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Managing the waste dumps has become a significant challenge, along with increasing mining production. Maintaining waste dump stability is vital to prevent failures that could lead to economic losses, environmental harm, and safety hazards. This study investigates the stability of waste dumps in open-pit coal mining operations, focusing on the impact of rainfall on dump stability. The objective was to evaluate a strainbased approach for predicting waste dump failures, accounting for changes in soil properties during rainfall events. A coupled hydro-mechanical framework was used to back-analyze the historical impact of rainfall on waste dump stability. The results showed strain values ranging from 2.79% to 7.36% during progressive slope failure. The weak nature of the waste dump material, with compressive strengths of less than 1 MPa and poor rock mass quality, enabled the development of an approximate maximum strain threshold graph. These findings could enhance predictive capabilities for waste dump stability and bridge the gap by utilizing coupled hydro-mechanical analysis, ultimately improving understanding and safety in waste dump operations. [ABSTRACT FROM AUTHOR]

Efficient and accurate acquisition of slope shear strength parameters is the key to slope stability analysis and landslide prevention engineering design. This paper establishes a back analysis method based on uniform design, artificial neural network, and genetic algorithm. It can obtain the shear strength parameters of slopes based on information such as the radius and center coordinates of the slip surface obtained from on‐site investigations. This method has been applied to engineering practice. The research results indicate that the stability of the waste dump slope is most sensitive to the response of the internal friction angle of the loose body, followed by cohesion, and least sensitive to the response of the soil volume weight. This method can effectively reduce the number of network training samples and efficiently and quickly determine the initial weights of the BP (abbreviation for back‐propagation) neural network. This method can efficiently and quickly conduct back analysis to obtain the shear strength parameters of slopes. Using the obtained shear strength parameters for slope stability calculation, the most dangerous slip surface abscissa error, ordinate error, and slip surface radius error are only 3.59%, 0.95%, and 1.83%. It is recommended to promote the back analysis method of shear strength parameters in engineering practice in the future. [ABSTRACT FROM AUTHOR]

The construction process of the Tilong Dam induced significant settlement in the surrounding areas. This study aimed to enhance our understanding of the factors that influenced settlement behavior and improve the reliability of predictive models by using instrumentation data regarding the dam's vertical displacement. Numerical modeling was conducted to consider the actual embankment conditions and analyze the changes in the immediate settlement during and after construction. After the Tilong Dam construction, the measurements and numerical analysis showed settlements ranging from 0 to 832 mm. It was noted that settlements were expected during and after the construction, particularly at the dam's mid-sections. The back analysis method was employed to establish the values for material properties, specifically Young's modulus and Poisson's ratio, which affected the displacement. A multivariate regression comparison between the observed and predicted data yielded a determination coefficient (R²) of 0.914. This indicated a strong correlation between the observed and predicted values.

Slope failures in mining engineering pose significant risks to slope stability control, necessitating a thorough investigation into their root causes. This paper focuses on a back analysis of a slope failure in the Zerga section of the Ouenza – Algeria open-pit iron mine. The primary objectives are to identify the causes of slope failure, propose preventive measures, and suggest techniques to enhance stability, thereby providing crucial insights for monitoring slope stability during mining operations. The study commenced with a reconstruction of the slopes in the affected zones, followed by a numerical analysis utilizing the Shear strength reduction method within the Finite element method (SSR-FE). This approach enables the examination of slope stability under both static and dynamic loads. The dynamic load assessment incorporated an evaluation of the vibrations induced by the blasting process during excavation, introducing seismic loading into the finite element analysis. The findings reveal that the primary triggering factor for the landslide was the vibration generated by the blasting process. Furthermore, the slope stability was found to be critically compromised under static loads, highlighting a failure to adhere to exploitation operation norms. The challenging geology, particularly the presence of marl layers where maximum shear strain occurs, contributed to the formation of the landslide surface. The study not only identifies the causes of slope failure but also provides valuable lessons for effective slope stability management in mining operations.

For today’s demands in underground infrastructure, geotechnical considerations are gaining prominence, emphasizing the resolution of complex problems through numerical modeling and soil-structure interaction analysis. There is a clear trend shifting away from two-dimensional (2-D) plane strain or axisymmetric idealizations to the comprehensive analysis of full three-dimensional (3-D) models. However, despite the inclination towards 3-D modeling of tunnels, establishing a realistic 3-D model for this purpose remains a timeconsuming process. This typically involves multiple iterative and incremental phases, essential for gaining deeper insights into the three-dimensional nature of the problem. Beyond selecting an appropriate constitutive soil model, realistically finite element modeling and accurate simulation of the tunneling process are of paramount importance. This study focuses on the development of a practical full 3-D model and simulation of the Earth Pressure Balance (EPB) shield tunneling process using the finite element code PLAXIS 3D. The numerical model incorporates tunnel boring machine driving data recorded during tunnel construction and is validated through back-analysis of field measurements of tunneling-induced ground surface settlements. The findings demonstrate that numerical simulation can realistically reproduce the main characteristics of EPB shield tunneling. The study recommends adopting non-linear face pressures with depth based on the analysis of tunneling data. Regarding grouting pressure, an effectively linear distributed pressure may be considered, accounting for the grout weight and the increase of soil stresses with depth. This validated numerical framework provides valuable guidance for researchers and practitioners to construct more efficient, reliable, and accurate 3-D models. [ABSTRACT FROM AUTHOR]

On 8 October 2017, persistent heavy rainfall triggered a rock collapse on Fenghuang Mountain in Wuxi Town, located within the Three Gorges Reservoir region of China. Subsequent field investigations and monitoring identified several potentially unstable rock masses in the area, posing a significant threat to the safety of nearby residents and their property. In this study,the Rapid Mass Movement Simulation (RAMMS) numerical tool was used to perform a back analysis of the rock collapse event. The well calibrated numerical model was then used to assess the risk of the potential unstable rock masses in the study area. The rock collapse on Fenghuang Mountain descended rapidly along the slope, with the dislodged material accumulating at the base and obstructing the road at the foot of the slope. Some debris breached the embankment and entered the Daning River. The computed maximum velocity during the rock collapse event was approximately 9.14 m/s, with an average maximum deposit thickness of around 4.48 m. The back-analysis of the rock collapse event closely aligns with the observed failure process and deposit morphology documented through field investigation. Using the well calibrated numerical model, a dynamic analysis was conducted on the potential unstable rock mass. The risk assessment indicates that the potential unstable rock mass is prone to instability, with a high likelihood of a subsequent rockfall under extreme rainfall conditions. The computed average maximum velocity for the potential rockfall is 33.83 m/s, with an average maximum deposit thickness of 2.20 m. The computed maximum impact pressure is about 164 kPa, which would result in significant damage to the road below. Additionally, a maximum wave height of 1.38 m from the surge caused by potential rockfall entering the Daning River was calculated by a semi-empirical model. This research offers a novel approach and methodology for assessing the risk of such hazardous events in similar geological setting globally.

Abstract Efficient and accurate acquisition of slope shear strength parameters is the key to slope stability analysis and landslide prevention engineering design. This paper establishes a back analysis method based on uniform design, artificial neural network, and genetic algorithm. It can obtain the shear strength parameters of slopes based on information such as the radius and center coordinates of the slip surface obtained from on‐site investigations. This method has been applied to engineering practice. The research results indicate that the stability of the waste dump slope is most sensitive to the response of the internal friction angle of the loose body, followed by cohesion, and least sensitive to the response of the soil volume weight. This method can effectively reduce the number of network training samples and efficiently and quickly determine the initial weights of the BP (abbreviation for back‐propagation) neural network. This method can efficiently and quickly conduct back analysis to obtain the shear strength parameters of slopes. Using the obtained shear strength parameters for slope stability calculation, the most dangerous slip surface abscissa error, ordinate error, and slip surface radius error are only 3.59%, 0.95%, and 1.83%. It is recommended to promote the back analysis method of shear strength parameters in engineering practice in the future.

Real-time prediction of excavation-induced displacement of retaining pile during the deep excavation process is crucial for construction safety. This paper proposes a modified back analysis method with multi-objective optimization procedure, which enables a real-time prediction of horizontal displacement of retaining pile during construction. As opposed to the traditional stage-by-stage back analysis, time series monitoring data till the current excavation stage are utilized to form a multi-objective function. Then, the multi-objective particle swarm optimization (MOPSO) algorithm is applied for parameter identification. The optimized model parameters are immediately adopted to predict the excavation-induced pile deformation in the continuous construction stages. To achieve efficient parameter optimization and real-time prediction of system behavior, the back propagation neural network (BPNN) is established to substitute the finite element model, which is further implemented together with MOPSO for automatic operation. The proposed approach is applied in the Taihu tunnel excavation project, where the effectiveness of the method is demonstrated via the comparisons with the site monitoring data. The method is reliable with a prediction accuracy of more than 90%. Moreover, different optimization algorithms, including non-dominated sorting genetic algorithm (NSGA-II), Pareto Envelope-based Selection Algorithm II (PESA-II) and MOPSO, are compared, and their influences on the prediction accuracy at different excavation stages are studied. The results show that MOPSO has the best performance for high dimensional optimization task.

The underground powerhouse of the Shuangjiangkou hydropower station is one of the largest caverns under construction in China, and its stability during construction is crucial for safe construction. To study the stability of the surrounding rock during excavation, the displacement and stress of the surrounding rock were monitored by multi-point displacement meters and bolt stress meters. Based on the monitoring data, the elastic modulus, Poisson's ratio, friction angle, and cohesion of surrounding rock were inversely analyzed by the PSO-BP algorithm. Then, the back-analyzed parameters were used to simulate the subsequent excavations and predict the stability of surrounding rock during the following construction. The analysis results show that the surrounding rocks were generally stable during the initial four stages of excavation, and the main factors affecting their stability were blasts and unfavorable geological structures, including the lamprophyre vein and the F1 fault. These unfavorable geological structures also significantly decrease the mechanical parameters of surrounding rock as demonstrated by back analysis, and the stability prediction results show that the omnibus bar cave and the tailrace tunnel were at the greatest risk of instability during the subsequent excavations. This study provides a practical analysis for engineering excavation of the underground caverns. [ABSTRACT FROM AUTHOR]

The investigation of seepage situation of a reservoir under complex geological conditions is greatly significant and is necessary to be determined by geologic survey or numerical analysis. Based on previous geological survey data, a 3-dimensional seepage back analysis was conducted. In this study, two hydraulic conditions of unsteady and steady seepage were considered, and the corresponding back analysis came down to a multi-objective decision-making problem. The GRNN model was trained by PSO algorithm for obtaining the relationship between permeability coefficients and monitoring data, and by combining the NSGA-II algorithm, the best unbiased solution of permeability coefficients for the multi-objective function established by monitoring data of seepage discharge and pressure head was searched via iteration calculation. On this basis, the seepage safety of the reservoir was evaluated. Through taking the seepage discharge of the whole reservoir into account, the problem in the traditional seepage field back analysis that the foundation strata seepage parameters are insensitive to the pressure head inside the dam was solved. And the inversion results can provide a supplement for the geological survey under complex geological conditions. The method adopted in this paper may provide significant references for the anti-seepage design and reinforcement of hydraulic structures with complex geological conditions. [ABSTRACT FROM AUTHOR]

Landslides govern the evolution of landforms and pose a serious threat across the globe, especially in mountainous areas. In the northwestern area of Vietnam, a slow-moving landslide occurred near an important economic road corridor in Caumay Ward, Sapa Town, Laocai Province. In December 2019, some serious cracks were observed at a construction site near this landslide. Since this phenomenon could cause not only loss of life but also damage to the properties located downhill, the construction was abandoned until the slope was rehabilitated. Geological investigations, laboratory tests, and surface displacement monitoring were conducted to understand the failure mechanism. The analysis results showed that the anthropogenic activities associated with the rising groundwater level due to frequent rainfall events, owing to climate change, had contributed to the sliding of the sloping soil mass. The rehabilitation works at the failed area were conducted chronologically in two stages: (1) backfilling at the downhill area; demolishing two villas located within the sliding area to reduce surcharge; constructing an anchor system in the uphill area, and (2) constructing the anchored wall at the downhill area. During the rehabilitation works, the Caumay landslide was observed to initially undergo gradual movement and then stabilize at the end of the first stage of the rehabilitation works. The rehabilitation techniques adopted at the failed site were validated using both numerical analysis and field measurements. The anchor reinforcement methodology adopted in this study is expected to help agencies and the public in stabilizing landslide-prone areas for residential and other infrastructure construction. [ABSTRACT FROM AUTHOR]

Accurate prediction of thermal conductivity (λ) in frozen soils is essential for understanding their thermal behavior and improving thermal response analyses. Currently, there are numerous models for calculating λ, but unified laboratory data to compare and evaluate these models are lacking. This study focuses on evaluating the performance of 17 models for applied to frozen soils using a unified laboratorial dataset. The heat-pulse-probe (HPP) method was employed to measure the thermal conductivity of silty clay, sand, and sand loam. Nuclear magnetic resonance experiments were conducted to measure the unfrozen water content (θw) and ice content(θi). This provides unified laboratorial dataset of λ-θi-θw. The predictive performance of 17 models demonstrated that the model of Zhang et al. (2018), Sass et al. (1971) and Tian et al. (2016) are the three optimal models: 1). The model of Zhang et al. (2018) is the provided the best predictive performance, with mean absolute error (MAE) values of 0.17 Wm-1K-1, 0.07 Wm-1K-1, and 0.06 Wm-1K-1 for silty clay, sand and sand loam, respectively. This model is advantageous due to its simplicity and the absence of undetermined parameters. 2). The model of Sass et al. (1971) is suitable for soils with low sensitivity to frozen volume deformation, such as sand and sand loam, achieving an MAE of 0.06 Wm-1K-1. 3). The model of Tian et al. (2016) exhibited strong performance for silty clay with an MAE of 0.11 Wm-1K-1, contingent on the precise determination of soil-specific parameters. This study provides a unified laboratory data for the establishment of thermal conductivity models. The evaluation of existing models can serve as a reference for future related research.

In response to the problem of significant post-construction settlement that may occur in a motor racing circuit (MRC), two representative composite foundation testing areas, PHC pile (pre-tensioned spun high-strength concrete pile) and CFG pile (cement fly ash gravel pile), were selected for field tests to obtain the deformation law of pile–soil. Then, finite element numerical simulation was used to carry out back analysis on the geological mechanical parameters of the testing areas. The results showed that the error of soil settlement between the piles in the PHC pile and CFG pile testing areas were 8.2% and 9.6%, respectively, with good inversion precision. The obtained geological mechanical parameters can be used to predict the settlement of the rest of the MRC. On this basis, a finite element numerical model was constructed to analyze the bearing and deformation characteristics of the foundation of the MRC under five types of working conditions that may cause significant post-construction settlement. It showed that the settlement of the embankment was large in the middle and small on both sides after the consolidation of the embankment. The maximum settlement was about 27.0 mm, and the maximum longitudinal uneven settlement ratio of the embankment was 1.3/4000. The axial force of piles in the PHC pile and CFG pile composite foundations increased first and then decreased with depth. The maximum bending moment was located at the foot of slopes or at the boundary of strata, which was relatively small in the middle of the embankment. The deformation of the embankment and the bearing capacity of the piles could meet engineering requirements. This study has certain guiding significance for the design and construction of similar pile-net composite foundations. [ABSTRACT FROM AUTHOR]

A landslide was experienced in Karyamekar Village, Cilawu District, Garut Regency, West Java, on 12 February 2021 at approximately 300 m length with a depth of 20 m, leading to a steep slope. Therefore, this study aimed to use 3D back analysis to determine soil shear strength to be subsequently applied in analyzing the possibility of further landslide with due consideration for tension crack and rainfall effect. It was also used to understand the influence of these factors on slope stability. Filled tension crack and rainfall effects were modeled using Finite Element Method (FEM) while Limit Equilibrium Method (LEM) was applied for back analysis. The results of back analysis showed that peak shear strength value of f was 31.18° at a cohesion of 8.01 kPa while the residual shear strength value of f was 10.35° with 2.31 kPa. The fpeak value was found to be close to the estimated 32°, but there was a significant difference in the fresidual which was approximated to be 30°. This discrepancy could be attributed to several factors such as the accuracy of rainfall data and geometry as well as the absence of some soil samples during the investigation. The cohesion values for peak and residual soil shear strength were considered acceptable because of the smaller values compared to the typical cohesion of SM (Silty Sand) which was set at 20°. Moreover, slope stability analyses conducted using only the effect of tension crack produced a safety factor of 0.996 while those with only the effect of rainfall had 1.172. The results showed that water pressure in tension crack had a more significant influence on slope stability compared to rain. However, it was important to state that the variation in the significance of each factor was based on the assumptions made during the analysis. [ABSTRACT FROM AUTHOR]

The underground powerhouse of the Shuangjiangkou hydropower station is one of the largest caverns under construction in China, and its stability during construction is crucial for safe construction. To study the stability of the surrounding rock during excavation, the displacement and stress of the surrounding rock were monitored by multi-point displacement meters and bolt stress meters. Based on the monitoring data, the elastic modulus, Poisson’s ratio, friction angle, and cohesion of surrounding rock were inversely analyzed by the PSO-BP algorithm. Then, the back-analyzed parameters were used to simulate the subsequent excavations and predict the stability of surrounding rock during the following construction. The analysis results show that the surrounding rocks were generally stable during the initial four stages of excavation, and the main factors affecting their stability were blasts and unfavorable geological structures, including the lamprophyre vein and the F1 fault. These unfavorable geological structures also significantly decrease the mechanical parameters of surrounding rock as demonstrated by back analysis, and the stability prediction results show that the omnibus bar cave and the tailrace tunnel were at the greatest risk of instability during the subsequent excavations. This study provides a practical analysis for engineering excavation of the underground caverns.

Aiming to investigate the problem that dam-monitoring data are difficult to analyze in a timely and accurate automated manner, in this paper, we propose an automated framework for dam health monitoring based on data microservices. The framework consists of structural components, monitoring sensors, and a digital virtual model, which is a hybrid of a finite element (FE) model, a geometric model, a mathematical model, and a deep learning algorithm. Long short-term memory (LSTM) was employed to accurately fit and predict the monitoring data, while dynamic inversion and simulation were used to calibrate and update the data in the hybrid model. The automated tool enables systematic maintenance and management, minimizing errors that are commonly associated with manual visual inspections of structures. The effectiveness of the framework was successfully validated in the safety monitoring and management of a practical dam project, in which the hybrid model improved the prediction accuracy of monitored data, with a maximum absolute error of 0.35 mm. The proposed method can be considered user-friendly and cost-effective, which improves the operational and maintenance efficiency of the project with practical significance. [ABSTRACT FROM AUTHOR]

Claystone is potentially the main rock formation for the deep geological disposal of high-level radioactive nuclear waste. A major factor that affects the deformation of the host medium is effective stress. Therefore, studying the effective stress principle of claystone is essential for a stability analysis of waste disposal facilities. Consolidated drained (CD) tests were carried out on claystone samples to study their effective stress principle in this paper. Firstly, two samples were saturated under a specified confining pressure and pore pressure for about one month. Secondly, the confining pressure and pore pressure were increased to a specified value simultaneously and then reverted to the previous stress state (the deformations of the samples were recorded during the whole process). Different incremental combinations of the confining pressure and pore pressure were tried at this step. Finally, the effective stress coefficients of the samples were obtained through a back analysis. Furthermore, some potential influencing factors (the neutral stress and loading rate) of the effective stress coefficient were also studied through additional tests. Some interesting results are worth mentioning: (1) the effective stress coefficient of claystone is close to one; (2) the neutral stress and loading rate may have little effect on the effective stress coefficient of claystone. [ABSTRACT FROM AUTHOR]

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Construction of urban tunnel engineering in mountainous karst regions involves a plethora of uncertain geological risk factors. Due to cost and schedule constraints, hydrogeological and engineering geological risk sources cannot be identified in detail, leading to frequent disasters. Expert scoring, which is influenced by human subjectivity, is a common method for disaster evaluation in tunnel engineering, and some evaluation indicators are difficult to quantify. In order to address these issues, Guiyang rail transit line 2 Phase I project was selected as a case study to establish a risk disaster evaluation system for urban tunnel engineering in mountainous karst regions. The location and type of the disasters during construction were recorded for 26 running tunnels, and geological risk factors that were significantly correlated were selected as evaluation factors. The coupling relationship between the frequency of disaster occurrence and the geological risk factors was inverted, leading to the establishment of the risk disaster evaluation system of urban tunnel engineering in mountainous karst region. The evaluation results demonstrate that the degree of consistency between the frequency of disaster occurrence and the segmentation results of the evaluation system is more than 69%, indicating that the evaluation system is capable of predicting the frequency of disaster occurrence effectively.

Mountain road tunnels are prone to water leakage and lining corrosion under the complex geological conditions and corrosive environments, which will reduce the strength of the lining structure until it loses its load-bearing capacity; eventually, the definitive lining will need to be replaced. In this paper, a highway tunnel in a mountainous area in Southwest China is taken as an example. Field investigation found that the tunnel was seriously corroded by sulfate, the strength of the definitive lining decreased, and large-scale cracks and spalling appeared on the surface, so the operator decided to replace the definitive lining by the method of interval replacement. Based on the data obtained from drilling and coring, a numerical model of long-distance replacement of the definitive lining of the damaged tunnel is established. First, the back analysis of the calculation parameters is carried out, and the modified calculation results are compared with the field monitoring results for verification. Then, the deformation trend of the tunnel and the development of the plastic zone during the process of long-distance replacement of the definitive lining are studied. Finally, the construction scheme is optimized. Numerical analysis results show that the replacement of the definitive lining of the tunnel mainly leads to the settlement of the arch crown and the uplift of the inverted arch. The deformation of the tunnel shows two rapid growth stages and two stable stages during the replacement process; after replacement, the deformation of the arch crown and the inverted arch is divided into two buffer zones and one stable zone. In the progress of the replacement of the definitive lining, the plastic zone does not change. Regarding the reinforcement measures, with the increase in the grouting range, the grouting efficiency decreases, and the effect of the temporary steel arch on controlling the overall deformation is not obvious. The length of the replacement of the single section should be determined according to the geological conditions of the replacement section and the monitoring data during construction. The research results can provide a reference for similar projects for the replacement of the definitive lining.

A landslide was experienced in Karyamekar Village, Cilawu District, Garut Regency, West Java, on 12 February 2021 at approximately 300 m length with a depth of 20 m, leading to a steep slope. Therefore, this study aimed to use 3D back analysis to determine soil shear strength to be subsequently applied in analyzing the possibility of further landslide with due consideration for tension crack and rainfall effect. It was also used to understand the influence of these factors on slope stability. Filled tension crack and rainfall effects were modeled using Finite Element Method (FEM) while Limit Equilibrium Method (LEM) was applied for back analysis. The results of back analysis showed that peak shear strength value of φ was 31.18° at a cohesion of 8.01 kPa while the residual shear strength value of φ was 10.35° with 2.31 kPa. The φpeak value was found to be close to the estimated 32°, but there was a significant difference in the φresidual which was approximated to be 30°. This discrepancy could be attributed to several factors such as the accuracy of rainfall data and geometry as well as the absence of some soil samples during the investigation. The cohesion values for peak and residual soil shear strength were considered acceptable because of the smaller values compared to the typical cohesion of SM (Silty Sand) which was set at 20°. Moreover, slope stability analyses conducted using only the effect of tension crack produced a safety factor of 0.996 while those with only the effect of rainfall had 1.172. The results showed that water pressure in tension crack had a more significant influence on slope stability compared to rain. However, it was important to state that the variation in the significance of each factor was based on the assumptions made during the analysis.

The article discusses the application of statistical metrics for the validation of comprehensive non-linear soil models. The assessment was carried out on the basis of triaxial, oedometer, consolidation and plate load tests of sandy and clay soils. Validation of non-linear soil models was divided depending on the problem type: strength-type problem and strain-type problem. For a strength-type problem the indicators of failure points should be compared. In the course of strain-type problem the stress-strain curves should be compared. Average ratio of experimental data to calculated and coefficient of variation showed the highest efficiency for standard triaxial and oedometer tests, as they allow taking into account the specificity of the deviation and its variability. Other statistical metrics are less effective in geotechnical engineering. Validation according to consolidation tests is recommended to be performed based on the analysis of the time of 100% primary consolidation and the slope of the consolidation curve during the creep phase. In the course of stress paths analysis (for example, in the course of unloading and further reloading), the advantage should be given to visual assessment. Acceptable values of validation metrics for geotechnical engineering are proposed. The specific values of deviations should be determined by the analyst depending on the required accuracy of calculations, the responsibility of the construction object and the assessment of the risk of an accident.

Aiming at some stress-induced failure phenomena in surrounding rock that occur during the construction of super-long and deep-buried tunnels, a method for estimating the in situ stress in the tunnels based on multivariate information integration is proposed, which uses a small amount of in situ stress measurement, stereographic projection technology, and a numerical simulation method. Firstly, by conducting a macroscopic analysis of the regional geological structure, topography, and pre-excavated small tunnels (such as exploration of adits and pilot tunnels), the strength of the tectonic stress field and the orientation of the principal stresses in the tunnel sections are preliminarily determined. Secondly, the reliability of the in situ stress measurement data were analyzed using full-space stereographic projection and the plane stress projection method. Then, some representative measurement points that reflected the distribution characteristics of in situ stress in the project area, on the whole, were determined. Thirdly, the finite difference (FDM) and multiple regression analysis (MRA) methods were used to inverse the in situ stress field in the project area. The proposed method was applied to a super-long and deep-buried tunnel project in Qinling, and the in situ stress distribution characteristics of the tunnel sections at different mileages were obtained. The results show that both the calculated principal stress values and the azimuth angle of the maximum horizontal principal stress are in good agreement with the measured ones, indicating that the method used in this study is reasonable. Finally, the typical surrounding rock failure phenomena encountered during the excavation of the project were investigated, and targeted treatment measures were proposed. The research results can provide references for support design and disaster management of surrounding rock in deep-buried long tunnels. [ABSTRACT FROM AUTHOR]

On 17 November 2016, 16 workers lost their lives as a result of a landslide in an open pit copper mine in Madenköy district of Siirt province in southeastern Turkey. The main aims of this study is to investigate the causes of the accident, to reveal its mechanism and to be prepared for such mass movements that may occur in the future. The study area consists from the north and getting younger towards the south. Further investigations have shown that hydrogeological conditions and geological structure are the most important factors affecting the units. A large number of boreholes were drilled to reveal the 3D features of the area and cross sections were obtained. The most critical geotechnical numerical cross section that best represents the mass movements was selected and the stability of the area was analysed by finite element method in dry and water saturated conditions using Plaxis 2D and 3D Connect Edition v22 software. [ABSTRACT FROM AUTHOR]

The determination of soil parameters in geotechnical engineering and their variations during the construction process have long been a focal point for engineering designers. While the artificial neural network (ANN) has been employed for back analysis of soil parameters, its application to caisson sinking processes remains limited. This study focuses on the Nanjing Longtan Yangtze River Bridge project, specifically the south anchoring of an ultra-large rectangular caisson. A comprehensive analysis of the sinking process was conducted using 400 finite element method (FEM) models to obtain the structural stress and earth pressure at key locations. Multiple combinations of soil parameters were considered, resulting in a diverse set of simulation results. These results were then utilized as training samples to develop a back-propagating artificial neural network (BP ANN), which utilized the structural stress and earth pressure as input sets and the soil parameters as output sets. The BP ANN was individually trained for each stage of the sinking process. Subsequently, the trained ANN was employed to predict the soil parameters under different working conditions based on actual monitoring data from engineering projects. The obtained soil parameter variations were further analyzed, leading to the following conclusions: (1) The soil parameters estimated by the ANN exhibited strong agreement with the original values from the geological survey report, validating their reliability; (2) The surrounding soil during the caisson sinking exhibited three distinct states: a stable state prior to the arrival of the cutting edges, a strengthened state upon the arrival of the cutting edges, and a disturbed state after the passage of the cutting edges; (3) In the stable state, the soil parameters closely resembled the original values, whereas in the strengthened state, the soil strength and stiffness significantly increased, while the Poisson's ratio decreased. In the disturbed state, the soil strength and stiffness were slightly lower than the original values. This study represents a valuable exploration of back analysis for caisson engineering. The findings provide important insights for similar engineering design and construction projects. [ABSTRACT FROM AUTHOR]

The Moroccan road network is susceptible to multiple landslides annually, particularly in the northern regions due to high rainfall and specific geology. These events result in significant economic and social negative consequences, highlighting the need for sustainable and cost-effective solutions for network maintenance. This study outlines the methodology employed in addressing the issues within the RR410 regional road (Rifain region of Morocco), which entailed a thorough examination of the malfunctions, specific surveys, laboratory testing, and problem modeling. By incorporating long-term test-derived shear strength parameters, the model indicated that the road platform was stable, and back analysis using TALREN 4 software allows for model calibration. At kilometric point 23, using earthwork-based solutions (e.g., purging and replacing the base layer, employing granular water-insensitive substitution material) was found to provide a sustainable alternative to the expensive reinforced concrete-based solutions commonly used. Furthermore, these solutions contributed to the use of environmentally friendly and locally sourced materials. Road alignment rectification to anchor the platform in suitable soil was also an effective solution, as demonstrated at kilometric point 48. Additionally, enhancing the drainage and sanitation infrastructure, such as installing draining trenches, spurs, and reinforcing existing water structures, is a crucial aspect of addressing most landslides in the region. [ABSTRACT FROM AUTHOR]

The purpose of this article is to provide an effective approach to evaluate slope stability in real-time in a reservoir area, which is significant for carrying out risk management for landslide disaster prevention in various engineering practices. A comprehensive idea for stability estimation of bank slope under the influence of rainfall or the reservoir water level is presented in this work. Slope stability analysis and back analysis of soil parameters are both included based on numerical simulation. The mechanical parameters of the bank slope were first back-analyzed using particle swarm optimization (PSO), and real-time stability analysis with high accuracy and efficiency was then established based on multiple continuously monitored displacements. Two case studies were carried out in this study. The results show that (1) based on the real-time monitored displacement and numerical simulation, the mechanical parameters of the slope can be reasonably retrieved through PSO; and (2) based on the inverse mechanical parameters, the safety factors of the slope can be numerically obtained, so that the real-time estimation of slope stability can be realized.

Determining the properties of mine waste dump material is very difficult, it is caused by the difference of dimension between the laboratory equipment and field material size distribution. This study aims to determine the material properties from mine waste dump material using back analysis method after failure was occurred. The back analysis method is based on a trial and error concept which focuses on failure geometry and it is conducted by varying the cohesion and friction angle until the safety factor was less than 1.0. The laboratory results showed a 66.2 kPa change as well as a 48.8°friction angle deviation in mine waste dump material properties, while the back analysis indicated 33.7 kPa and 27.4°. It means, there is a reduction in the value. Therefore, the increasing in these properties are expected to allow the redesign of heap stability.

ABSTRACT: Numerical back analysis is a valuable tool available to rock mechanics researchers and practitioners. Recent studies related to back analysis methods focused primarily on applications of increasingly sophisticated optimization algorithms (primarily machine learning algorithms) to rock mechanics problems. These methods have typically been applied to relatively simple problems; however, more complex back analyses continue to be conducted primarily through ad hoc manual trial-and-error processes. This paper provides a review of the basic concepts and recent developments in the field of numerical back analysis for rock mechanics, as well as some discussion of the relationship between back analysis and more broadly established frameworks for numerical modelling. The challenges of flexible constraints, non-uniqueness, material model limitations, and disparate data sources are considered, and representative case studies are presented to illustrate their impacts on back analyses. The role of back analysis (or “model calibration”) in bonded particle modelling (BPM), bonded block modelling (BBM), and synthetic rock mass (SRM) modelling is also considered, and suggestions are made for further studies on this topic.

Construction of urban tunnel engineering in mountainous karst regions involves a plethora of uncertain geological risk factors. Due to cost and schedule constraints, hydrogeological and engineering geological risk sources cannot be identified in detail, leading to frequent disasters. Expert scoring, which is influenced by human subjectivity, is a common method for disaster evaluation in tunnel engineering, and some evaluation indicators are difficult to quantify. In order to address these issues, Guiyang rail transit line 2 Phase I project was selected as a case study to establish a risk disaster evaluation system for urban tunnel engineering in mountainous karst regions. The location and type of the disasters during construction were recorded for 26 running tunnels, and geological risk factors that were significantly correlated were selected as evaluation factors. The coupling relationship between the frequency of disaster occurrence and the geological risk factors was inverted, leading to the establishment of the risk disaster evaluation system of urban tunnel engineering in mountainous karst region. The evaluation results demonstrate that the degree of consistency between the frequency of disaster occurrence and the segmentation results of the evaluation system is more than 69%, indicating that the evaluation system is capable of predicting the frequency of disaster occurrence effectively. [ABSTRACT FROM AUTHOR]

In response to the problem of significant post-construction settlement that may occur in a motor racing circuit (MRC), two representative composite foundation testing areas, PHC pile (pre-tensioned spun high-strength concrete pile) and CFG pile (cement fly ash gravel pile), were selected for field tests to obtain the deformation law of pile–soil. Then, finite element numerical simulation was used to carry out back analysis on the geological mechanical parameters of the testing areas. The results showed that the error of soil settlement between the piles in the PHC pile and CFG pile testing areas were 8.2% and 9.6%, respectively, with good inversion precision. The obtained geological mechanical parameters can be used to predict the settlement of the rest of the MRC. On this basis, a finite element numerical model was constructed to analyze the bearing and deformation characteristics of the foundation of the MRC under five types of working conditions that may cause significant post-construction settlement. It showed that the settlement of the embankment was large in the middle and small on both sides after the consolidation of the embankment. The maximum settlement was about 27.0 mm, and the maximum longitudinal uneven settlement ratio of the embankment was 1.3/4000. The axial force of piles in the PHC pile and CFG pile composite foundations increased first and then decreased with depth. The maximum bending moment was located at the foot of slopes or at the boundary of strata, which was relatively small in the middle of the embankment. The deformation of the embankment and the bearing capacity of the piles could meet engineering requirements. This study has certain guiding significance for the design and construction of similar pile-net composite foundations.

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At present, there is no commonly used method for predicting soil resistance to the driving (SRD) of monopiles, because all available methods are developed based on an installed offshore pile with a diameter of 2–3 m. In addition, due to the complexity of soil profiles in situ, the accuracy of methods used is often not stable under different soil conditions. Based on two typical stratified soil conditions of offshore wind farms in the East China Sea, which are clay-interlayered sand and sand-interlayered clay where, according to the pile driving records of the monopiles in sites, the SRD is obtained by back analysis using the method of the wave equation. At the same time, SRD is also calculated using Steven and Alm methods and compared with that of the back analysis. The results show that the SRDs from the Steven and Alm methods are basically consistent with that of the back analysis, but the predicted SRD of the clay layer is higher than that of back analysis, while the predicted SRD of the sand layer is lower. Based on the characteristics of SRD in different soil layers, a modified method for calculating unit friction in clay and the unit end resistance in sand is proposed for stratified soil, and the error between SRD of the proposed method and of the back analysis was approximately 20%. It could be helpful to improve the accuracy of the monopile drivability analysis in stratified soil. [ABSTRACT FROM AUTHOR]

Landslide risk analysis is a common geotechnical evaluation and it aims to protect life and infrastructure. In the case of sensitive clay zones, landslides can affect large areas and are difficult to predict. Here we propose a methodology to determine the landslide hazard across a large territory, and we apply our approach to the Saint-Jean-Vianney area, Quebec, Canada. The initial step consists of creating a 3D model of the surficial deposits of the target area. After creating a chart of the material electrical resistivity adapted for eastern Canada, we applied electric induction to interpret the regional soil. We transposed parameter values obtained from the laboratory to a larger scale, that is to a regional slope using the results of a back analysis undertaken earlier, on a smaller slide within the same area. The regional 3D model of deposits is then used to develop a zonation map of slopes that are at risk and their respective constraint areas with the study region. This approach allowed us to target specific areas where a more precise stability analysis would be required. Our methodology offers an effective tool for stability analysis in territories characterized by the presence of sensitive clays. [ABSTRACT FROM AUTHOR]

Determining the properties of mine waste dump material is very difficult, it is caused by the difference of dimension between the laboratory equipment and field material size distribution. This study aims to determine the material properties from mine waste dump material using back analysis method after failure was occurred. The back analysis method is based on a trial and error concept which focuses on failure geometry and it is conducted by varying the cohesion and friction angle until the safety factor was less than 1.0. The laboratory results showed a 66.2 kPa change as well as a 48.8°friction angle deviation in mine waste dump material properties, while the back analysis indicated 33.7 kPa and 27.4°. It means, there is a reduction in the value. Therefore, the increasing in these properties are expected to allow the redesign of heap stability. [ABSTRACT FROM AUTHOR]

Copyright of Duzce University Journal of Science & Technology is the property of Duzce University Journal of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study was conducted to determine the cause of landslides in the toll road embankment of the national road project in the Porong-Sidoarjo area. The landslide was observed only on the north side of the embankment, with a maximum height of 7.8 meters from the subgrade despite the reinforcement with a retaining wall and pile foundation. The land shift and subsidence on the Northside led to a decline in the embankment elevation and the displacement to a maximum depth of 3.50 m. Back analysis through the limit equilibrium method was used to determine the strength of the existing reinforcement against the landslide. The results showed that the heavy rain was indeed one of the causes of landslides in the location, while the main cause was the depth of soft soil, much deeper than those in the surrounding locations. This is why a severe landslide was recorded on one side of the embankment. Moreover, the existing anti-slide pile reinforcement was discovered not to be sufficient due to its shallower length compared to the area of the landslide, and this was associated with the absence of overall stability analysis in this design. The findings showed that it is necessary to conduct a comparative study between the overall stability and the active and passive forces analyses for the soil to produce the safest design required to avoid landslides. [ABSTRACT FROM AUTHOR]

Numerical simulation is important for the risk assessment of subaerial landslide-induced tsunami (SLIT) hazards; however, their predictive performances are thus far limited as these works fail to consider the involved uncertainties. We propose a novel probabilistic risk assessment framework for quantifying several uncertainties, such as the model parameters and bias. We successfully couple the numerical simulation and Bayesian-based back analysis method. The wave height and run-up are captured by a three-dimensional granular-flow landslide and renormalization group turbulence model in FLOW3D; furthermore, the relevant parameter information is calibrated using a Markov chain Monte Carlo algorithm with the differential evolution adaptive metropolis. In this framework, which incorporates the prior information of model parameters, and field observations, as well as numerical model bias, calibrated parameters exhibit a probability distribution with a small standard deviation, facilitating improved risk prediction capabilities; In addition, the optimized adaptive Kriging-based surrogate model with multiple outputs is established to reduce the computation cost of the framework with acceptable accuracy. The framework's outputs, including a spatial probability that tsunamis inundate elements at risk, and a hazard zonation map, contribute to the evaluation of SLIT hazards and prioritize mitigation measures. Our work introduces a paradigm for the application of the framework, demonstrated through studies of two landslides in Wu Gorge. Without loss of generality, the framework offers a novel perspective for the quantitative assessment of SLIT hazards. • Propose a Bayesian-based back analysis framework for assessing the subaerial landslide-induced tsunami hazard. • Successfully present the spatial probability and risk zonation maps considering multi-uncertainties. • Overcoming the computational cost problem in quantifying uncertainty. • This framework can combine various numerical methods. • Results can be utilized in the probability tsunami hazard analysis framework. [ABSTRACT FROM AUTHOR]

Aiming to investigate the problem that dam-monitoring data are difficult to analyze in a timely and accurate automated manner, in this paper, we propose an automated framework for dam health monitoring based on data microservices. The framework consists of structural components, monitoring sensors, and a digital virtual model, which is a hybrid of a finite element (FE) model, a geometric model, a mathematical model, and a deep learning algorithm. Long short-term memory (LSTM) was employed to accurately fit and predict the monitoring data, while dynamic inversion and simulation were used to calibrate and update the data in the hybrid model. The automated tool enables systematic maintenance and management, minimizing errors that are commonly associated with manual visual inspections of structures. The effectiveness of the framework was successfully validated in the safety monitoring and management of a practical dam project, in which the hybrid model improved the prediction accuracy of monitored data, with a maximum absolute error of 0.35 mm. The proposed method can be considered user-friendly and cost-effective, which improves the operational and maintenance efficiency of the project with practical significance.

In this study, the back analysis of 7·25 landslide triggered by rainfall on the north side of Fushun West Open-pit Mine was carried out, and the obtained initial water level, failure time and failure sliding surface are all consistent with the actual situation, thus verifying the correctness and effectiveness of the calculation and results. On this basis, the influence of drainage pipe failure and depth of weathering fracture zone on slope stability was studied. The calculation results show that the drainage pipe can effectively reduce the underground water level and improve the slope stability. Once the drainage pipe enters in failure state, the slope safety will be decreased, and the slope may be unstable in a shorter time under the condition of rainfall. Therefore, a regular maintenance of drainage pipe is essential for its effective work. The weathering fracture zone also has a great influence on the slope stability. Under the influence of weathering and unloading, the depth of weathering fracture zone may change dynamically, so it is necessary to enhance dynamic monitoring to ensure the safety and stability of the slope.

Geomaterial mechanical parameters are critical to implementing construction design and evaluating stability through feedback analysis in geotechnical engineering. The back analysis is widely utilized to identify and calibrate the geomaterial mechanical properties in geotechnical engineering. This study developed a novel back-analysis framework by combining a reduced-order model (ROM), grey wolf optimization (GWO), and numerical technology. The ROM was adopted to evaluate the response of the geotechnical structure based on a numerical model. GWO was used to search and identify the geomaterials properties based on the ROM. The developed back analysis framework was applied to a circular tunnel and a practical tunnel for determining the mechanical property of the surrounding rock mass. The results showed that the ROM could be an excellent surrogated model and replaced it with the numerical model. The obtained geomaterial properties were in excellent agreement with the actual properties. The deformation behavior captured by the developed framework was consistent with the theoretical solution in a circular rock tunnel. The developed framework provides a practical, accurate, and convenient approach for calibrating the geomaterial properties based on field monitoring data in practical geotechnical engineering applications. [ABSTRACT FROM AUTHOR]

Due to the characteristics of soil–rock composites and large-span arches, the surrounding rock parameters of stations are difficult to obtain accurately under soft upper and hard lower geological conditions when the arch cover method is used to carry out the construction of a large-span underground excavation station. To optimize the design of stations and guide the next step of construction, an intelligent inverse analysis method, the Gaussian process differential evolution co-optimization algorithm (GP-DE algorithm), is proposed for the arch cover method for station construction. Taking the Shikui Road station of the Dalian Metro Line Five as the engineering background, the finite element model of FLAC3D is established. By combining the measured data of the sensor and the monitoring data obtained using the orthogonal scheme, this algorithm is used for the joint back analysis of displacement stress and the accuracy of the inversion parameters is verified by forwarding the calculation for FLAC3D. By using the obtained surrounding rock parameters, the demolition length of the center diaphragm to the Shikui Road station is optimized. Under different numbers of training samples, the inversion effect of the GP-DE algorithm and the other three common back-analysis algorithms is compared and analyzed. Finally, based on the iteration rate and convergence effect, the value range of the differential evolution algorithm parameters F and CR is given. The results show that the forward calculation results of the parameters obtained from the back analysis are in good agreement with the actual values, and the accuracy of the back-analysis results is high. [ABSTRACT FROM AUTHOR]

It is well-known that the longwall mining method (with roof caving) is widely used in underground mining extraction for bedded deposits (e.g. coal) due to its numerous advantages. Generally, this method is not commonly applied for ore deposits such as copper deposit. In Poland, the longwall mining method has been tested for thin copper deposits at the Polkowice-Sieroszowice copper mine (KGHM). Various failure modes were observed during longwall operation in the 5A/1 panel. This paper aims to examine these occurred failures. To do so, an analysis has been conducted using 3D numerical modelling to investigate the failure mode and mechanism. Based on the 3D numerical modelling results with extensive in situ measurements, causes of failure are determined and practical recommendations for further copper longwall operations are presented.

Claystone is potentially the main rock formation for the deep geological disposal of high-level radioactive nuclear waste. A major factor that affects the deformation of the host medium is effective stress. Therefore, studying the effective stress principle of claystone is essential for a stability analysis of waste disposal facilities. Consolidated drained (CD) tests were carried out on claystone samples to study their effective stress principle in this paper. Firstly, two samples were saturated under a specified confining pressure and pore pressure for about one month. Secondly, the confining pressure and pore pressure were increased to a specified value simultaneously and then reverted to the previous stress state (the deformations of the samples were recorded during the whole process). Different incremental combinations of the confining pressure and pore pressure were tried at this step. Finally, the effective stress coefficients of the samples were obtained through a back analysis. Furthermore, some potential influencing factors (the neutral stress and loading rate) of the effective stress coefficient were also studied through additional tests. Some interesting results are worth mentioning: (1) the effective stress coefficient of claystone is close to one; (2) the neutral stress and loading rate may have little effect on the effective stress coefficient of claystone.

Aiming at some stress-induced failure phenomena in surrounding rock that occur during the construction of super-long and deep-buried tunnels, a method for estimating the in situ stress in the tunnels based on multivariate information integration is proposed, which uses a small amount of in situ stress measurement, stereographic projection technology, and a numerical simulation method. Firstly, by conducting a macroscopic analysis of the regional geological structure, topography, and pre-excavated small tunnels (such as exploration of adits and pilot tunnels), the strength of the tectonic stress field and the orientation of the principal stresses in the tunnel sections are preliminarily determined. Secondly, the reliability of the in situ stress measurement data were analyzed using full-space stereographic projection and the plane stress projection method. Then, some representative measurement points that reflected the distribution characteristics of in situ stress in the project area, on the whole, were determined. Thirdly, the finite difference (FDM) and multiple regression analysis (MRA) methods were used to inverse the in situ stress field in the project area. The proposed method was applied to a super-long and deep-buried tunnel project in Qinling, and the in situ stress distribution characteristics of the tunnel sections at different mileages were obtained. The results show that both the calculated principal stress values and the azimuth angle of the maximum horizontal principal stress are in good agreement with the measured ones, indicating that the method used in this study is reasonable. Finally, the typical surrounding rock failure phenomena encountered during the excavation of the project were investigated, and targeted treatment measures were proposed. The research results can provide references for support design and disaster management of surrounding rock in deep-buried long tunnels.

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The back analysis is an effective tool to determine the representative values of rock mass mechanical properties in rock engineering. The surrogate model is widely used in back analyses since analytical or numerical models are usually unavailable for practical engineering problems. This study proposes a novel back analysis framework by adopting the AdaBoost algorithm for deriving the surrogate model. Moreover, the simplicial homology global optimization (SHGO) algorithm, which is robust and applicable for a black-box global problem, is also integrated into the framework. To evaluate the performance, an experimental tunnel in Goupitan Hydropower Station, China, is introduced, and the representative rheological properties of the surrounding rock are obtained by applying the proposed framework. Then the computed displacements based on the acquired properties via both surrogate and numerical models are compared with field measurements. By taking triple-day data, the discrepancy between the calculated and field-measured displacements is less than 0.5 mm This validates the reliability of the obtained properties and the feasibility of the proposed framework. As an AdaBoost-based method, the proposed framework is sensitive to noise and outliers in the data, the elimination of which is recommended before application. [ABSTRACT FROM AUTHOR]