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X-ray fluorescence spectroscopy analysis is a major method for quantitative analysis of metal elements in coal. The accuracy of background subtraction directly affects mineral metal sorting. As traditional background subtraction methods feature low background fit and large diffraction peak area errors, this study proposes an optimized method of complex wavelet transform with inverse derivative fitting for background subtraction. We obtained a simulated background spectral line through reversed peak searching and separated the overlapping peaks and valleys using Largrange's interpolation to push the simulated background close to the actual background. We then decompose and reconstruct the simulated background spectral line through complex wavelet transform to accomplish background subtraction of XRF analysis. We used the optimized method of complex wavelet with inverse derivative fitting for background subtraction of the simulated XRF spectrum and the real XRF spectrum, and compared with Continuous Wavelet and Dual-tree Complex Wavelet. The experimental results indicate that the optimized method outperforms the traditional methods in background subtraction accuracy, with less than 1 % of diffraction peak area error and less than 0.1 % of background area.

Studies on mining-induced overburden rock movement, damage and surface deformation cracks are essential to the safety production of coal mines and mining damage protection. Taking the 12203 working face of a mine of Zhengzhou Coal Group as an example, this study analyzed the evolution mechanism of overburden rock affected by mining via theoretical analysis, on-site measurement and numerical simulation. We investigated the functional relationship between back-mining distance and height of overburden development and between sufficiently destructive depth of overburden and back-mining distance. Moreover, we analyzed the distribution of the ground cracks in this geological conditions. Results show that: ① The overburden destruction of thin bedrock in thick loose layer encompasses 4 stages: the beginning, rapid increase, slow increase and stabilization; the overburden destruction height shows a Logistic relationship with back-mining distance, and a linear relationship with the thickness of the coal seam. The back-mining distance is equal to the depth of burial when the overburden is sufficiently destroyed in this geologic condition. ② In the evolution of overlying rock fracture, bedrock is more violently damaged than the loose layer. ③ The cracks in the ground are mainly tensile cracks interacting with step cracks. The cracks at the edge of the working face show an "elliptical-circular-elliptical" dynamic variation pattern along with the back mining of the working face; the development of cracks in the ground occurs at a certain distance in front of the working face. The distance of the dynamically overrunning cracks is 84.07m, and its angle is 73.15°.

The conventional pretreatment methods for mine water generally include coagulation, sedimentation (flotation), and filtration. However, large equipment footprint, long processing time and pollution from coagulants and flocculants have been limiting the further development of underground mine water treatment. In this light, we designed an underground mine water pretreatment device based on ultrasonic atomization for clarifying and pre-softening mine water so that the turbid mine water could be treated to meet the needs of underground production, firefighting, and dust reduction. We conducted indoor experiments on mine water clarification and pre-softening treatment using water and rock samples from the field mined-out area. The results show that: (1) This method can clarify black-gray turbid mine water with a large amount of solid impurities, effectively removing insoluble solid impurities in the water. (2) Ultrasonic atomization reduces the total hardness of the water by 72.24%. The milligram equivalent concentration of Ca2+ is reduced from 5.33 mg/L to 0.81 mg/L and the milligram equivalent concentration of Mg2+ drops from 5.23 mg/L to 2.13 mg/L, with little impact on pH. (3) The water from the mined-out area after ultrasonic atomization can meet the requirements of sprinkling in underground firefighting, spraying in dust reduction, the mining process of coal mining equipment, and the use of cooling water.

Deep geothermal resources in China are widely distributed, with large reserves, and have broad prospects for development and utilization. In order to investigate the seepage characteristics and evolution laws of deep high-temperature reservoirs under the condition of intermittent water injection geothermal exploitation. Using the combines method of laboratory testing and microscopic analysis, a seepage test was carried out on granite after alternating thermal and cold cycles at different temperatures, and the variation of permeability with temperature under different confining pressure were analyzed. Combining microscopic characteristics and CT scaning reconstruction results, the evolution of the microscopic pore and crack structure with temperature and cycle times was studied. The results indicated that: (1)The permeability of granite is related to temperature and cycle numbers. Under the two cooling methods, the permeability of granite gradually increases with the increase of temperature, and the permeability increases sharply when the temperature exceeds 500℃. In addition, the permeability increase under water-cooled conditions is significantly greater than that under natural cooling conditions, and the parameter changes after 10 water-cooled cycles are more significant. (2)The stress state has a significant influence on the permeability. Under the confining pressure, the internal pore and fracture structure of the specimen is closed. With the increase of confining pressure, the permeability of the granite decreases after the alternating hot and cold cycles at different temperatures, and gradually increases with the increase of osmotic pressure. (3)Under the action of high temperature cooling cycle, micro-pore cracks in granite gradually develop, temperature gradient stress causes non-uniform deformation among mineral particles, and degradation damage such as intergranular cracks, transgranular cracks and particle spalling occurs under the combined action of physical and chemical reactions such as dehydration and phase transformation. With the increase of cycle times, the number, size and connectivity of cracks further increase. The research results can provide theoretical support and technical reference for geothermal development and reservoir construction in deep dry hot rock.

The Crushed Coal Pressurized Slagging Gasification (British Gas-Lurgi, BGL) renders the use of gates obsolete and changes from dry slag discharge to liquid slag discharge, significantly improving the gasification performance. This study aims to reveal the essential structural characteristics of BGL coal gasification to further improve the performance of gasification equipment. We established the thermodynamic equilibrium model, coal gasification dynamics model and Euler multiphase flow model via numerical simulation, and validated these models. The simulation results show that 1) compared with Lurgi coal gasification, the gasification equilibrium temperature increases from 795 ℃ (Lurgi gasifier) to 1 029 ℃, and the decomposition rate of water vapor increases from 32.66 % to 93.12 %. The maximum bed temperature increases from 1 110 ℃ to 1 837 ℃, much higher than the coal ash flow temperature (1 210 ℃). This improves the gasification intensity and ensures liquid slag discharge. 2) BGL coal gasification reaction is mainly completed in the lower part of the furnace, with only a small amount of water vapor participating in the shift reaction. CH4 in the crude gas mainly comes from coal pyrolysis. 3) The fluctuation of bed surge in gasifier enhances heat and mass transfer. 4) Nozzle Jet impacts and squeezes coal char particles, forming an ellipsoidal combustion raceway extending to the central area. This becomes an important functional unit of BGL gasification, realizing primary gas distribution and providing heat for gasification layer and slag pool. 5) The liquid slag in the slag pool whirls up and down, which is beneficial to reduce carbon residue in slag and ensure smooth slag discharge.

This study investigates the influence of water accumulation in goaf on the stability of surrounding rock in a coal mine in Shanxi Province via field test, laboratory experiment and numerical simulation. Specifically, we established 3D geometric models of water bodies and goaf in water-bearing goaf based on 3D laser scanning and sonar. We then conducted permeability test on coal rock under different degrees of damage, and obtained permeability variation patterns. We then analyzed the stability of surrounding rock near water-cut goaf using numerical software by considering the dynamic changes of permeability. Results show that: ① pore water pressure exerts significant impact on the surrounding rock and overlying rock mass. ② The surrounding rock is prone to water seepage and percolation after the old goaf is flooded. ③ A large range of plastic zone with low stability is observed in the coal pillar between the goaf and roadway due to mining disturbance and water seepage. Therefore to ensure the safety of underground production, it is suggested to increase temporary underground drainage facilities for in-time water discharge to avoid flooding accidents.

In order to enhance the efficiency of tunnel support in coal mines, a study focused on the six-degree-of-freedom drill anchor robot manipulator arm and proposed an optimal trajectory planning method based on an improved grey wolf optimization algorithm. Firstly, the kinematic model of the manipulator arm was established using the D-H parameter method. Monte Carlo method was utilized for workspace analysis of the manipulator arm, and MATLAB software was employed for simulation verification; Secondly, joint-space trajectory of the manipulator arm was planned using piecewise polynomial interpolation; Finally, an improved grey wolf optimization algorithm was proposed and its performance tested for time optimization of the manipulator arm based on trajectory planning. The results show that the drill-anchoring robot manipulator meets the requirements for coal mine roadway anchoring operations; the 3-5-3 piecewise polynomial interpolation method provides smoother operation of the manipulator; and the time required for the manipulator to reach predefined trajectory points under constraint conditions is reduced by 30.40 % to 50.28 %, outperforming traditional trajectory planning methods.

Briquette production method is vital to improving its strength and permeability in physical simulation test of coal mine gas disasters. This study adopts the Horsfield dense packing theory to optimize the ratio of briquette materials and investigates the mechanical-seepage characteristics, molecular and pore structure of hot-pressed briquettes under different heating rates. Results show that as the heating rate increases, the proportion of C1s elements and the contents of alcohol, C—O/C—OH, aromatic hydrocarbons and C—C/C—H in functional groups in the molecular structure of hot-pressed briquettes show a fluctuating pattern of initial increase, subsequent decrease and final increase; the uniaxial compressive strength first increases and then decreases, while the initial permeability first decreases and then increases. The optimum heating rate is 5 ℃/min. This study offers references to improving the similarity between briquette and raw coal.

This study proposes a new algorithm to enhance the accuracy of measuring internal deformation, identify and quantify damage in rocks using digital volume correlation (DVC). This algorithm integrates the multimesh refinement technology into a mechanically regularized global DVC algorithm that incorporates nodal force equilibrium. The accuracy of different DVC algorithms was assessed through scanning experiments on particles with different sizes and digital virtual fracture models. The internal deformation and damage patterns of red sandstone were quantitatively analyzed using in-situ CT scanning during uniaxial compression experiments. The results indicate that the introduction of the mechanical regularization term reduced the measurement uncertainty of the global DVC method by 1-2 orders of magnitude. For the red sandstone specimens, the new algorithm was able to identify sub-voxel microcracks with an aperture of 0.15 voxels, while reducing the computational cost by 85.15%. The damage quantification analysis revealed that newborn cracks with a maximum aperture of 0.32 voxels occurred in the specimen when the axial stress reached 50.58% of its peak value, and these microcracks evolved into voxel-scale fractures when the stress increased to 84.27% of the peak value. The new algorithm not only improves the computational efficiency, but also demonstrates a strong capability in identifying sub-voxel scale newborn cracks, providing a novel method for quantifying internal deformation and damage in rocks.

The roof of the main coal seam in Tingnan Coal Mine of Binchang Mining Area is a typical thick sandstone aquifer structure, and the multi-dynamic disaster outburst problem of rock burst, water damage and gas. Based on the analysis of the field measured data, two typical disaster chains of' rock burst-water disaster and rock burst-gas disaster' in Tingnan Coal Mine were obtained. The disaster-causing mechanism of the disaster chain was studied through laboratory tests, and the principle of coordinated prevention and control of disasters was formulated. The coordinated prevention and control methods of roof disasters in extremely thick sandstone aquifers were designed, including two stages of pre-mining and mining, as well as the overall prevention and control of source chain breaking and systematic prevention and control of isolated chain breaking, and were applied in Tingnan Coal Mine. The results show that with the increase of impact amplitude, the ultimate bearing capacity of dynamic damaged coal and rock mass decreases, and the impact leads to the damage and weakening of roof, which communicates with the thick sandstone aquifer. The porosity of sandstone samples after strong impact is 8.23 %, which is 34.48 % higher than that without impact. The occurrence of rock burst increases the fracture of rock mass and provides a channel for gas escape. Through the cooperative prevention and control technology of roof disaster in extremely thick sandstone aquifer, the average resistance of the support is 35.03 MPa, and there is no obvious stress surge. The water inflow of the working face is stable at 250~280 m3/h, and the methane emission fluctuates at the level of 0.2 %. The research can provide basic theoretical support for the prevention and control of multi-dynamic disasters in coal mines in Binchang mining area, help to achieve efficient prevention of coal mine disaster risks, and promote the progress of multi-disaster collaborative prevention and control technology.

In order to reveal the characteristics of overlying rock migration and mining pressure manifestation in deep well long wall paste filling mining, the 1123 filling working face of Gucheng Coal Mine was taken as the research object, and geological radar, multi-point displacement meter, microseismic monitoring and other methods were used for research. The research results show that: (1) The range of influence of advanced mining in the working face is 33~37 m, and the range of influence of advanced mining on the coal pillar side of the intake roadway increases to 50 m. The range of influence of advanced mining in the fault affected area of the return airway shows an increasing trend; (2) The microseismic events in the filling working face exhibit distribution characteristics such as asymmetry, low energy, low vertical development height, concentrated bottom plate, and dispersed top plate, with a majority of small energy events; (3) The top plate of the filling working face is mainly deformed and sunk, without large-scale damage or major energy events, indicating that filling mining reduces the migration mode and strength of the overlying rock layers; (4) When the progress of filling the working face reached 165.6 meters, there was no significant subsidence on the surface, indicating that filling mining has a good inhibitory effect on surface subsidence.

Changes of wind barrier angles exert significant effect on the occurrence of low oxygen gas in the upper corner. Taking the 100510 working face of a mine in Shanxi Province as example, this study uses Ansys Fluent software to build a gas migration model of the working face to simulate the occurrence patterns of low oxygen gas in the upper corner under different wind barrier angles, and verifies the model through field measurement. Results show that setting wind barrier could increase wind speed in the upper corner, which offers a solution to the low oxygen problem in upper corner. The optimal treatment of low oxygen in the upper corner is realized with wind barrier angle set at 60° at the position 5m away from the return air channeling. This study provides implications for solutions to the low oxygen issue in the upper corner and thereby ensure safety production.

This study aims to investigate the crack propagation mechanism of directional hydraulic fracturing of coal mine roof and explore the relationship between fracture criteria. By drawing on fracture mechanics, we propose a hydraulic fracturing mechanical model of drilling and derive the calculation formulas of crack initiation angle and critical water pressure under different fracture criteria to analyze the impact of different variables on crack initiation angle and critical water pressure. Results show that: ① the increase of stress difference leads to a gradual increase of the crack initiation angle; ② the effect of prefab crack length and borehole radius on crack initiation angle is caused by two factors. The crack initiation angle increases with the decrease in the ratio of these two factors; ③ Poisson's ratio has limited effect on crack initiation angle; ④ under high stress difference and low prefab crack inclination angle, the critical water pressure decreases with the increase of stress difference and inclination angle, and vice versa; ⑤ the increase of borehole radius and prefabricated crack length would significantly reduce the critical water pressure. The two criteria yield different calculation results as ① prefab crack length and borehole radius would impact crack initiation angle; ② principal stress difference and prefab crack angle would impact critical water pressure. The theoretical calculation results and the experimental results show a good fit. The present study offers reference to the hydraulic fracturing site construction.

Coal mine solid waste is an industrial solid waste generated during coal mining, washing, and utilization. Despite a recent increase in its utilization rate in China, it still possesses substantial storage, which not only encroaches on land resources, but also causes serious environmental pollution. This paper reviews existing studies on the environmental impact of coal mine solid waste that were published in CNKI, Web of Science, and Google Scholar databases between 2014 and 2024. Results reveal that the environmental impact of coal mine solid waste mainly includes: ① the emitted gases such as polycyclic aromatic hydrocarbons and SO2 and the fine particulate matter generated during the storage process of coal mine solid waste could pollute the atmosphere; ② the heavy metals in coal mine solid waste would pollute the surrounding groundwater during the leaching process; ③ the heavy metals such as Cd, Cr, Hg in coal mine solid waste could migrate and be released to the surrounding soil through weathering and leaching, causing serious heavy metal pollution in soil. Given the current research progress in the comprehensive utilization and treatment of coal mine solid waste, this study proposes future research foci by drawing on the current regulations in mining safety, environmental protection and monitoring.

This study proposes a layout scheme for external staggered roadway and builds a mechanical model for unconventional coal pillars with staggered positions as a solution to the waste of resources caused by the large coal pillar size between the sections of 1301 fully mechanized top coal caving face and the difficulty in supporting the roadway in Xinjulong Coal Mine. We analyzed the stress environment and characteristics of the extreme equilibrium zone of unconventional coal pillars using the limit equilibrium theory. For the bottom roadway, the reasonable horizontal staggered distance in the lower section is set at 3.0 meters after considering its stress environment at different horizontal offset conditions and the distribution of elastic strain energy density of the section coal pillars. Meanwhile, we proposed a joint support scheme for adjacent roadways between sections. We simulated and verified the original support scheme and the joint support scheme in actual geological conditions during the mining stage of the continuous working face. Results show that the joint support scheme for adjacent roadways between sections outperforms the original support scheme. The peak stress of the joint support scheme reduced from 80 MPa to 64 MPa, with a reduction rate of 20 %, indicating that the it is more effective in controlling the surrounding rock of the roadway. Moreover, the unit reserved area of coal pillars in the section was 111.5 m2, which is a 34.4 % reduction from 170 m2 in the original support scheme. This study offers implications for reducing the reserved size of coal pillars in fewer sections and improving the coal recovery rate.

The CO2 flooding and sequestration technology displays significant effect in CO2 emission reduction and oil displacement, which could alleviate global warming, achieve China's dual carbon goals and sustainable development. This study reviews existing CO2-EOR projects with 100 000 tons and above, with a focus on domestic engineering cases. Specifically, we analyzed such major issues as technology matching, safety monitoring, economic constraints and legal policy preference in implementing CO2-EOR projects in China, and discussed its future prospects. The implementation of this technology shows a late start in China and still lags behind those in Europe and the USA due to a lack of large-scale commercialized projects. By drawing on foreign scholarly efforts, we need to optimize the whole process of CO2 flooding and storage through the introduction of artificial intelligence, upgrade CO2 leakage risk identification and control as well as CO2 dynamic monitoring to accelerate the commercialization and industrialization of large-scale CO2-EOR projects.

To extract and transport the residual heat from mine return air over long distances, and considering the high moisture content and large volume of return air, along with the heat transfer theory of heat pipe systems, this paper designs a gravity-type split heat pipe air supply system for mine return air heat recovery. This system can transfer the recovered low-temperature residual heat to the mine's fresh air platform for preheating, meeting the anti-freezing heat demand at the mine shaft entrance and successfully realizing the extraction of low-temperature heat sources for industrial application. Through continuous three-day testing of certain heat exchange modules, the results show that the system can raise the temperature of low-temperature fresh air by 12℃ to 16.5℃, achieving the goal of preventing freezing at the shaft entrance. These findings demonstrate practical industrial application value.

Understanding the thermal conductivity of granite is critical for many geological and deep engineering applications. The heated granite was subjected to air-, water-, and liquid nitrogen (LN2-) coolings in this context. The transient hot-wire technique was used to determine the equivalent thermal conductivity (ETC) of the granite before and after treatment. The deterioration mechanism of ETC is analyzed from the meso-perspective. Finally, the numerical model is used to quantitatively study the impact of cooling rate on the microcrack propagation and heat conduction characteristics of granite. The results show that the ETC of granite is not only related to the heating temperature, but also affected by the cooling rate. The ETC of granite decreases nonlinearly with increasing heating temperature. A faster cooling rate causes a greater decrease in ETC at the same heating temperature. The higher the heating temperature, the stronger the influence of cooling rate on ETC. The main explanation for the decrease in ETC of granite is the increase in porosity and microcrack density produced by the formation and propagation of pore structure and microcracks during heating and cooling. Further analysis displays that the damage of granite at the heating stage is induced by the difference in thermal expansion and elastic properties of mineral particles. At the cooling stage, the faster cooling rate causes a higher temperature gradient, which in turn produces greater thermal stress. As a result, it not only causes new cracks in the granite, but also aggravates the damage at the heating stage, which induces a further decrease in the heat conduction performance of granite, and this scenario is more obvious at higher temperatures.

Laser scanning technology has been widely used in landslide aspects. However, the existing deformation analysis based on terrain laser scanners can only provide limited information, which is insufficient for understanding landslide kinematics and failure mechanisms. To overcome this limitation, this paper proposes an automated method for processing point clouds collected in landslide physical modeling. This method allows the acquisition of quantitative three-dimensional (3D) deformation field information. The results show the organized and spatially related point cloud segmentation in terms of spherical targets. The segmented point clouds can be fitted to determine the locations of all preset targets and their corresponding location changes. The proposed method has been validated based on theoretical analysis and numerical and physical tests, which indicates that it can batch-process massive data sets with high computational efficiency and good noise resistance. Compared to existing methods, this method shows a significant potential for understanding landslide kinematics and failure mechanisms and advancing the application of 3D laser scanning in geotechnical modeling.

The prediction of slope stability is considered as one of the critical concerns in geotechnical engineering. Conventional stochastic analysis with spatially variable slopes is time-consuming and highly computation-demanding. To assess the slope stability problems with a more desirable computational effort, many machine learning (ML) algorithms have been proposed. However, most ML-based techniques require that the training data must be in the same feature space and have the same distribution, and the model may need to be rebuilt when the spatial distribution changes. This paper presents a new ML-based algorithm, which combines the principal component analysis (PCA)-based neural network (NN) and transfer learning (TL) techniques (i.e. PCA–NN–TL) to conduct the stability analysis of slopes with different spatial distributions. The Monte Carlo coupled with finite element simulation is first conducted for data acquisition considering the spatial variability of cohesive strength or friction angle of soils from eight slopes with the same geometry. The PCA method is incorporated into the neural network algorithm (i.e. PCA-NN) to increase the computational efficiency by reducing the input variables. It is found that the PCA-NN algorithm performs well in improving the prediction of slope stability for a given slope in terms of the computational accuracy and computational effort when compared with the other two algorithms (i.e. NN and decision trees, DT). Furthermore, the PCA–NN–TL algorithm shows great potential in assessing the stability of slope even with fewer training data.

The abrupt occurrence of the Zhongbao landslide is totally unexpected, resulting in the destruction of local infrastructure and river blockage. To review the deformation history of the Zhongbao landslide and prevent the threat of secondary disasters, the small baseline subsets (SBAS) technology is applied to process 59 synthetic aperture radar (SAR) images captured from Sentinel-1A satellite. Firstly, the time series deformation of the Zhongbao landslide along the radar line of sight (LOS) direction is calculated by SBAS technology. Then, the projection transformation is conducted to determine the slope displacement. Furthermore, the Hurst exponent of the surface deformation along the two directions is calculated to quantify the hidden deformation development trend and identify the unstable deformation areas. Given the suddenness of the Zhongbao landslide failure, the multi-temporal interferometric synthetic aperture radar (InSAR) technology is the ideal tool to obtain the surface deformation history without any monitoring equipment. The obtained deformation process indicates that the Zhongbao landslide is generally stable with slow creep deformation before failure. Moreover, the Hurst exponent distribution on the landslide surface in different time stages reveals more deformation evolution information of the Zhongbao landslide, with partially unstable areas detected before the failure. Two potential unstable areas after the Zhongbao landslide disaster are revealed by the Hurst exponent distribution and verified by the GNSS monitoring results and deformation mechanism discussion. The method combining SBAS-InSAR and Hurst exponent proposed in this study could help prevent and control secondary landslide disasters.

The influences of biological, chemical, and flow processes on soil structure through microbially induced carbonate precipitation (MICP) are not yet fully understood. In this study, we use a multi-level thresholding segmentation algorithm, genetic algorithm (GA) enhanced Kapur entropy (KE) (GAE-KE), to accomplish quantitative characterization of sandy soil structure altered by MICP cementation. A sandy soil sample was treated using MICP method and scanned by the synchrotron radiation (SR) micro-CT with a resolution of 6.5 μm. After validation, tri-level thresholding segmentation using GAE-KE successfully separated the precipitated calcium carbonate crystals from sand particles and pores. The spatial distributions of porosity, pore structure parameters, and flow characteristics were calculated for quantitative characterization. The results offer pore-scale insights into the MICP treatment effect, and the quantitative understanding confirms the feasibility of the GAE-KE multi-level thresholding segmentation algorithm.

Since the impoundment of Three Gorges Reservoir (TGR) in 2003, numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall. One case is the Outang landslide, a large-scale and active landslide, on the south bank of the Yangtze River. The latest monitoring data and site investigations available are analyzed to establish spatial and temporal landslide deformation characteristics. Data mining technology, including the two-step clustering and Apriori algorithm, is then used to identify the dominant triggers of landslide movement. In the data mining process, the two-step clustering method clusters the candidate triggers and displacement rate into several groups, and the Apriori algorithm generates correlation criteria for the cause-and-effect. The analysis considers multiple locations of the landslide and incorporates two types of time scales: long-term deformation on a monthly basis and short-term deformation on a daily basis. This analysis shows that the deformations of the Outang landslide are driven by both rainfall and reservoir water while its deformation varies spatiotemporally mainly due to the difference in local responses to hydrological factors. The data mining results reveal different dominant triggering factors depending on the monitoring frequency: the monthly and bi-monthly cumulative rainfall control the monthly deformation, and the 10-d cumulative rainfall and the 5-d cumulative drop of water level in the reservoir dominate the daily deformation of the landslide. It is concluded that the spatiotemporal deformation pattern and data mining rules associated with precipitation and reservoir water level have the potential to be broadly implemented for improving landslide prevention and control in the dam reservoirs and other landslide-prone areas.

To achieve the loading of the stress path of hard rock, the spherical discrete element model (DEM) and the new flexible membrane technology were utilized to realize the transient loading of three principal stresses with arbitrary magnitudes and orientations. Furthermore, based on the deep tunnel of China Jinping Underground Laboratory II (CJPL-II), the deformation and fracture evolution characteristics of deep hard rock induced by excavation stress path were analyzed, and the mechanisms of transient loading-unloading and stress rotation-induced fractures were revealed from a mesoscopic perspective. The results indicated that the stress–strain curve exhibits different trends and degrees of sudden changes when subjected to transient changes in principal stress, accompanied by sudden changes in strain rate. Stress rotation induces spatially directional deformation, resulting in fractures of different degrees and orientations, and increasing the degree of deformation anisotropy. The correlation between the degree of induced fracture and the unloading magnitude of minimum principal stress, as well as its initial level is significant and positive. The process of mechanical response during transient unloading exhibits clear nonlinearity and directivity. After transient unloading, both the minimum principal stress and minimum principal strain rate decrease sharply and then tend to stabilize. This occurs from the edge to the interior and from the direction of the minimum principal stress to the direction of the maximum principal stress on the ε1-ε3 plane. Transient unloading will induce a tensile stress wave. The ability to induce fractures due to changes in principal stress magnitude, orientation and rotation paths gradually increases. The analysis indicates a positive correlation between the abrupt change amplitude of strain rate and the maximum unloading magnitude, which is determined by the magnitude and rotation of principal stress. A high tensile strain rate is more likely to induce fractures under low minimum principal stress.

The geometric properties of fracture surfaces significantly influence shear-seepage in rock fractures, introducing complexities to fracture modelling. The present study focuses on the hydro-mechanical behaviours of rough rock fractures during shear-seepage processes to reveal how dilatancy and fracture asperities affect these phenomena. To achieve this, an improved shear-flow model (SFM) is proposed with the incorporation of dilatancy effect and asperities. In particular, shear dilatancy is accounted for in both the elastic and plastic stages, in contrast to some existing models that only consider it in the elastic stage. Depending on the computation approaches for the peak dilatancy angle, three different versions of the SFM are derived based on Mohr-Coulomb, joint roughness coefficient-joint compressive strength (JRC-JCS), and Grasselli's theories. Notably, this is a new attempt that utilizes Grasselli's model in shear-seepage analysis. An advanced parameter optimization method is introduced to accurately determine model parameters, addressing the issue of local optima inherent in some conventional methods. Then, model performance is evaluated against existing experimental results. The findings demonstrate that the SFM effectively reproduces the shear-seepage characteristics of rock fracture across a wide range of stress levels. Further sensitivity analysis reveals how dilatancy and asperity affect hydraulic properties. The relation between hydro-mechanical properties (dilatancy displacement and hydraulic conductivity) and asperity parameters is analysed. Several profound understandings of the shear-seepage process are obtained by exploring the phenomenon under various conditions.

Non-contact remote sensing techniques, such as terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) photogrammetry, have been globally applied for landslide monitoring in high and steep mountainous areas. These techniques acquire terrain data and enable ground deformation monitoring. However, practical application of these technologies still faces many difficulties due to complex terrain, limited access and dense vegetation. For instance, monitoring high and steep slopes can obstruct the TLS sightline, and the accuracy of the UAV model may be compromised by absence of ground control points (GCPs). This paper proposes a TLS- and UAV-based method for monitoring landslide deformation in high mountain valleys using traditional real-time kinematics (RTK)-based control points (RCPs), low-precision TLS-based control points (TCPs) and assumed control points (ACPs) to achieve high-precision surface deformation analysis under obstructed vision and impassable conditions. The effects of GCP accuracy, GCP quantity and automatic tie point (ATP) quantity on the accuracy of UAV modeling and surface deformation analysis were comprehensively analyzed. The results show that, the proposed method allows for the monitoring accuracy of landslides to exceed the accuracy of the GCPs themselves by adding additional low-accuracy GCPs. The proposed method was implemented for monitoring the Xinhua landslide in Baoxing County, China, and was validated against data from multiple sources.

In current practice of bolt reaming and anchoring of roadways in soft coal and rock mass, resin cartridges bend easily under the strong pushing and stirring of bolts, and the resin accumulates in the bolt-reamed area and does not participate in the stirring. As a result, bolts encounter high drilling resistance and cannot reach the bottom of drillholes. The effective anchorage length is far less than the actual anchorage length. Bolts are not centered, and the shear is misaligned at the joint surface in the reaming area, which leads to cracking of the whole anchoring solid and large shear deformation of bolts. This study systematically analyzes the characteristics of roadway bolt reaming and anchoring. The influences of resin stirring force, bolt pull-out force, and reaming–anchoring solid strength on reaming–anchoring performance were analyzed theoretically. The main purpose is to develop a device that enhances reaming and anchoring. The mechanism through which the device strengthens the reaming–anchoring solid was analyzed theoretically. Numerical simulation and experiments were carried out to verify the improved performance of the small-pore reaming and anchoring using the proposed technology. The results showed that the stirring migration rate of the resin cartridge is greatly improved by adding the device to bolts. The reaction rate of the anchoring mixture, stirring pressure, pull-out force of the reaming and anchoring system, bolt concentricity, and shear and compressive strengths of the anchoring solid are also enhanced in the reaming area. This ensures that the resin cartridge in the reaming area is completely stirred, which greatly improves the shear resistance of the reaming–anchoring solid. Meanwhile, the drilling performance, torsional force, and stirring efficiency of bolts are maximized and prevail over those of conventional bolts.

The accuracy of landslide susceptibility prediction (LSP) mainly depends on the precision of the landslide spatial position. However, the spatial position error of landslide survey is inevitable, resulting in considerable uncertainties in LSP modeling. To overcome this drawback, this study explores the influence of positional errors of landslide spatial position on LSP uncertainties, and then innovatively proposes a semi-supervised machine learning model to reduce the landslide spatial position error. This paper collected 16 environmental factors and 337 landslides with accurate spatial positions taking Shangyou County of China as an example. The 30–110 m error-based multilayer perceptron (MLP) and random forest (RF) models for LSP are established by randomly offsetting the original landslide by 30, 50, 70, 90 and 110 m. The LSP uncertainties are analyzed by the LSP accuracy and distribution characteristics. Finally, a semi-supervised model is proposed to relieve the LSP uncertainties. Results show that: (1) The LSP accuracies of error-based RF/MLP models decrease with the increase of landslide position errors, and are lower than those of original data-based models; (2) 70 m error-based models can still reflect the overall distribution characteristics of landslide susceptibility indices, thus original landslides with certain position errors are acceptable for LSP; (3) Semi-supervised machine learning model can efficiently reduce the landslide position errors and thus improve the LSP accuracies.

Polymer-blend geocell sheets (PBGS) have been developed as substitute materials for manufacturing geocells. Various attempts have been made to test and predict the behaviors of commonly used geogrids, geotextiles, geomembranes, and geocells. However, the elastic-viscoplastic behaviors of novel-developed geocell sheets are still poorly understood. Therefore, this paper investigates the elastic-viscoplastic behaviors of PBGS to gain a comprehensive understanding of their mechanical properties. Furthermore, the tensile load-strain history under various loading conditions is simulated by numerical calculation for widespread utilization. To achieve this goal, monotonic loading tests, short-term creep and stress relaxation tests, and multi-load-path tests (also known as arbitrary loading history tests) are performed using a universal testing machine. The results are simulated using the nonlinear three-component (NLTC) model, which consists of three nonlinear components, i.e. a hypo-elastic component, a nonlinear inviscid component, and a nonlinear viscid component. The experimental and numerical results demonstrate that PBGS exhibit significant elastic-viscoplastic behavior that can be accurately predicted by the NLTC model. Moreover, the tensile strain rates significantly influence the tensile load, with higher strain rates resulting in increased tensile loads and more linear load-strain curves. Also, parametric analysis of the rheological characteristics reveals that the initial tensile strain rates have negligible impact on the results. The rate-sensitivity coefficient of PBGS is approximately 0.163, which falls within the typical range observed in most geosynthetics.

Deformation analysis is fundamental in geotechnical modeling. Nevertheless, there is still a lack of an effective method to obtain the deformation field under various experimental conditions. In this study, we introduce a process–based physical modeling of a pile–reinforced reservoir landslide and present an improved deformation analysis involving large strains and water effects. We collect multi–period point clouds using a terrain laser scanner and reconstruct its deformation field through a point cloud processing workflow. The results show that this method can accurately describe the landslide surface deformation at any time and area by both scalar and vector fields. The deformation fields in different profiles of the physical model and different stages of the evolutionary process provide adequate and detailed landslide information. We analyze the large strain upstream of the pile caused by the pile installation and the consequent violent deformation during the evolutionary process. Furthermore, our method effectively overcomes the challenges of identifying targets commonly encountered in geotechnical modeling where water effects are considered and targets are polluted, which facilitates the deformation analysis at the wading area in a reservoir landslide. Eventually, combining subsurface deformation as well as numerical modeling, we comprehensively analyze the kinematics and failure mechanisms of this complicated object involving landslides and pile foundations as well as water effects. This method is of great significance for any geotechnical modeling concerning large-strain analysis and water effects.

In light of the escalating global energy imperatives, mining of challenging-to-access resources, such as steeply inclined extra-thick coal seams (SIEC), has emerged as one of the future trends within the domain of energy advancement. However, there is a risk of gas and coal spontaneous combustion coupling disasters (GCC) within the goaf of SIEC due to the complex goaf structure engendered by the unique mining methodologies of SIEC. To ensure that SIEC is mined safely and efficiently, this study conducts research on the GCC within the goaf of SIEC using field observation, theoretical analysis, and numerical modeling. The results demonstrate that the dip angle, the structural dimensions in terms of width-to-length ratio, and compressive strength of the overlying rock are the key factors contributing to the goaf instability of SIEC. The gangue was asymmetrically filled, primarily accumulating within the central and lower portions of the goaf, and the filling height increased proportionally with the advancing caving height, the expansion coefficient, and the thickness of the surrounding rock formation. The GCC occurs in the goaf of SIEC, with an air-return side range of 41 m and an air-intake side range of 14 m, at the intersection area of the “”-shaped gas concentration distribution (gas explosion). The optimal nitrogen flow rate is 1000 m3/h with an injection port situated 25 m away from the working face for the highest nitrogen diffusion efficacy and lowest risk of gas explosion, coal spontaneous combustion, and GCC. It has significant engineering applications for ensuring the safe mining of SIEC threatened by the GCC.

Landslides are destructive natural disasters that cause catastrophic damage and loss of life worldwide. Accurately predicting landslide displacement enables effective early warning and risk management. However, the limited availability of on-site measurement data has been a substantial obstacle in developing data-driven models, such as state-of-the-art machine learning (ML) models. To address these challenges, this study proposes a data augmentation framework that uses generative adversarial networks (GANs), a recent advance in generative artificial intelligence (AI), to improve the accuracy of landslide displacement prediction. The framework provides effective data augmentation to enhance limited datasets. A recurrent GAN model, RGAN-LS, is proposed, specifically designed to generate realistic synthetic multivariate time series that mimics the characteristics of real landslide on-site measurement data. A customized moment-matching loss is incorporated in addition to the adversarial loss in GAN during the training of RGAN-LS to capture the temporal dynamics and correlations in real time series data. Then, the synthetic data generated by RGAN-LS is used to enhance the training of long short-term memory (LSTM) networks and particle swarm optimization-support vector machine (PSO-SVM) models for landslide displacement prediction tasks. Results on two landslides in the Three Gorges Reservoir (TGR) region show a significant improvement in LSTM model prediction performance when trained on augmented data. For instance, in the case of the Baishuihe landslide, the average root mean square error (RMSE) increases by 16.11%, and the mean absolute error (MAE) by 17.59%. More importantly, the model's responsiveness during mutational stages is enhanced for early warning purposes. However, the results have shown that the static PSO-SVM model only sees marginal gains compared to recurrent models such as LSTM. Further analysis indicates that an optimal synthetic-to-real data ratio (50% on the illustration cases) maximizes the improvements. This also demonstrates the robustness and effectiveness of supplementing training data for dynamic models to obtain better results. By using the powerful generative AI approach, RGAN-LS can generate high-fidelity synthetic landslide data. This is critical for improving the performance of advanced ML models in predicting landslide displacement, particularly when there are limited training data. Additionally, this approach has the potential to expand the use of generative AI in geohazard risk management and other research areas.

Historically, landslides have been the primary type of geological disaster worldwide. Generally, the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations. Moreover, the stability of reservoir banks changes with the long-term dynamics of external disaster-causing factors. Thus, assessing the time-varying reliability of reservoir landslides remains a challenge. In this paper, a machine learning (ML) based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction. This study systematically investigated the prediction performances of three ML algorithms, i.e. multilayer perceptron (MLP), convolutional neural network (CNN), and long short-term memory (LSTM). Additionally, the effects of the data quantity and data ratio on the predictive power of deep learning models are considered. The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides. The CNN model outperforms both the MLP and LSTM models in predicting the failure probability. Furthermore, selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.

Granitic veins (GVs) have a significant influence on the mechanical responses of tunnels excavated in granitic strata. Distinguishing the mechanical properties of host granites (HGs), GVs and vein-granite interfaces (VGIs) is critical. For this, this paper analyzed the mechanical behaviors and rupture processes of typical HG, GV, and VGI samples under uniaxial compression condition. For the rocks studied, although the linear axial stress‒strain relation can be identified and the deformation modulus can be determined, the transverse deformation developed nonlinearly with axial stress. As a result, the instantaneous Poisson's ratio increases continuously and may even exceed 0.5, making it extremely difficult to accurately determine the Poisson's ratio. In addition, the studied GV samples were found to be significantly brittle, indicating that large-scale GVs cannot be ignored when assessing rockburst hazards in granitic strata with brittle GVs. In terms of the rupture process, the HG and GV samples were gradually damaged by the formation of small-scale cracks and then ruptured by large cracks formed from small-scale cracks, whereas the VGI samples ruptured along large cracks with significant energy release. By examining the characteristic stress thresholds of these three granites, it is noted that the crack closure stress σcc exceeds both the crack initiation stress σci and the crack damage stress σcd for the HG and VGI samples. The transverse damage to a tested sample appears to be significantly greater than the axial damage, which is essentially related to the rock grain size and grain size distribution.

This paper aims to investigate the role of bi-directional shear in the mechanical behaviour of granular materials and macro-micro relations by conducting experiments and discrete element method (DEM) modelling. The bi-directional shear consists of a static shear consolidation and subsequent shear under constant vertical stress and constant volume conditions. A side wall node loading method is used to exert bi-directional shear of various angles. The results show that bi-directional shear can significantly influence the mechanical behaviour of granular materials. However, the relationship between bi-directional shear and mechanical responses relies on loading conditions, i.e. constant vertical stress or constant volume conditions. The stress states induced by static shear consolidation are affected by loading angles, which are enlarged by subsequent shear, consistent with the relationship between bi-directional shear and principal stresses. It provides evidence for the dissipation of stresses accompanying static liquefaction of granular materials. The presence of bi-directional principal stress rotation (PSR) is demonstrated, which evidences why the bi-directional shear of loading angles with components in two directions results in faster dissipations of stresses with static liquefaction. Contant volume shearing leads to cross-anisotropic stress and fabric at micro-contacts, but constant vertical stress shearing leads to complete anisotropic stress and fabric at micro-contacts. It explains the differentiating relationship between stress-strain responses and fabric anisotropy under these two conditions. Micromechanical signatures such as the slip state of micro-contacts and coordination number are also examined, providing further insights into understanding granular behaviour under bi-directional shear.

When assessing the sliding stability of a concrete dam, the influence of large-scale asperities in the sliding plane is often ignored due to limitations of the analytical rigid body assessment methods provided by current dam assessment guidelines. However, these asperities can potentially improve the load capacity of a concrete dam in terms of sliding stability. Although their influence in a sliding plane has been thoroughly studied for direct shear, their influence under eccentric loading, as in the case of dams, is unknown. This paper presents the results of a parametric study that used finite element analysis (FEA) to investigate the influence of large-scale asperities on the load capacity of small buttress dams. By varying the inclination and location of an asperity located in the concrete-rock interface along with the strength of the rock foundation material, transitions between different failure modes and correlations between the load capacity and the varied parameters were observed. The results indicated that the inclination of the asperity had a significant impact on the failure mode. When the inclination was 30° and greater, interlocking occurred between the dam and foundation and the governing failure modes were either rupture of the dam body or asperity. When the asperity inclination was significant enough to provide interlocking, the load capacity of the dam was impacted by the strength of the rock in the foundation through influencing the load capacity of the asperity. The location of the asperity along the concrete-rock interface did not affect the failure mode, except for when the asperity was located at the toe of the dam, but had an influence on the load capacity when the failure occurred by rupture of the buttress or by sliding. By accounting for a single large-scale asperity in the concrete-rock interface of the analysed dam, a horizontal load capacity increase of 30%–160% was obtained, depending on the inclination and location of the asperity and the strength of the foundation material.

To investigate the long-term stability of deep rocks, a three-dimensional (3D) time-dependent model that accounts for excavation-induced damage and complex stress state is developed. This model comprises three main components: a 3D viscoplastic isotropic constitutive relation that considers excavation damage and complex stress state, a quantitative relationship between critical irreversible deformation and complex stress state, and evolution characteristics of strength parameters. The proposed model is implemented in a self-developed numerical code, i.e. CASRock. The reliability of the model is validated through experiments. It is indicated that the time-dependent fracturing potential index (ξTFPI) at a given time during the attenuation creep stage shows a negative correlation with the extent of excavation-induced damage. The time-dependent fracturing process of rock demonstrates a distinct interval effect of the intermediate principal stress, thereby highlighting the 3D stress-dependent characteristic of the model. Finally, the influence of excavation-induced damage and intermediate principal stress on the time-dependent fracturing characteristics of the surrounding rocks around the tunnel is discussed.

The travel time of rock compressional waves is an essential parameter used for estimating important rock properties, such as porosity, permeability, and lithology. Current methods, like wireline logging tests, provide broad measurements but lack finer resolution. Laboratory-based rock core measurements offer higher resolution but are resource-intensive. Conventionally, wireline logging and rock core measurements have been used independently. This study introduces a novel approach that integrates both data sources. The method leverages the detailed features from limited core data to enhance the resolution of wireline logging data. By combining machine learning with random field theory, the method allows for probabilistic predictions in regions with sparse data sampling. In this framework, 12 parameters from wireline tests are used to predict trends in rock core data. The residuals are modeled using random field theory. The outcomes are high-resolution predictions that combine both the predicted trend and the probabilistic realizations of the residual. By utilizing unconditional and conditional random field theories, this method enables unconditional and conditional simulations of the underlying high-resolution rock compressional wave travel time profile and provides uncertainty estimates. This integrated approach optimizes the use of existing core and logging data. Its applicability is confirmed in an oil project in West China.

The presence of discontinuities (e.g. faults, fractures, veins, layering) in crystalline rocks can be challenging for seismic interpretations because the wide range of their size, orientation, and intensity, which controls the mechanical properties of the rock and elastic wave propagation, resulting in equally varying seismic responses at different scales. The geometrical characterisation of adjacent outcrop discontinuity networks allows a better understanding of the nature of the subsurface rocks and aids seismic interpretation. In this study, we characterise the discontinuity network of the Balmuccia peridotite (BP) in the Ivrea–Verbano Zone (IVZ), northwestern Italy. This geological body is the focus of the Drilling the Ivrea–Verbano zonE (DIVE), an international continental scientific drilling project, and two active seismic surveys, SEismic imaging of the Ivrea ZonE (SEIZE) and high-resolution SEIZE (Hi-SEIZE), which aim to resolve the subsurface structure of the DIVE drilling target through high-resolution seismic imaging. For fracture characterisation, we developed two drone-based digital outcrop models (DOMs) at two different resolutions (10−3–10 m and 10−1–103 m), which allowed us to quantitatively characterise the orientation, size, and intensity of the main rock discontinuities. These properties affect the seismic velocity and consequently the interpretation of the seismic data. We found that (i) the outcropping BP discontinuity network is represented by three more sets of fractures with respect to those reported in the literature; (ii) the discontinuity sizes follow a power-law distribution, indicating similarity across scales, and (iii) discontinuity intensity is not uniformly distributed along the outcrop. Our results help to explain the seismic behaviour of the BP detected by the SEIZE survey, suggesting that the low P-wave velocities observed can be related to the discontinuity network, and provide the basic topological parameters (orientation, density, distribution, and aperture) of the fracture network unique to the BP. These, in turn, can be used for interpretation of the Hi-SEIZE seismic survey and forward modelling of the seismic response.

The accurate prediction of the friction angle of clays is crucial for assessing slope stability in engineering applications. This study addresses the importance of estimating the friction angle and presents the development of four soft computing models: YJ-FPA-MLPnet, YJ-CRO-MLPnet, YJ-ACOC-MLPnet, and YJ-CSA-MLPnet. First of all, the Yeo-Johnson (YJ) transformation technique was used to stabilize the variance of data and make it more suitable for parametric statistical models that assume normality and equal variances. This technique is expected to improve the accuracy of friction angle prediction models. The friction angle prediction models then utilized multi-layer perceptron neural networks (MLPnet) and metaheuristic optimization algorithms to further enhance performance, including flower pollination algorithm (FPA), coral reefs optimization (CRO), ant colony optimization continuous (ACOC), and cuckoo search algorithm (CSA). The prediction models without the YJ technique, i.e. FPA-MLPnet, CRO-MLPnet, ACOC-MLPnet, and CSA-MLPnet, were then compared to those with the YJ technique, i.e. YJ-FPA-MLPnet, YJ-CRO-MLPnet, YJ-ACOC-MLPnet, and YJ-CSA-MLPnet. Among these, the YJ-CRO-MLPnet model demonstrated superior reliability, achieving an accuracy of up to 83% in predicting the friction angle of clay in practical engineering scenarios. This improvement is significant, as it represents an increase from 1.3% to approximately 20% compared to the models that did not utilize the YJ transformation technique.

Soil tensile strength is a critical parameter governing the initiation and propagation of tensile cracking. This study proposes an eco-friendly approach to improve the tensile behavior and crack resistance of clayey soils. To validate the feasibility and efficacy of the proposed approach, direct tensile tests were employed to determine the tensile strength of the compacted soil with different W-OH treatment concentrations and water contents. Desiccation tests were also performed to evaluate the effectiveness of W-OH treatment in enhancing soil tensile cracking resistance. During this period, the effects of W-OH treatment concentration and water content on tensile properties, soil suction and microstructure were investigated. The tensile tests reveal that W-OH treatment has a significant impact on the tensile strength and failure mode of the soil, which not only effectively enhances the tensile strength and failure displacement, but also changes the brittle failure behavior into a more ductile quasi-brittle failure behavior. The suction measurements and mercury intrusion porosimetry (MIP) tests show that W-OH treatment can slightly reduce soil suction by affecting skeleton structure and increasing macropores. Combined with the microstructural analysis, it becomes evident that the significant improvement in soil tensile behavior through W-OH treatment is mainly attributed to the W-OH gel's ability to provide additional binding force for bridging and encapsulating the soil particles. Moreover, desiccation tests demonstrate that W-OH treatment can significantly reduce or even inhibit the formation of soil tensile cracking. With the increase of W-OH treatment concentration, the surface crack ratio and total crack length are significantly reduced. This study enhances a fundamental understanding of eco-polymer impacts on soil mechanical properties and provides valuable insight into their potential application for improving soil crack resistance.

Landslides occurring in sensitive clay often result in widespread destruction, posing a significant risk to human lives and property due to the substantial decrease in undrained shear strength during deformation. Assessing the consequences of these landslides is challenging and necessitates robust numerical methods to comprehensively investigate their failure mechanisms. While studies have extensively explored upward progressive landslides in sensitive clays, understanding downward progressive cases remains limited. In this study, we utilised the nodal integration-based particle finite element method (N-PFEM) with a nonlinear strain-softening model to analyse downward progressive landslides in sensitive clay on elongated slopes, induced by surcharge loads near the crest. We focused on elucidating the underlying failure mechanisms and evaluating the effects of different soil parameters and strain-softening characteristics. The simulation results revealed the typical pattern for downward landslides, which typically start with a localised failure in proximity to the surcharge loads, followed by a combination of different types of failure mechanisms, including single flow slides, translational progressive landslides, progressive flow slides, and spread failures. Additionally, inclined shear bands occur within spread failures, often adopting distinctive ploughing patterns characterised by triangular shapes. The sensitive clay thickness at the base, the clay strength gradient, the sensitivity, and the softening rate significantly influence the failure mechanisms and the extent of diffused displacement. Remarkably, some of these effects mirror those observed in upward progressive landslides, underscoring the interconnectedness of these phenomena. This study contributes valuable insights into the complex dynamics of sensitive clay landslides, shedding light on the intricate interplay of factors governing their behaviour and progression.

This paper introduces a novel approach for parameter sensitivity evaluation and efficient slope reliability analysis based on quantile-based first-order second-moment method (QFOSM). The core principles of the QFOSM are elucidated geometrically from the perspective of expanding ellipsoids. Based on this geometric interpretation, the QFOSM is further extended to estimate sensitivity indices and assess the significance of various uncertain parameters involved in the slope system. The proposed method has the advantage of computational simplicity, akin to the conventional first-order second-moment method (FOSM), while providing estimation accuracy close to that of the first-order reliability method (FORM). Its performance is demonstrated with a numerical example and three slope examples. The results show that the proposed method can efficiently estimate the slope reliability and simultaneously evaluate the sensitivity of the uncertain parameters. The proposed method does not involve complex optimization or iteration required by the FORM. It can provide a valuable complement to the existing approximate reliability analysis methods, offering rapid sensitivity evaluation and slope reliability analysis.

The deterioration of unstable rock mass raised interest in evaluating rock mass quality. However, the traditional evaluation method for the geological strength index (GSI) primarily emphasizes the rock structure and characteristics of discontinuities. It ignores the influence of mineral composition and shows a deficiency in assessing the integrity coefficient. In this context, hyperspectral imaging and digital panoramic borehole camera technologies are applied to analyze the mineral content and integrity of rock mass. Based on the carbonate mineral content and fissure area ratio, the strength reduction factor and integrity coefficient are calculated to improve the GSI evaluation method. According to the results of mineral classification and fissure identification, the strength reduction factor and integrity coefficient increase with the depth of rock mass. The rock mass GSI calculated by the improved method is mainly concentrated between 40 and 60, which is close to the calculation results of the traditional method. The GSI error rates obtained by the two methods are mostly less than 10%, indicating the rationality of the hyperspectral-digital borehole image coupled evaluation method. Moreover, the sensitivity of the fissure area ratio (Sr) to GSI is greater than that of the strength reduction factor (α), which means the proposed GSI is suitable for rocks with significant fissure development. The improved method reduces the influence of subjective factors and provides a reliable index for the deterioration evaluation of rock mass.

Comprehensive data from in situ and laboratory tests in residual soil have been presented by Zhang et al. (2023). A number of issues addressed in the paper have been the interest of the discussers, namely the characterisation and behaviour of residual soils, limitation of piezocone testing due to the capacity of the entire system, measurement of shear wave velocity, rate effect of piezocone (CPTU) testing and piezocone testing with dual pore pressure penetrometers. Clarification and complementation of these issues are required with regard to both the execution and interpretation of the tests.

Degradation of rock mass produced by rock blasting, stress relief, and other causes is an important factor in the assessment of rock strength. Quantified as a disturbance factor, such degradation varies depending on blasting control, stress state and stress relief, and rock mass quality. This study focuses on the impact of disturbance on the safety of slopes. The disturbance in the rock mass is characterized by the geometry of the disturbed zone, its size, the magnitude, and the decaying rate with the distance away from the slope surface. A method accounting for decay of rock disturbance is presented. A study of the impact of rock disturbance characteristics on the quantitative stability measures of slopes was carried out. These characteristics included disturbed zone geometry, its thickness, the maximum magnitude of the disturbance factor, and the rate of disturbance decaying. The thickness of the disturbed zone and the maximum factor of disturbance were found to have the greatest impact. For example, the factor of safety for a 45° slope in low-quality rock mass can decrease from 1.96 to 1.09 as the thickness of the disturbed zone increases from 1/4 of slope height H to the double of H and the maximum disturbance factor increases from 0.5 to 1. Uniform thickness of a disturbed zone was found to yield more conservative outcomes than the triangular zones did. The critical failure surfaces were found to be shallow for high rates of disturbance decay, and they were the deepest for spatially uniform disturbance factors.

A series of direct shear tests under constant normal loading conditions were carried out on specimens of bolted sandstone single-joint treated with different numbers of dry–wet cycles. The experimental results show that the peak shear strength and shear stiffness of bolted sandstone joints were significantly reduced after 12 dry–wet cycles. The decrease in the shear strength of rough joints is more significant than that of flat joints. Due to the decrease in the strength of the surrounding rock, the deformation characteristics of the bolts are significantly affected by the number of dry–wet cycles performed. With an increase in the number of dry–wet cycles, the plastic hinge length of the bolt gradually increases, resulting in an increase in the corresponding shear displacement when the bolt breaks. Compared with the tensile–shear failure mode of the bolts in flat joints, the tensile–bending failure mode arises for bolts in rough joints. A shear curve model describing the whole process of bolted rock joints is established based on the deterioration of rock mechanical parameters caused by dry‒wet cycles. The model proposed considers the change in the friction angle of the joint surface with the shear displacement, which is applied to the derivation of the model by introducing the dynamic evolutionary friction angle parameter. The reasonably good agreement between a predicted curve and the corresponding experimental curve indicates that this method can effectively predict the shear strength of a bolted rock joint involving rough joint under dry–wet cycling conditions.

Intense precipitation infiltration and intricate excavation processes are crucial factors that impact the stability and security of towering and steep rock slopes within mining sites. The primary aim of this research was to investigate the progression of cumulative failure within a cracked rock formation, considering the combined effects of precipitation and excavation activities. The study was conducted in the Huangniuqian eastern mining area of the Dexing Copper Mine in Jiangxi Province, China. An engineering geological investigation was conducted, a physical model experiment was performed, numerical calculations and theoretical analysis were conducted using the matrix discrete element method (MatDEM), and the deformation characteristics and the effect of the slope angle of a fractured rock mass under different scenarios were examined. The failure and instability mechanisms of the fractured rock mass under three slope angle models were analyzed. The experimental results indicate that as the slope angle increases, the combined effect of rainfall infiltration and excavation unloading is reduced. A novel approach to simulating unsaturated seepage in a rock mass, based on the van Genuchten model (VGM), has been developed. Compared to the vertical displacement observed in a similar physical experiment, the average relative errors associated with the slope angles of 45°, 50°, and 55° were 2.094%, 1.916%, and 2.328%, respectively. Accordingly, the combined effect of rainfall and excavation was determined using the proposed method. Moreover, the accuracy of the numerical simulation was validated. The findings contribute to the seepage field in a meaningful way, offering insight that can inform and enhance existing methods and theories for research on the underlying mechanism of ultra-high and steep rock slope instability, which can inform the development of more effective risk management strategies.

This paper focuses on the performance of a braced deep excavation in soft soil based on field monitoring and numerical modeling. Laboratory tests were conducted to determine the soil parameters used in the modified Cam–Clay (MCC) model. Intelligent field monitoring means were adopted and a three-dimensional model was established. Spatial and temporal effects induced by the excavation are investigated for the deep-large foundation pit in soft soil. Deformation characteristics of the enclosure structure and the surrounding environment throughout the excavation process are presented. The behaviors of diaphragm walls, columns, the maximum wall deflection rate, ground surface settlement, and utility pipelines were focused on and investigated during the whole excavation process. Besides, the axial forces of the internal supports are analyzed. Based on the measured and simulated data, the following main conclusions were obtained: the numerical simulation results are in good agreement with the measured values, which proves the accuracy of the model parameters; the wall and the ground surface showed the maximum displacement increment at stage 9, which was a coupled product of the “creep effect” of the soft soil in Nanjing, China and the “depth effect” of the excavation; as the excavation progressed, the ground settlement changed from a “rising” to a “spoon-shaped” trend, δvm was measured between δvm = 0.0686%H and δvm = 0.1488%H; the rebound deformation curve of the pit bottom was corrugated, and the depth of disturbance of the pit bottom after the completion of soil unloading was 2–3 times the excavation depth; the closer the pipeline is to the corner of the pit, the less the excavation process will affect the settlement of the pipeline and the less the obvious pit corner effect will occur; the support strength of the buttress and the longest corner brace should be strengthened during the actual construction process to ensure the stability of the foundation deformation.

Since the classical element model cannot describe the nonlinear characteristics of rock during the entire compressive creep process, nonlinear elements and creep damage are generally introduced in the model to resolve this issue. However, several previous studies have reckoned that creep damage in rock only occurs in the accelerated creep stage and is only described by the Weibull distribution. Nevertheless, the creep damage mechanism of rocks is still not clearly understood. In this study, a reasonable representation of the damage variables of solid materials is presented. Specifically, based on the Gurson damage model, the damage state functions reflecting the constant creep stage and accelerated creep stage of rock are established. Further, the one-dimensional and three-dimensional creep damage constitutive equations of rock are derived by modifying the Nishihara model. Finally, the creep-acoustic emission tests of phyllite under different confining pressures are conducted to examine the creep damage characteristics of phyllite. And the proposed constitutive model is verified by analyzing the results of creep tests performed on saturated phyllite. Overall, this study reveals the relationship between the creep characteristics of rocks and the corresponding damage evolution pattern, which bridges the gap between the traditional theory and the quantitative analysis of rock creep and its damage pattern.