Rockfall is a globally frequent geological hazard, with its hazardous bodies typically comprising unstable rock masses formed by discontinuities cutting through the parent rock and exhibiting potential failure modes. A threedimensional (3D) model of an unstable rock mass not only provides an intuitive representation of its spatial configuration, but also enables the direct extraction of its geometric parameters, such as centroid coordinates and volume. Furthermore, it serves as a foundation for integrating numerical simulations to analyse the mechanical behaviour of rock masses. With the widespread application of non-contact measurement techniques, such as oblique photography, the efficiency of acquiring point cloud data for rock mass surfaces has significantly improved, thereby accelerating the development of point cloud-based methods for identifying rock discontinuities. However, point clouds obtained via oblique photography are typically massive and disordered, thereby making it challenging to construct closed, complete, and void-free 3D solid models of unstable rock masses. This limitation restricts the further application of 3D modelling technology in stability assessment and hazard mitigation. To address this issue, this study proposes a partitioned grid-based reconstruction method using discrete surface point clouds of the rock mass. By integrating structural plane information to generate bounding surfaces, the method provides a structured workflow for constructing 3D solid models suitable for engineering analysis. This approach effectively transforms "scattered point clouds" into "lightweight solid models," thereby enhancing the application potential of 3D modelling in rockfall studies.

Time-dependent heave deformation in red-bed soft rock (RBSR) subgrades poses a critical threat to high-speed railway safety. However, its creep mechanism remains unclear because of limited understanding of the creep properties of red-bed silty mudstone (RBSM) and the lack of suitable constitutive models. In this study, multistage loading creep tests with acoustic emission (AE) monitoring are conducted on RBSM under different water contents and low confining pressures. A unified nonlinear creep damage-coupled model is developed by combining statistical damage theory with fractional calculus. Experimental results show that RBSM exhibits stress-dependent nonlinear creep behavior, including viscoelastic deformation at low-stress levels, viscoelastic-viscoplastic deformation at intermediate stress levels, and trimodal deformation at high stress levels. The long-term strength remains within 64-75

Owing to its versatility in civil-engineering applications such as slope stabilisation, foundation consolidation, and tunnel construction, jet grouting has been lauded for its swift implementation, cost effectiveness, and high structural integrity. This study introduces an innovative framework and procedural technique for landslide reinforcement using jet grouting. Using the transfer-coefficient method, we develop an integrated strength model that encompasses the altered mechanical attributes of soil layers following jet-grouting treatment at the slide interface. This model underpins a bespoke stability calculation formula for landslides reinforced by jet grouting. The Sanhepu landslide is used as a case study, where the methodology unfolds across the testing, reinforcement- scheme design, project-execution, and monitoring phases. Our study shows that jet grouting substantially enhances the shear strength of sliding soil, with the treated soil exhibiting greater strength than its interface with a rock. A strategic reinforcement plan that considers the positioning, spacing, and height of jet-grouting columns is shown to significantly improve landslide stability. The stability coefficient for the Sanhepu site increases significantly from 1.184 before intervention to 1.453 after intervention. The theoretical findings are applied in practice to the Sanhepu landslide, with emphasis on targeted sliding-soil reinforcement. Post-intervention monitoring substantiates the stabilisation and confirms the effectiveness of the jet-grouting method for soils susceptible to sliding.

Battery status is influenced by various internal and external factors, and battery management systems (BMSs) still face many challenges in fault prediction. To address issues such as neglecting external features, insufficient feature selection dimensions, and limited BMS hardware computation in real-time environments, this study proposes a lithium-ion battery fault prediction method that integrates internal and external features with a stacking ensemble model. By combining internal sensor data with external features, a sliding time window-Lempel-Ziv-Welch method is proposed. Feature importance is calculated using the Gini coefficient, and multiple discriminant correlation analysis is used for feature fusion across different domains. Finally, hyperparameters are optimized using Newton-Raphson-based optimizer algorithm, and the stacking model is trained, with recall, precision, accuracy, and area under the curve (AUC) as evaluation metrics. Experimental results show that compared to individual models, the proposed method improves precision, recall, and accuracy by 11.2%, 9.88%, and 9.1%, respectively, with an AUC of 0.897. This research aims to enhance battery fault prediction accuracy and reliability, providing new technical support for the safe and reliable operation of new energy vehicles.

The occurrence of rockfalls is a prevalent geological hazard, especially in the Three Gorges Reservoir area of the Yangtze River. Analyzing the pre-rockfall evolution process of hazardous rock mass is crucial for stability assessment, risk monitoring, and evaluation. Generally, numerical analysis is conducted to study the rock stability and failure; however, it is primarily based on the two-dimensional calculation of typical cross-sections without considering the shape of the three-dimensional space of the hazardous rock mass, thus leading to distorted results. To address this issue, this paper proposes a methodological approach for the analysis of the stability conditions of a hazardous rock mass. The approach starts with field investigations and an Unmanned aerial vehicle (UAV) photogrammetric survey to gather data. These data are then used to construct a three-dimensional (3D) geological model of rock mass. Finally, a 3D numerical simulation is performed to analyse the potential failure processes of hazardous rock mass. In this study, we focused on the hazardous Diaozui rock mass of the Qutang Gorge in the Three Gorges Reservoir area (China). We constructed a 3D geological model of the rock mass based on the data from the field survey and UAV photogrammetric survey. Using this 3D geological model, we established a 3D numerical analysis model to assess the rockfall hazard. By utilizing the Strength reduction method (SRM) and simulating the collapse process of the hazardous rock mass, we analyzed the instability mechanism and failure evolution process of the Hazardous Diaozui rock mass. The results illustrated the potential failure mode, the key-oriented wedges of the rock mass, and the potential critical failure point for the hazardous rock mass. These findings provide valuable insights for stability assessment, risk monitoring, and evaluation of the hazardous rock mass in the Three Gorges Reservoir area.

In the field of overhanging rock prevention and control,the stability calculations have traditionally used simplified two-dimensional profiles as the calculation model.However,the irregular shape of overhanging rocks in nature cannot be accurately represented by this simplified model,leading to limitations in stress analysis.To address this,a three-dimensional calculation method for overhanging rock stability was developed based on limit equilibrium theory and previous research.The proposed method focuses on the stability against overturning of overhanging rocks controlled by the tensile strength of the trailing edge crack.A three-dimensional calculation formula was derived,taking into account the tension resistance,water pressure,and moment of the trailing edge rock.The formula was implemented using numerical integration and spatial geometry methods,providing a comprehensive approach to analyzing the stability of overhanging rock.To validate the proposed method,an application was conducted using the Diaozui overhanging rock in the Qutangxia area of the Three Gorges Reservoir.Numerical analysis was performed to verify the results.By analyzing the stability of different forms of overhanging rock in three dimensions,the relationship between the three-dimensional stability calculation results and the traditional two-dimensional stability analysis was explored.The findings revealed that the shape of overhanging rock significantly impacts the stability calculation results.It was concluded that three-dimensional calculations provide more accurate and practical results compared to the traditional two-dimensional approach.

高边坡广泛存在于市政、铁路等工程中,对发生突发变形、滑移的高边坡进行应急抢险加固是保障坡顶建筑安全的重要措施.结合FLAC3D软件数值模拟方法,针对坡顶有临空建筑物的岩质高边坡进行应急抢险加固设计,总结坡顶带临空建筑高边坡应急抢险加固技术.研究得到:预应力锚索支护因施工工期短、经济适用性好、对岩土体扰动小,是对带临空建筑高边坡变形快速控制的最优选择;提出基于高边坡塑性区面积和位移矢量变化趋势的预应力锚索预应力大小取值方法;根据高边坡变形区形态与坡顶建筑变形控制的相互关系,总结出预应力锚索+格构面板支护+地表排水+M10砂浆封闭裂缝相结合的应急抢险加固方案.后续监测显示抢险加固效果好,达到预期目标.

针对现有预应力锚索抗滑桩使用空间受限的情况,提出一种大角度斜拉桩,结合Winker弹性地基梁理论和弹性支座法,为其建立力学计算模型.用桩锚变形协调条件,推导锚索拉力计算公式,并将抗滑桩从滑面处分为上、下两部分,滑面以上部分按结构力学方法计算,滑面以下部分按Winker弹性地基梁法计算.通过Matlab编程实现锚索拉力、桩身内力及位移计算结果输出.采用OptumG2软件建立数值模型对理论模型进行验证,结果表明:计算方法能准确反映桩顶大角度斜拉桩的受力、变形特点,计算结果的精确程度取决于地基系数选取的合理性与准确性.最后,以重庆某基坑边坡工程为例,与普通抗滑桩进行对比分析,计算结果表明:大角度斜拉桩受力模式更加合理,大角度斜拉锚索可有效减小桩身弯矩、剪力、位移等,进而减小桩身截面尺寸、配筋和嵌固段长度.

In the current code, the E-ak formula for active rock pressure of slopes sliding along gently inclined outward weak structural planes does not consider the water pressure of the trailing edge fractures, which leads to deviation in E-ak calculation. In view of this problem, according to the balance relationship and geometric conditions of the force system, the stress analysis and simplification are carried out considering the water pressure of the trailing edge crack, and the calculation formula of the active rock pressure is derived to determine whether there is an extreme point and its location. The research results show that the error of E-ak is 21.89%-100% without considering water pressure; E-ak has a maximum in the effective range. The dip angle of gently inclined rock stratum theta and the friction angle in the structural plane phi are compared, it is found that if theta>phi, the width of potential slip surface at the top of slope is generally 0.2-1.2 times of the slope height H; and if theta <= phi, the maximum value of E-ak appears on the slope. This study improves the calculation formula by classification, and analyses the correlation between the extreme point position and some factors including H. It is of theoretical and practical significance for the prevention and control of sliding slope along gently inclined soft outward inclined structural plane.

The sliding surface deformation of the soil slope mainly presents progressive failure characteristics, and serial acoustic emission (AE) signals are generated during the deformation process of progressive landslide. Early warning systems for soil slope instability should alert users of slope deformation stage to make the right decision. Thus, a model test aiming at reproducing the typical shear surface deformation of a soil slope is designed. The displacement, AE data and corresponding time–frequency characteristics are comprehensively analyzed to evaluate the progressive deformation behavior. Comparisons with different granular backfills measurements show that cumulative AE count increases proportionally with the shear surface displacement, and the experiments demonstrate that the glass sand backfill exhibits remarkable AE detection characteristics and stronger correlation results. Significantly, AE signal exhibits variant dominant frequencies at different deformation stages, and there is the significant phenomenon that not only the low-frequency signals generated with a significantly increase number, at the same time the continuous high-frequency signals appear during the accelerating deformation stage. Furthermore, from the statistical trend of the energy percentage of the high-frequency band into 312.5–500 kHz, it is found that the correlative energy proportion occupies up to 15%, or even higher during the accelerating stage, indicating that the landslide may be about to enter a severely dangerous stage. This study proposes a new perspective on the frequency characteristics as the early warning index, which can be combined with other traditional acoustic emission indicators to improve the accuracy of the field warning monitoring for the soil progressive landslides.

三维地质在油气、水利水电、矿产等领域已得到大量应用,而从三维地质发展起来的工程勘察设计BIM技术在滑坡治理工程中的应用实例相对较少.通过对现有软件的整合,充分发挥各软件特点,形成了一种滑坡治理工程勘察设计BIM技术应用方法.首先对地形测绘、地质钻孔和地质剖面等勘察数据进行处理;然后借助GOCAD软件的流程化建模方法构建三维地质模型;最后将三维地质模型导入数值分析软件开展滑坡治理工程设计.以重庆周家岩滑坡治理工程为例对提出的工程勘察设计BIM技术方法进行了实际应用,其工程实际效果论证了技术方法的可行性和实用性.

Abstract. An innovative combined optical fiber transducer (COFT) based on the optical fiber bending loss characteristic has been developed for landslide monitoring. To better understand the working principle and improve the monitoring performance of the transducer, the capability of the COFT for exploring subsurface properties of slopes (sliding direction, magnitude, and rate of slope movement) and the deformation compatibility between the COFT and surrounding geo-materials were explained semi-empirically and semi-theoretically, which was also verified by the laboratory shear experiments of the COFTs constructed with two kinds of host materials (expanded polystyrene and polyvinyl chloride) and three kinds ratios of cement mortars (sand to cement 1:4, 1:5, and 1:6) and the related numerical simulation. In the following, model monitoring tests of an artificial slope and field monitoring application of the proposed COFTs in a field slope were carried out and the progressive slope movements were effectively determined, which validated the performance of the proposed COFT in landslide monitoring.

To investigate the acoustic emission (AE) precursor detection of landslide failures, a model test aiming at reproducing the typical shear surface deformation of different landslide modes was designed. The evolution characteristics of the AE signals were analyzed in terms of AE count, cumulative AE count, AE correlation diagrams, and corresponding time-frequency properties. The test results show that for the progressive deformation mode, the AE count experiences a low-level period, an active period and a rapid increase period, and the distribution of correlation diagram hits concentrates in a relatively small scale and then gradually scatters. There is low frequency signals firstly and then high frequency signals, and the energy proportion of the high-frequency signals shows an increasing tendency. For the sudden deformation mode, the magnitude of AE count increases sharply, leading to the cumulative AE count curve rises steeply, and correlation diagram hits distribution turns into relatively scattering rapidly. Furthermore, the high frequency signals and high energy proportion appear much earlier than that of the progressive deformation mode. For steady deformation mode, however, the acoustic emission activity is quite active in the initial stage, the cumulative AE count curve rises sharply and then maintains relatively flat trend, and correlation diagram hits distribution scatters firstly, then the signal hits distribution begins to concentrate in a relatively small scale. There are intensive high-frequency hits and high energy proportion earlier, and later they tend to decay in response to smaller magnitudes of movement. Comprehensive use of multiple features can help identify landslide deformation patterns more accurately under complex natural conditions, which may provide a promising reference for the field warning monitoring of the diverse landslide failures.

In order to form fracture network and improve drainage area, gas shale reservoir have to be reformed by hydraulic fracturing. The geometric size, extension direction of fracturing can be predicted with microseismic monitoring, the stimulated effect and performance of gas production can be evaluated. Due to the complex environment and diversity of noise types, the signal energy of surface microseismic monitoring is weak, which is easily covered by noise, and the signal-to-noise ratio (SNR) of raw data is very low. In this paper, the SURE algorithm based on the continuous wavelet transform (CWT) is proposed to separate the signal from the noise on the wavelet coefficients. The low SNR data are decomposed into approximate coefficients and detail coefficients in time and frequency domain. The thresholds are changed with different decomposition levels, which is adapted to the noise level. The algorithm can effectively improve the SNR of the raw data and the event location accuracy. The method has been successfully applied to the surface microseismic monitoring of shale gas fracturing in X well in southwest of China. The SNR of raw data has been improved, the effective stimulated reservoir volume (ESRV) and the performance of gas production are predicted with the microseismic results, which provides important technical support for shale gas development in the area.

Limited by geological survey methods, processes, and cost, it has long been a difficult thing to accurately detect the position of landslide slip surface and monitor the landslide internal deformation. Fiber Bragg grating (FBG) sensing technology has been widely used in geological engineering and geotechnical engineering due to its high-precision property. In this research, FBG sensing technology was applied to the monitoring of landslide internal deformation in Toudu, Chongqing, China. The in situ monitoring by FBG accurately determined the position of the landslide slip surface. Based on the relationship between fiber grating strain and deflection, the formula between landslide internal deformation and fiber grating strain was obtained, and the rationality of the formula was verified by the monitoring data of surface displacement. Finally, the internal deformation at the monitoring point of the Toudu landslide was calculated and the mechanism of the landslide was analyzed.

With monitoring the acoustic emission phenomenon caused by rock deformation and failure, microseismic monitoring has been widely used in deformation monitoring of mines, oilfields and dams, especially in the development of unconventional oil and gas fields. In the process of data processing, a lot of human resources needs to discriminate the first break picking, and the accuracy directly affects the error of microseismic event location. In this paper, a method is proposed for picking up first break wave of low signal-to-noise ratio data based on AIC criterion and characteristic function. Threshold is established by maximizing the waveform in the time window, and the first break of low signal-to-noise ratio data is automatically and accurately judged, which reduces the computational complexity and improves the accuracy of events location. The effectiveness of the method is verified by fracturing monitoring of shale gas reservoirs.

With monitoring of the acoustic emission phenomenon caused by rock deformation and failure, microseismic monitoring has been widely used in the development of unconventional oil and gas fields. Due to the complex environment and diversity types of the noise, the signal energy of surface microseismic monitoring is weak and the signal-to-noise ratio (S/N) of raw data is very low. In the process of data processing, many human resources are needed to discriminate the first-break picking because of the low S/N, and this directly affects the error of microseismic event location. We have adopted the regularization to Stein unbiased risk estimation (R-SURE) algorithm based on the continuous wavelet transform to separate the signal from the noise in different decomposition levels. The regularization factor is the adaptive change of the different geology and fracturing engineering, which is related to shale brittleness, fracturing pressure, and displacement. As a result, the threshold from the R-SURE algorithm is multiresolution in different levels, and the S/N could be improved effectively. In addition, we established the threshold discriminant for picking up the first-break wave of low-S/N data combined with the Akaike information criterion and characteristic function, which compared the maximum absolute value in the time window. The method has good robustness and low computational complexity. The first arrival is automatically and accurately judged, which improves the accuracy of the event location. We successfully applied these methods to the surface microseismic monitoring of shale gas fracturing in several wells in southwest China. The S/N of the raw data has been improved, the effective stimulated reservoir volume and the performance of the gas production are predicted with the results, which provides important technical support for shale gas development in the area.

The resource potential of coalbed methane (CBM) in China is huge, the geological resources is 0.68 × l012 m3 in Chongqing upon the depth of 2000 m. The high content of coalbed methane reveals that Chongqing has a good potential of coalbed methane resources. With the artificial intelligence technology applying to many respects of unconventional oil and gas exploration and development, the neural network technology is playing a more and more important role to solve the complex geophysical model. In this paper, the regularization dropout to long short term memory (RD-LSTM) neural network algorithm is proposed for CBM well productivity prediction. Different weights are given by the gate control unit combining with the factors that affect the production of CBM well, which is from the geology, geophysics, fracturing, and recovery technology. In order to discard the invalid operator, reduce the computational complexity of different hidden layers, regularization dropout mechanism is added to gated units such as forget gate, output gate, external output gate, et al. The regularization function is determined by the geometric average of the probability of the different unit. When the value is zero, the dropout occurs. The state of the gate would participate in the next sub-network. The result shows that the algorithm has lower complexity and higher computational efficiency than LSTM algorithm. In addition, the algorithm can accurately predict the production of the CBM well after increasing the sample data, which is beneficial to improve the recovery of CBM well, well pattern planning, process of drainage and recovery.