion of argillaceous sandstone residual soil slopes, a slope rainfall erosion test is designed. The surface erosion effect is analysed by 3D laser scanning technology on site. The infiltration characteristics, surface brush evolution mechanism and erosion failure mechanism of argillaceous sandstone residual soil slopes are further clarified by using a high-density electrical method. The results show that in the initial stage of the experiment, the precipitation was highly permeable and mainly migrated to the foot of the slope, and no obvious rills were formed on the surface of the slope. In the middle period of the erosion test, the soil at the foot of the slope reached saturation first, and slope runoff was formed, and the rill expanded to form small-scale erosion chutes and chip erosion areas.In the later stage of the test, the soil erosion in the middle of the slope and at the foot of the slope was serious. The upwards part of the channel at the foot of the slope extended, and the erosion area expanded, which led to the structural change in the surface soil, and the permeability difference was obvious. The rainfall erosion of argillaceous sandstone residual soil slope was mainly divided into three parts. The soil loss of slope mainly occurred in the last stage, with a maximum rill rate of 16.9% and gully connectivity of up to 0.74.

Three-dimensional numerical analysis of the Changgeluo landslide-tunnel engineering disaster on Shangri-Lato Lijiang highway

Wang Jianfei, Liu Kunjue, Zhou Wenjiao, Zhang Yufang, Wang Yankun, Fan Jiawei

2022, 41(2): 34-43. doi: 10.19509/j.cnki.dzkq.2022.0009

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Accurately evaluating the interaction and stability of the landslide tunnel and formulating a reasonable disaster prevention plan are of great significance for ensuring the smooth completion of the Shangri-La to Lijiang highway. This paper takes the typical landslide-tunnel disaster site of Shangri-La to Lijiang highway-Changgeluo landslideas an example, uses on-site engineering geological surveys, drilling, and other methods to determine the cause mechanism and deformation characteristics of the landslide, utilizes numerical simulation to study the spatial stress-strain characteristics and stability state of the Changgeluo landslide under natural, rainfall and tunnel excavation conditions, studies the interaction between the landslide and the tunnel, and proposes corresponding disaster prevention and control plans. The results show that the Changgeluo landslide is a giant rock sliding landslide, which is in an unstable state under natural conditions. The tunnel excavation has limited influence on the overall stability of the landslide, but it will cause local deformation of the landslide.Affected by the deformation of the landslide body, the tunnel part of the landslide body will produce tensile-shear deformation failure. Rainfall seriously deteriorates the stability of the landslide, causing the landslide to lose instability and further causing the tunnel to fail and be destroyed. The original route selection plan faces huge risks, and the optimal prevention plan is to move the route eastward to avoid the tunnel so that the tunnel passes under the sliding surface. The research methods and results can provide a useful reference for similar Shangri-La to Lijiang highway disaster sites.

Modelling rules of landslide susceptibility prediction considering the suitability of linear environmental factors and different machine learning models

Huang Faming, Li Jinfeng, Wang Junyu, Mao Daxiong, Sheng Mingqiang

2022, 41(2): 44-59. doi: 10.19509/j.cnki.dzkq.2022.0010

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For linear environmental factors such as river, road and geological fault networks, buffer analysis in GIS is commonly used to extract the buffer distances to the river and/or road networks. However, the line distances are discrete variables with random fluctuations of different grid sizes and are more sensitive to the errors of point and/or line elements, leading to a reduction in the accuracy of landslide susceptibility prediction (LSP). This study aims to use continuous environmental factors, such as the spatial density of river and road networks, to improve the suitability of linear environmental factors. Taking An'yuan County of Jiangxi Province as an example, 14 environmental factors, such as elevation, topographic relief, distances to river and road networks (original factors), are selected. Then, the two linear environmental factors of distances to river and road networks are improved to river and road density (improved factors). Based on machine learning models such as logistic regression (LR), multilayer perceptron (MLP), support vector machine (SVM) and C5.0 decision tree, original factor-based and improved factor-based machine learning models are built to carry out the LSP. The receiver operating characteristic (ROC) curves and the distribution characteristics of landslide susceptibility indexes are used to evaluate the LSP modelling rules. The results show that ① the LSP accuracy of the improved factor-based models are higher than those of the original factor-based models, indicating that the spatial density is more suitable for LSP; ② the C5.0 model has the best LSP performance among the four machine learning models, followed by the SVM, MLP and LR models; and ③ river and road factors are of great significance for landslide evolution, and their importance does not decrease underimproved factor-based machine learning models.

Evolution mechanism of rainstorm-induced shallow landslides on slopes covered by arbors considering the influence of wind-induced vibration

Miao Haibo, Wang Gonghui

2022, 41(2): 60-70. doi: 10.19509/j.cnki.dzkq.2022.0011

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Shallow landslides on slopes covered by trees are often the result of the coaction of heavy rainfall and strong winds under extreme weather, such as severe convection or typhoons. The Fanzhangzu landslide, a rainstorm-induced shallow landslide in the mountainous area in southern Anhui, was taken as a case study. Through field investigation and meteorological data analysis, it is considered that in addition to rainstorms, wind loads may also promote landslide initiation. To reveal the mechanism of the landslide evolution process, including initiation and postfailure movement, the stability under actual rainfall conditions was first analysed based on the infinite slope model. Then, by using a DPRI ring shear apparatus, undrained cyclic shear tests and natural drainage residual shear tests were carried out on two kinds of soil samples taken from the surroundings of the arbor roots and the sliding surface, respectively. The results show that ① The increase in porewater pressure in the sliding surface results from rainfall infiltration, and the subsequent decrease in stability is the direct reason for the initiation of the Fanzhangzu landslide during rainstorms. ② For the saturated soils around the arbor roots, high excess porewater pressure can be built up under cyclic shear loading resulting from wind-induced vibration, which leads to local failure in the shallow layer and elevates the potential for instability of the Fanzhangzu landslide. ③ The residual strength of the sliding surface soil has a significant positive shear rate effect, so the Fanzhangzu landslide does not show the characteristics of high-speed and long-distance movement in the postfailure stage, which is consistent with the field investigation.

Quantitative risk analysis of toppling slope considering seismic risk

Wei Jinbing, He Zhiliang, Yang Zhongkang

2022, 41(2): 71-78. doi: 10.19509/j.cnki.dzkq.2022.0018

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Risk analysis and assessment are important tools to solve the inherent uncertainty of slopes. At present, there are few studies on systematic quantitative risk analysis of slopes considering the uncertainty of external load and internal geotechnical mechanical parameters at the same time. This paper takes the toppling slopebehind the power plant of the Zhala hydropower station in Tibet as an example. Based on the probability density function (PDF) of site seismic peak acceleration and the fitting function of slope failure probability under different seismic peak accelerations, the overall slope failure probability is calculated by numerical integration, and the influence range of the slope is simulated by the discrete element method (DEM). Then, vulnerability analysis and quantitative risk calculation of elements at risk are carried out. Finally, the ALARP criterion is used for risk assessment. The results show that, considering the seismic risk, the failure probability of the slope is 0.061 9 in the 50-year design reference period. The slope poses a great threat to the ground powerhouse of hydropower stations, and the corresponding economic risk is 54.82 million RMB. According to the ALARP criterion, the slope risk is in the unacceptable area, and measures should be taken to prevent or avoid the risk. The research results have guiding significance for decision-making and risk management of slope treatment engineering.

Landslide susceptibility prediction and identification of its main environmental factors based on machine learning models

Huang Faming, Hu Songyan, Yan Xueya, Li Ming, Wang Junyu, Li Wenbin, Guo Zizheng, Fan Wenyan

2022, 41(2): 79-90. doi: 10.19509/j.cnki.dzkq.2021.0087

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The modelling processes and uncertainties of various machine learning models for landslide susceptibility prediction (LSP) are different, and effectively identifying the main conditioning factors of landslide susceptibility is of great significance. Aiming at these problems, this study aims to discuss the LSP processes and the uncertainties of landslide susceptibility based on machine learning models, namely, support vector machine (SVM) and random forest (RF), and then to innovatively propose the "weighted mean method" for calculating more accurate landslide main control factors. First, the landslide inventories and 10 basic environmental factors of Yanchang County in Shaanxi Province are obtained, and the frequency ratios (FRs) of the environmental factors are taken as the input variables of the SVM and RF models.Then, the landslide and randomly selected nonlandslide samples are divided into model training and testing datasets. Furthermore, the trained RF and SVM models are used to predict the landslide susceptibility and draw the landslide susceptibility prediction (LSP) map.Finally, the uncertainties of LSP modelling are evaluated by the receiver operating characteristic (ROC) curve, mean value and standard deviation, and the main landslide control factors are calculated.The results show that ① Machine learning models can effectively predict the susceptibility of regional landslides. The accuracy of RF in LSP is higher, and its uncertainties are lower than those of SVM. As a whole, the landslide susceptibility distribution rules of the two models are similar.②The main control factors of landslide susceptibility in Yanchang County calculated by the weighted mean method are slope, elevation and lithology.③Case studies and literature reviews show that the RF model is a more reliable susceptibility model than other types of machine learning models.

Type identification and engineering geology zoning of the unstable slope in Tongkuangling

Jia Wei, Luo Changhong, Dong Zhao, Wang Mingfei, Liu Xiaohong, Bao Liulei

2022, 41(2): 91-103. doi: 10.19509/j.cnki.dzkq.2022.0057

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The subgrade, tunnel and bridge engineering of highways or railways may be affected by some geological disasters, especially by unknown disaster types, which directly affects the overall treatment decision.This article takes the Tongkuangling unstable slope on the Yiba Expressway as an example andidentifies the types of the Tongkuangling unstable slope by using field geological surveys, engineering geological analysis and monitoring data analysis. The field investigation shows that this unstable slope is made up of the eluvial deluvial deposit of the upper part and siltstone with an inverted layer of the lower part. Combined with the displacement monitoring data, it is determined that there are multiple shear slip surfaces in the loose deposits. The unstable slope is comprehensively determined to be a deep creep deformation body. Last, according to the characteristics of deformation, the Tongkuangling deformation body is finally divided into two zones, of which zone Ⅱ can be subdivided into two small zones. The Ⅱ₂ zone is the key control part. This provides the geological basis for the subsequent treatment design of the deep deformation body.It can be seen that the combination of traditional engineering geological surveys and monitoring data analysis is an effective means to identify the type of geological disasters and determine the boundary range.

Three-dimensional discrete element simulation of the amplification effect of the slope surface under the action of strong earthquakes

Cai Guojun, Chen Xirui, Sun Wenpeng, Jia Jun

2022, 41(2): 104-112. doi: 10.19509/j.cnki.dzkq.2022.0058

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To study the dynamic amplification effect of slope surfaces under the action of strong earthquakes, a three-dimensional model was established using a rocky slope in Mian County, Shaanxi Province, as an example. The discrete element software 3DEC is used to simulate the deformation and instability process of the slope under dynamic conditions, analyse the dynamic response characteristics of the slope surface, and study the difference in the dynamic response of the slope surface under different seismic wave input conditions. The main conclusions are that when considering the influence of seismic longitudinal waves, the vertical acceleration is significantly enhanced, and the PGA amplification factor of the slope is increased by approximately 1.62 times. The slope shape strongly affects the dynamic response characteristics of the slope surface. Under the action of strong earthquakes, the amplification of the slope shoulder and the slope turning point is very strong, followed by the protruding parts, and the amplification on both sides of the slope surface is the weakest. Under different input conditions, the horizontal PGA amplification factor at the slope turning point maintains a high value, especially when only the horizontal acceleration is input, and this part should be given special attention in the prevention of earthquake landslide disasters. The movement process of a landslide caused by strong earthquakes can be summarized as the initiation stage of the landslide-the high-speed movement stage of the squeeze collision-the accumulation stage. The research results can provide certain theoretical support for disaster prevention and mitigation in this region.

Slope failure criterion for the strength reduction material point method

Jiang Xianping, Zhang Peng, Lu Yiwei, Liu Leilei, Zhang Minghui

2022, 41(2): 113-122. doi: 10.19509/j.cnki.dzkq.2021.0075

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It is necessary to select an instability criterion for the material point strength reduction method (SRMPM) to solve the slope safety factor (F_s), and there are some differences in the obtained F_s values with different instability criteria. To examine the rationality and applicability of the four common instability criteria (i.e., calculation nonconvergence, displacement mutation of the feature point, transfixion of the plastic zone and the limit value), this paper uses the SRMPM to analyse the stability of two slope examples. The F_s obtained by the Spencer limit equilibrium method (LEM) is taken as a reference to further verify the rationality and accuracy of the results. The results show that ① the material point calculation is convergent, so the calculation nonconvergence cannot be used as the slope instability criterion; ② when the displacement mutation of the feature is regarded as the criterion of slope instability, the F_s is basically consistent with the LEM, so the displacement mutation of the feature point can be used as the slope instability criterion; and ③ the limit value and the transfixion of the plastic zone cannot be used alone as the slope instability criterion.

Analyzing the characteristics and reason for the ground collapse hazard in Shenzhen

Shi Qiuhua, Wei Huilong, Tan Fei, Zhou Jinwen, Zhu Jianghuang

2022, 41(2): 123-129. doi: 10.19509/j.cnki.dzkq.2022.0056

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To ascertain the causes of ground collapse in Shenzhen and put forward prevention and control measures, this paper collects ground collapse accidents in Shenzhen between 2016 and 2020 and analyses the spatial and temporal distribution, hazard degree of ground collapse, and causes of ground collapse through field investigation, statistical data analysis and GIS spatial analysis. The results show that ground collapse disasters in Shenzhen are in a stage of continuous growth, most of which are small-scale ones, and most of which occur in the rainy season, especially from May to August. The disaster sites of ground collapse are mainly in Futian District, Luohu District and Guangming District, and the main sites of ground collapse are municipal roads and sidewalks. The main reason for ground collapse disasters is damage to water pipelines, damage to culverts, improper construction, rainwater erosion, settlement of soft soil, excessive vehicle loads and so on. Among them, water pipeline damage and improper construction are the main causes of ground collapse. The research results can provide some reference for the prevention and control of ground collapse in Shenzhen and other similar cities.

Stability prediction of landslide dams based on SSA-Adam-BP neural network model

Song Yixiang, Zhang Xiaobo, Huang Da

2022, 41(2): 130-138. doi: 10.19509/j.cnki.dzkq.2022.0040

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Most of the existing landslide dam stability prediction models are linear models, which cannot fully consider the complex nonlinear relationship between landslide dam stability and its morphological characteristics and hydrodynamic conditions.In view of this, a new SSA-Adam-BP model for predicting the stability of landslide dams is proposed by combining the back propagation neural network model and the salp optimization algorithm.The grid search method is used to select the best combination of hyperparameters that can determine the structure of the model.Then, the models with different optimization algorithms are evaluated by cross-validation and ROC curve drawing.The practical application of the model is explained and verified by using the global data of 153 landslide dams in the open source database.Compared with the traditional linear model, the combination of the SSA and Adam optimization algorithm improves the global search ability of the BP model, and its average cross-verification accuracy reaches 91.73%.It not only has a lower misjudgment rate but can also use fewer parameters to quickly and accurately predict the stability of landslide dams.The SSA-Adam-BP model can accurately predict the stability of typical projects in recent years, with certain practicality and system platform promotion application value.

Energy conversion of the high-speed landslide movement process based on a sliding surface partition mechanical model

Liu Yiliang, Chen Jianxiang, Gao Chenxi, Song Kun, Tang Xuan

2022, 41(2): 139-146. doi: 10.19509/j.cnki.dzkq.2022.0061

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High-speed landslides have the characteristics of fast movement speed and rapid spread. Therefore, it is necessary to study the whole movement process of landslides starting, accelerating and resting.Based on the mechanical properties of the sliding surface, the sliding surface is divided into an elastic medium region and a strain weakening region, and a two-dimensional mechanical model of a high-speed landslide is constructed. The energy calculation formulas of landslide initiation and landslide movement processes are proposed. Taking the Qianjiangping landslide as an example, the initiation speed of the landslide is 2.35 m/s by using the energy calculation formula of landslide initiation. According to the sliding surface morphology, the landslide movement trajectory can be divided into a fast acceleration stage, a steady acceleration stage, a steady deceleration stage, and a sharp deceleration stage. The maximum speed is 16.8 m/s during analysing the motion process. The elevation plane of the landslide front is taken as the potential energy datum plane to analyze the variation in different energy and total energy ratios. In the four movement stages of the landslide, the proportions of kinetic energy were 9.1%, 25.6%, 15.1%, and 0%; the proportions of friction loss energy were 5.5%, 58.8%, 81.7%, and 95.5%; the proportions of potential energy were 85.2%, 14.2%, 0%, and 0%;and the proportions of other resistance energy consumption were 0.2%, 1.4%, 3.2%, and 4.5%. The research conclusions are of great significance to the hazard mechanism and risk analysis of high-speed landslides.

Experiments on the bearing capacity of aeolian sand stabilized by cement stabilizers

Sheng Mingqiang, Zou Chun, Qian Zengzhen, Lu Xianlong

2022, 41(2): 147-153. doi: 10.19509/j.cnki.dzkq.2021.0259

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Aeolian sands are inherently very low in strength and very poor in stability. By using local sources according to local conditions, aeolian sand stabilization with cement may be an alternative method to improve the mechanical characteristics of aeolian sand in desert areas. In this study, shear, compression and uplift bearing capacity tests were carried out on the cement-stabilized aeolian sand with 3% water content by using aeolian sand collected from the Kubuqi Desert of Inner Mongolia. The results show that cement stabilization has a much greater enhancement on the cohesive strength than that of the inner frictional angle. After 28 days of normal temperature curing, the average unconfined compressive strength of the stabilized aeolian sand with 3% water content and 6% cement content is 0.156 MPa. The uplift load-displacement curve of stabilized aeolian sand shows a two-stage change law from the initial elastic section to the peak load and failure after the peak load, which has obvious brittle failure characteristics. The results show that the uplift capacity of aeolian sand stabilized by cement is related to the foundation slab size, uplift embedment, and the ratio of uplift embedment to foundation slab width.

Influence of bedrock depth on the seismic response of a nuclear reactor building foundation considering soil structure interaction

Gao Yun, Xu Ruoshi, Sun Wenjing

2022, 41(2): 154-164. doi: 10.19509/j.cnki.dzkq.2022.0043

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Earthquakes events can impact on safety of nuclear power plants. With the increasing number of nuclear power plants, the necessity of seismic safety of nuclear power plants becomes higher than ever before. Nuclear reactor building is an important part of nuclear power plant, so the importance to understand its seismic response is critical.Adopting the direct method, this paper utilized FLAC3D to model the soil-nuclear reactor building three-dimensionally on three different site conditions(medium hard soil, soft rock and hard rock).To capture the separation and sliding between the superstructure and the rock/soil deposit, Interface elements were set between the foundation of the nuclear reactor building and the rock/soil surface. The superstructure was simulated by lumped mass model, and the influence of bedrock depth on the seismic response of nuclear reactor building was investigated considering soil structure interaction. Finally, the acceleration response spectrum, shear force, foundation rocking, foundation differential settlement and lateral displacement of the structural members of the nuclear reactor building were obtained. The results show that the displacement and shear force decreased with the increasein bedrock depth in medium hard soil; In the hard rock site, the trends tended to be opposite; However, under the condition of soft rock site, the response of superstructure is more complex. For the foundation rocking and differential settlement, in the medium hard soil site, the reactions decreased with the increase in bedrock depth; In soft and hard rock sites, there is no obvious trend. The differential settlement of foundation can directly reflect the damage of structure. The results show that the differential settlement of foundation in medium hard soil site exceeded the allowable value, so the influence of differential settlement of foundation on nuclear reactor building can not be ignored, which is important for the safety design of nuclear power plant.

Discrete element analysis on influencing factors of deposit morphology of landslide dam

Liu Shiqi, Wang Huanling, Gao Chuang, Qu Xiao

2022, 41(2): 165-175. doi: 10.19509/j.cnki.dzkq.2022.0042

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Landslides are the most important reason of landslide dams and can be formed under the action of earthquakes, rainfall, ice and snow melting water. The deposit shape range of a landslide dam has an important influence on the stability evaluation. In this paper, the effects of sliding distance, sliding surface outlet width, sliding surface angle, riverbed inclination angle and valley shape on the deposit shape of landslide dams are analysed systematically by the discrete element method (DEM). The results are as follows: The sliding distance and outlet width have the greatest influence on the dam height. With increasing outlet width and sliding surface angle, the dam length and width linearly increase and decrease, respectively. Sliding distance can effectively control the velocity of the sliding body and then affect the forward dip angle. The angle of the riverbed mainly affects the length of the dam. The regression analysis of dam height, dam length, upstream and downstream absolute dip tangents and deposit angle tangent shows that the mathematical model fits well, indicating that its shape can be predicted. Two parameters, λ and χ are proposed to describe the deposit characteristics of the landslide dam. The influence of the river valley shape is mainly reflected in the fact that the climbing ability of the sliding body increases with increasing bottom width of the river valley. This study is of great significance for predicting the deposit shape of landslide dams and then evaluating safety and provides a reference for further research on the collapse of landslide lakes.

Simulation method of stratigraphic uncertainty using a boundary model and generalized coupled Markov chain model

Pan Min, Deng Zhiping, Jiang Shuihua

2022, 41(2): 176-186. doi: 10.19509/j.cnki.dzkq.2022.0106

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Stratigraphic uncertainty has a significant impact on the performance evaluation of geotechnical structures, and it is important for engineering practice to accurately characterize the uncertainty. Hence, an effective simulation method of geological uncertainty is proposed. In the framework of probability, the boundary model and the generalized coupled Markov chain model are coupled to make full use of their advantages. First, the parameters of the boundary model are identified by the Bayes method, and then the boundary of the rock-soil material is simulated by a conditional random field. Then, the boundary model simulation results are used as background information in the generalized coupled Markov chain model to realize the coupling of the two models. Finally, taking a construction site in Hong Kong as an example, the simulation results of stratigraphic uncertainties for three different models are compared, and the advantages of the combination model proposed in this paper are clarified. The effects of the number and location of boreholes on the stratigraphic uncertainty simulation are discussed. The results show that compared with the boundary model and the generalized coupled Markov chain model, the coupling model can not only simulate the complicated stratum distribution but also consider the spatial distribution trend of the boundary and effectively avoid the geological anomaly phenomenon. The borehole layout scheme has a great impact on the stratigraphic uncertainty and its realization.

Identification of geological hazards based on the combination of InSAR technology and disaster background indicators

Dong Jiahui, Niu Ruiqin, Qi Mengru, Ding Zan, Xu Hang, He Rui

2022, 41(2): 187-196. doi: 10.19509/j.cnki.dzkq.2022.0024

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Synthetic aperture radar interferometry (InSAR) is an important method to obtain surface deformation information. Due to the limitations of InSAR data acquisition and the accuracy errors produced in the data processing, the identification of hidden dangers also needs to be combined with the analysis of geological hazards themselves, so a method based on InSAR technology combined with the disaster-pregnancy background in the study area is proposed. This study took the Badong section of the Three Gorges Reservoir area as the study area, and ALOS-2 PALSAR radar images were used to obtain the spatial distribution and change rate of deformation in the study area by using time-series InSAR technology. Combining the disaster-prone background of the study area, four indicators of the susceptibility level, slope, engineering rock group and distance from the disaster catalogue point are used as indicators for the identification of hidden dangers of geological disasters. As a result, 19 suspected hidden disaster areas were identified comprehensively, and then the suspected hidden geological disaster areas were verified in the field one by one. The success rate of verification and identification was 78.9%, proving that the method combining the disaster pregnancy background and InSAR results is feasible and can play an important role in regional disaster identification.

County comprehensive geohazard modelling based on the grid maximum method

Fan Yajie, Fan Xuanmei, Fang Chengyong

2022, 41(2): 197-208. doi: 10.19509/j.cnki.dzkq.2022.0046

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Sichuan Province is characterized by great differences in topography, lithologic structure and frequent occurrence of various local disasters. Therefore, it is of great significance to carry out evaluations of the vulnerability of geological disasters. Rockfall and debris flows are landslides in a broad sense. Taking Danba County, Sichuan Province, as a case study, the spatial probability distributions of collapse, landslide and debris flow are comprehensively considered from the perspective of the susceptibility of different types of landslides to regional geological disasters. Based on ArcGIS, 10 key control factors of geological hazards, such as elevation and slope, were selected by a high-precision digital elevation model, and the susceptibility of comprehensive geological hazards was evaluated by an information content model. Finally, the Cell Statistics function of ArcGIS was used to realize the synthesis and comprehensive vulnerability of the maximum value method of multiple raster layers, and the ROC curve was further used to verify the accuracy of the vulnerability model of landslide categories in a single area. According to the natural break point method, the very low-, low-, medium-, high- and very high-prone areas were divided, and the high- and very high-prone areas were mainly concentrated in Zhanggu Town, Taipingqiao Township and Jiaju Town.This paper shows that the information model can evaluate a single type of geological hazard and that the grid maximum method is an effective evaluation method to obtain the comprehensive vulnerability.

Study on the effect of tower foundation landslide protection measures based on a physical model test

Li Side, Li Yuanyao, Yin Kunlong, Zhong Yuan, Liu Yi, Xu Yilin

2022, 41(2): 209-218. doi: 10.19509/j.cnki.dzkq.2022.0044

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A large number of high voltage transmission tower foundations crossing mountainous and hilly areas are often located in high-prone slope areas of landslide disasters. Applying appropriate protective measures to improve their stability is the key to ensuring the continuous and safe operation of transmission lines. To study the protection effect of different protection measures on the tower foundation landslide, this paper takes the Yanzi landslide in Badong County, Hubei Province as a geological prototype, designs and produces a physical test model, and carries out physical model tests of the landslide under extreme rainfall conditions(50, 100 mm/h) without protection, applying anti-slide piles and lattice protection. The deformation and failure characteristics of the landslide and the protective effect of different protective measures are revealed from the experimental point of view. The results show that under two extreme conditions, the unprotected landslide experienced the evolution process of slope surface erosion, crack propagation, local collapse and deformation, and overall sliding. The anti-slide pile measures have a significant effect on the overall protection of the landslide. The landslide is in a stable state, the deformation of the tower foundation is small, and the inclination rate of the tower meets the specification, but the slope surface will be scoured and collapsed. Lattice slope protection measures can effectively reduce the risk of slope erosion and slope toe collapse, but the overall stabilization of the tower foundation under continuous heavy rainfall is slightly weaker. The model test results are consistent with the historical deformation of the landslide and the actual treatment effect. The test conclusions can provide a reference for the failure mechanism research and protection engineering design of similar tower foundation landslides.

Analysis of instability disaster of rainfall induced shallow landslides at the regional scale based on the modified Green Ampt model

Yang Shuai, Tan Zeying, Chen Hongxin, Zhang Jie

2022, 41(2): 219-227. doi: 10.19509/j.cnki.dzkq.2022.0048

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Due to similar engineering and hydrogeological conditions, landslides in the same area often occur in groups under highly correlated rainfall. As a result, predicting shallow landslide instability disasters at the regional scale is of great significance to disaster prevention and mitigation work. This paper suggests a new prediction model, the regional assessment of rainfall induced landslides (RARIL), in which the modified Green-Ampt model is used to analyse rainfall infiltration, the infinite-slope model is used to calculate the safety factor, and the reliability principle is used to consider the parameter uncertainty in regional landslide stability analysis. The model has the advantages of considering the instability mechanism of rainfall-induced shallow landslides, the uncertainty of the slope soil parameters in the area, and high computational efficiency and can be easily implemented in GIS. The case study shows that the RARIL model can accurately predict the landslide disaster caused by heavy rainfall in the region along the 303 provincial Highway K0-K20 section from 11∶00 on August 12, 2010, to 9∶00 on August 14, 2010. Therefore, it has good application prospects in predicting regional landslide instability disasters induced by rainfall.

Machine learning based on landslide susceptibility assessment with Bayesian optimized the hyperparameters

Yang Can, Liu Leilei, Zhang Yili, Zhu Wenqing, Zhang Shaohe

2022, 41(2): 228-238. doi: 10.19509/j.cnki.dzkq.2022.0059

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In machine learning-based landslide susceptibility assessment, there are some differences in the evaluation results obtained by using different hyperparameters. This paper aims to use the Bayesian algorithm to optimize the hyperparameters of four common machine learning models (logistic regression, support vector machine, artificial neural network and random forest) and to explore the optimization effect of this algorithm. Taking the landslide susceptibility assessment of four counties (Anhua, Xinhua, Taojiang, and Taoyuan Counties) in central Hunan as an example, the feasibility and applicability of the algorithm are illustrated. Based on the landslide inventory, 1 017 landslide points in the study area were determined, and 15 landslide influencing factors were selected to construct the training set and test set. The Bayesian optimization algorithm is used to optimize the main hyperparameters of the four machine learning models, and four optimal models are established according to the optimized hyperparameters. The AUC value and other indicators are used to compare the predictive ability of different models. The results show that ① the prediction performance of the hyperparameters optimized models is better than that of the unoptimized models. ② Among the four optimization models, the coupling model of the random forest and Bayesian optimization algorithm has the best prediction performance.

Outlier detection method for geotechnical engineering based on MetaOD model selection

Zou Tongtong, Liu Xiaoyi, Liu Jinquan, Yuan Hailiang, Lu Yubin, Zhang Wanhu

2022, 41(2): 239-245. doi: 10.19509/j.cnki.dzkq.2022.0041

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The geotechnical engineering field and indoor parameter test data are the foundation of engineering construction, design and evaluation. The existence of abnormal data often misleads the determination of parameters such as construction and design. Data anomaly detection is the most basic but extremely important task to ensure the safety and reliability of a project. Aiming at the blindness of detection due to the lack of model selection in traditional anomaly detection algorithms, this paper proposes an anomaly detection model system based on a combination of meta-learning outlier detection (MetaOD) and data mining algorithms. The system first selects the initial model class and its parameters suitable for different data types according to the characteristics of the data, averages the selected parameters of the same type of algorithm, and then uses the selected algorithm to diagnose data anomalies, thereby improving the anomaly accuracy of detection. To evaluate the effectiveness of the model, the machine learning test dataset (glass dataset) proposed by the University of California Irvine, is used for test analysis. The results show that the accuracy rate of anomaly detection using this model system reaches 96.41%, which is much higher than that of other detection algorithms. Finally, the model system is applied to the uniaxial compressive strength dataset of the Macau granite and the groundwater monitoring data of the Junchang Tunnel to carry out anomaly detection and analysis and to identify 9 and 10 abnormal points, respectively.

Optimization of the landslide identification method based on a dual attention mechanism

Wu Qi, Zhou Chuangbing, Huang Faming, Yao Chi

2022, 41(2): 246-253. doi: 10.19509/j.cnki.dzkq.2022.0053

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With the development of computer vision technology, studies on landslide identification have gradually been carried out by means of deep learning. By introducing the dual attention model, an optimization algorithm for landslide image recognition based on a convolutional neural network is proposed in this paper. Based on 2 200 landslide image datasets, this paper discusses the effects of 10 network structures and 4 attention models on landslide recognition results. The effectiveness of this method is verified by using a 4∶1 training set and test set for landslide recognition. The results show that the ResNet structure performs better than other network structures. For this example, the ResNet-101 structure has the highest recall rate, precision rate and F1-measure. Compared with a single neural network, the convolutional neural network with a dual attention model has a higher accuracy of landslide identification, and the segmentation result of the landslide boundary is closer to the real landslide boundary. Among them, the ResNet-101+DAN model is the optimal model. In contrast, a single neural network cannot overcome the influence of the image noise, and the result of the image segmentation is poor.

Susceptibility assessment of a translational rockslide considering the control mechanism and spatial uncertainty of a weak interlayer: Application study in Tiefeng Township, Wanzhou District

Feng Xiao, Wang Yu, Liu Yang, Liu Qingli, Du Juan, Chai Bo

2022, 41(2): 254-266. doi: 10.19509/j.cnki.dzkq.2022.0049

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Translational rockslides are an important disaster that endangers the safety of mountain towns. The dip slopes with weak interlayers are the areas prone to translational rockslides. The regional translational rockslide susceptibility assessment should consider the sliding mechanism and spatial distribution uncertainty analysis of the weak interlayer. Taking Tiefeng Town of Wanzhou District as the study area, based on the detailed investigation of the material, structure and spatial distribution of weak interlayers, this paper analysed the evolution mechanism of shale and mudstone developing into sliding surfaces under the action of primary deposition, tectonic deformation and supergene transformation and summarized the deformation and failure mechanism of translational rockslides. Considering the spatial distribution uncertainty of the weak interlayer, a calculation model of the vertical distribution of the weak interlayer and the contribution of the weak interlayer to slip control in the effective control depth are proposed. The key factors that characterize the sliding structure, including the type of weak interlayer and the contribution degree of the weak interlayer, are selected as susceptibility assessment factors. In addition, four elements, topography, slope structure, hydrogeology and human activities, are considered. The susceptibility of translational rockslides in the study area was assessed with slope units adopting the analytic hierarchy process. The investigation and assessment results show that the mud interlayers of the Jurassic Zhenzhuchong Formation and the shale layer of the Ziliujing Formation are the main potential slip surfaces of the translational rockslide in the study area. The extremely high susceptibility area and high susceptibility area accounted for 9.7% and 25.8%, respectively. The distribution of the underlying weak interlayer and the excavation of the slope units are the main factors affecting the susceptibility to landslide disasters. Human activities such as house building and road excavation are the main triggering factors of translational rockslides.Compared with the susceptibility assessment results without considering the factors of the weak interlayer, the results of the method proposed in this paper are more consistent with the facts.

Multiduration critical rainfall prediction model for typhoons and non-typhoon rainfall landslides

Li Qianqian, Shi Xushan, Chai Bo, Wang Wei

2022, 41(2): 267-273. doi: 10.19509/j.cnki.dzkq.2021.0076

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The statistical determination of critical rainfall is a commonly used method for the early warning of landslides. The typhoon rainstorm in southeast coastal areas is different from the general rainfall, and often cause landslide disasters, thus threatening the safety of people's property in coastal, in order to establish the critical rainfall prediction model of typhoon and nontyphoon rainfall landslides, taking Lishui City, Zhejiang Province, as an example, based on the statistics of both rainstorm and nontyphoon-included landslides and rainfall during 2010-2020. The relationship between the occurrence probability of landslides and effective rainfall in Lishui City was constructed. A multiduration critical rainfall prediction model was proposed, and the results of typhoon and nontyphoon prainfall landslide prediction models were compared and analysed. The results show that the difference in rainfall type and rainfall between nontyphoon rainfall and typhoon rainstorms is the main reason for the difference in the two types of prediction models in Lishui City. The critical rainfall value method and effective rainfall days determined by the multiduration prediction model are more consistent with the prediction of rainfall landslides in Lishui City, and the prediction accuracy is higher than that of the traditional correlation analysis method.The research results have theoretical significance for the development of the regional rainfall-induced landslide predictive model, and have important practical significance for the early warning of the flood season landslides in the southeastern coastal areas of my country.

Failure experiment of soft-hard interlayer bedding rock slope

Tan Mingjian, Zhou Chunmei, Sun Dong, Zhou Zichao

2022, 41(2): 274-281, 324. doi: 10.19509/j.cnki.dzkq.2021.0096

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Bedding rock slopes with soft-hard interlayers have complicated failure types and are difficult to prevent. In view of the prone and frequent occurrence of such slope geological disasters, research is carried out from the aspects of slope angle, rock formation tendency and combination form, and joint distribution.Slope physical model testing is an important means to reveal the mechanism of slope deformation and failure.Based on similarity theory, this paper takes the Sunjia landslide in Wanzhou District, Chongqing City, as the engineering support and designs the indoor slope physical model test according to the geological exploration report of the landslide area.The test simulates gravity loading through a jack-up model box and explores the relationship between the front slope angle and the weak interlayer inclination when the bedding rock slope slope is damaged.Combined with the finite element analysis software Plaxis 2D, multiple sets of numerical simulation tests were performed on the physical model to verify the failure mechanism of bedding rock slopes with soft-hard interlayers. The results show that for a bedding rock slope, when the inclination angle of the weak interlayer is approximately 22°, the leading edge excavation slope angle is about 58°, the bedding rock slope is prone to sliding, and the sliding surface is the joint surface of the trailing edge and the weak interlayer. Through the surface.Therefore, the stability of a bedding rock slope is controlled by the density of the layer and the joint surface. When the slope contains multiple weak layers, it is easy to break along the layer and the back edge of the joint. As the number of weak surfaces increases, the slope stability coefficient gradually decreases.The research results can provide a theoretical basis for the instability mechanism and stability evaluation of bedding rock slopes caused by road excavation and slope cutting, and provide support for the prediction of the bedding rock slope instability.

Influence of anchor uncertainty on the failure probability of reinforced slope

Wang Shangshang, Chen Fu, Li Dongxian, Lin Houlai, Liu Zhiliang, Li Liang

2022, 41(2): 282-289. doi: 10.19509/j.cnki.dzkq.2022.0055

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To explore the influence of anchor uncertainty on the failure probability of reinforced slopes, the uncertainty of anchors is considered through the following two approaches: one assumes that the friction force on the unit surface of the contact surface between the anchor and the anchor solid is a log-normal distribution variable, and the other introduces the attenuation coefficient of the friction force on the unit surfaceof the contact surface between the anchor and the anchor solid to consider the uncertainty of the anchor during construction and maintenance. The limit equilibrium method and Monte Carlo sampling method are used to calculate and compare the variation curve of the failure probability of the reinforced slope through two approaches.Finally, the effectiveness of the proposed method is validated against an example of the slope retaining project of the Shenzhen Holiday Inn foundation pit.The results show that the failure probability of the reinforced slope increases gradually with the increase range in the coefficient of variation of unit surface friction on the contact surface between the anchor and the anchor solid under the same soil statistical parameters, and the increase range is between 18.03% and 41.90% for the first approach. For the second approach, the failure probability of the reinforced slope increases rapidly with the decrease in the attenuation coefficient of the anchor ranging from 1.0 to 0.0, and the increase range is between 55.64% and 124.90%. Under the same attenuation coefficient, the failure probability of the reinforced slope increases with the increase in the number of attenuation anchors. The research results provide decision support for the management of anchors during construction and operation.

Susceptibility assessment of geological disasters based on an information value model: A case of Gulin County in Southeast Sichuan

Wen Xin, Fan Xuanmei, Chen Lan, Liu Shikang

2022, 41(2): 290-299. doi: 10.19509/j.cnki.dzkq.2022.0054

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Geological disasters threaten the safety of people's lives and property in mountainous areas. The assessment of the susceptibility to geological disasters will help mountainous towns carry out planning and construction to avoid disaster risks. Gulin County in Southeast Sichuan was chosen as the study area. First, based on the ArcGIS spatial analysis, we select the seven evaluation factors of elevation, slope, lithology, slope structure, vegetation index, distance from fault and distance from road and use the information value model to assess the susceptibility of landslide and rockfall disasters. Furthermore, the ArcGIS cell statistics function was used to compare the information value of landslide and rockfall susceptibility, and a relatively larger information value was selected as the final information value of the raster unit to draw the comprehensive geological hazard susceptibility map of the study area. The susceptibility of geological disasters in Gulin County is divided into extremely low, low, medium, high and extremely high susceptibility zones by the natural breaks method. The results show that geological disasters are mainly distributed near faults and roads. Faults and human engineering activities are the main reasons for the frequent occurrence of geological disasters in the study area. The total area of high and extremely high susceptibility zones is 1 315.62 km², accounting for 41.32% of the total area. The performance of the prediction model is tested by the ROC curve, and the AUC is 0.812 5, indicating that the comprehensive disaster susceptibility of Gulin County predicted by the raster maximum method is good.

Deformation and evolution characteristics of landslides with multiple sliding zones based on physical model test

Yang Dengfang, Hu Xinli, Xu Chu, Wang Qiang, Niu Lifei, Zhang Jiehao

2022, 41(2): 300-308. doi: 10.19509/j.cnki.dzkq.2021.0069

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The deformation and evolution characteristics of landslides has always been a key problem to be solved in the field of landslide disaster prediction and prevention, but there are few studies on the deformation evolution characteristics of multiple sliding zone landslides. A physical model of landslides with three sliding zones has been developed to study the whole deformation evolution process of landslides with multiple sliding zones. To realize multiparameter data analysis of multiple sliding zone landslide evolution processes. The displacement data of the slope surface are obtained by PIV technology, and the deep displacement of the landslide is monitored by a flexible inclinometer. At the same time, the soil pressure box is arranged to obtain the change in the internal soil pressure of the landslide. The experimental results show that the failure of multiple sliding zone landslides can be divided into four stages: the initial deformation stage, uniform deformation stage, accelerated deformation stage and failure stage. The main deformation area of the landslide is different in different stages.The deformation of the lower sliding mass gradually develops to shallow depths under the action of gravity and thrust due to the traction of the upper sliding mass. During the deformation process, the stress of the landslide gradually concentrates to the sliding zone, and the landslide thrust presents a multilevel trapezoidal distribution in the direction of depth. During the accelerated deformation stage, the stress at the sliding zone increases rapidly, multilayer stress concentration zones occur in the landslide body, and the thrust change at the sliding zone position is significantly related to the landslide displacement.

Laboratory experiment on the influence of constraint conditions on landslide-generated waves

Zhang Yujie, Xu Guoqing, Wang Yang, Yang Chaoyue, Peng Keng, Wang Wei

2022, 41(2): 309-314. doi: 10.19509/j.cnki.dzkq.2022.0052

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The constraint conditions have a great influence on the geometry of reservoir landslides during mass movement and are one of the most important parameters for predicting landslide-generated waves. To explore the effects of constraint conditions on the characteristics of landslide-generated waves (such as wave height, amplitude and period), 54 sets of landslide-generated wave physical model experiments based on the orthogonal experimental design method were conducted in this paper. Furthermore, the wave characteristics under constrained and semiconstrained conditions were analysed using statistical methods. The results indicate that the wave period is basically unaffected by the constraint conditions, while the wave height and amplitude of the semiconstrained model are smaller than those of the constrained model, the initial wave height of the semiconstrained model is approximately 0.95 times higher than that of the constrained model, and the maximum amplitude of the semiconstrained model is approximately 0.9 times that of the constrained model. Therefore, it is safer to predict the initial wave height and maximum amplitude by using the geometric parameters before failure, although the geometry of the landslide has been greatly changed from its original state.This study can provide a theoretical basis for landslide-tsunamis prediction.

Strength characteristics of slip zone soils of the Tongjiaping landslide in the Three Gorges Reservoir area under different ring shear conditions

Zhao Fancheng, Miao Fasheng, Wu Yiping, Xue Yang, Meng Jiajia

2022, 41(2): 315-324. doi: 10.19509/j.cnki.dzkq.2022.0045

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Studying the strength characteristics of slip zone soils under different shear conditions is of great significance for the stability evaluation of reservoir landslides. Aiming at the weak research on the mechanical properties of landslide zone soil in the reservoir bank accumulation layer at present, in this paper, the Tongjiaping landslide slip zone soil in the Three Gorges Reservoir area is taken as an example to research the strength variation characteristics of slip zone soils under different shear test conditions. The ARS-E2 ring shear apparatus is employed to operate the shear modes of constant velocity, acceleration and deceleration on the strength variation characteristics of the slip zone soil. The experimental results indicate that the stable residual strength of slip soil samples tends to be obtained under constant low-speed shear conditions; meanwhile, the phenomenon of 'strain softening' is prone to appearing after reaching the peak strength. Moreover, the change trend of shear stress is basically the same whether accelerated ring shear or decelerated ring shear under the same shear stress condition, which both have a positive correlation with the normal stress. However, the change in shear rate will significantly affect the peak cohesion of slip zone soils. The research results reveal the mechanical properties of the sliding zone soil under different ring shear conditions, which provide a theoretical basis for revealing the mechanical mechanism of the deformation and failure of reservoir bank accumulation landslides.

Determinations of the critical sliding surface of planar sliding rock slopes and their stability analysis

Zhou Ke, Huang Xiaocheng, Lei Deyang, Chen Qiunan, Jiang Feifei

2022, 41(2): 325-334. doi: 10.19509/j.cnki.dzkq.2022.0062

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It is still a difficult problem to determine the sliding surface of a rock slope quickly and accurately because the efficiency and accuracy cannot be met at the same time in traditional searching methods. The limit equilibrium method is widely accepted in the stability analysis of rock slopes. The planar shear sliding model of a rock slope is adopted to characterize the position of the potential sliding surface by the inclination of the sliding surface; the analytical solution of the potential sliding surface of a multistage rock slope under the condition of limit equilibrium is derived based on the extreme value method, and its accuracy is verified combined with the Sau Mau Ping slope in Hong Kong. Furthermore, the system stability of the Dayingpanshan slope in Yibi, Sichuan Province with multiple steps in a highway is analysed. The results show that the slope potential sliding surface inclination determined by this method is in agreement with the practical sliding inclination of the Sau Mau Ping slope. In practical engineering applications, the dip angles of the sliding surface obtained by using the Cuckoo search method and simulated annealing method in Slide software are 38.0° and 37.0°, respectively, and the dip angle obtained by the analytical method in this paper is 34.8°.The Janbu method, Morgenstern-Price method and Sarma method are selected to calculate the corresponding stability coefficients, the results are approximately 1.04. The stability coefficient obtained in this paper is 1.15. The results obtained by this method are basically accurate. Through parameter sensitivity analysis, it is found that with the increase in cohesion, the inclination angle of the slope slip surface decreases, and the stability coefficient also increases. When the internal friction angle increases, the slope slip surface inclination and stability coefficient also increase.

Experimental research on uplift bearing capacity of the assembled foundation with cone tube and slab in frozen subsoil

Zhang Xueli, Cui Qiang, Zhang Shulin

2022, 41(2): 335-342. doi: 10.19509/j.cnki.dzkq.2022.0050

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Aiming at the scientific problem of transmission line foundation freeze-thaw failure in frozen subsoil, this paper takes an assembled foundation with cone tubes and slabs as the research object. The research method of the indoor model test and analysis is adopted, and a series of freezing tests and uplift loading tests of the model foundation are carried out under different ambient temperatures. The distribution characteristics of the temperature field and displacement field of the foundation and the relationship between the ultimate uplift capacity and temperature are analysed. Simultaneously, the failure mode of the frozen soil foundation under uplift load is also revealed. The research results show that in the freezing test, the displacement of the model foundation is less than the frost heave displacement of the surrounding foundation soil; the closer the distance from the foundation is, the stronger the frost heaving anti-restraint effect of the foundation is.In the uplift loading test of the foundation under different freezing ambient temperatures, the ultimate uplift capacity increases approximately linearly with the decrease in the ambient temperature, and the increase rate is close to 1.8 kN/℃. Under the double action of freezing and uplift, the foundation soil first exhibits local tensile failure, and with the increasing uplift load, the foundation soil gradually transitions from local tensile failure to overall shear failure. The results of this paper can provide a theoretical basis and practical experience for the application of this type of foundation in frozen subsoil.

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2022 Vol. 41, No. 2