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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.

Loess landslides pose significant physical and environmental threats to communities of the Heifangtai Terrace in Gansu Province, China. Estimating potentially affected areas using dynamic numerical simulations provides a foundation for risk assessment and management. However, current studies often use rheological input parameters derived from the back analysis of an individual historical landslide, which requires that the potential landslide is quite similar to the historical landslide to guarantee the accuracy of predictions. We collected data from 20 loess flowslides that occurred from 2015 to 2019 in the Heifangtai Terrace. A friction model embedded in MassFlow was used to simulate run-out behavior. Accumulation depths at multiple control points were used as observation information. A multi-objective optimization back analysis was used to calibrate optimal rheological parameters for each flowslide, yielding a region-specific database of 20 datasets for statistical analyses. Finally, two flowslides that occurred in 2019 were employed as potential landslides to conduct probabilistic run-out predictions based on the database. These predictions agreed well with the observed accumulation areas in both cases, thus validating our method. This database will be useful for future landslide run-out predictions in this area. [ABSTRACT FROM AUTHOR]

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.

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.)

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]

Aiming at the problem of time-consuming calculation due to a large number of numerical calculation models used in the back analysis of geomechanical parameters in complex underground engineering, a new bionic optimization surrogate back analysis method honey badger algorithm-Gaussian process regression-FLAC3D(HBA-GPR-FLAC3D) was proposed. The error between the numerical calculation results of the surrounding rock and the measured value was taken as the optimization objective function, and the geo-mechanical parameters was taken as the optimization variables. The HBA with excellent optimization performance was used to search for the global minimum value of the objective function. In the local optimization of the current optimal operator neighborhood, the GPR surrogate model was used as the operator fitness evaluation tool instead of the objective function constructed based on FLAC3D calculation. The research shows that compared with the back analysis method based on the bionic optimization algorithm, the number of numerical model calls of the proposed method is significantly reduced under the condition of the same calculation accuracy. It is suitable for rock mechanics parameters of complex underground engineering whose single-time numerical calculation is relatively time-consuming. [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.)

Municipal sludge is a sedimentation waste produced during the wastewater process in sewage treatment plants. Among recent studies, pilot and field tests showed that chemical conditioning combined with vacuum preloading can effectively treat municipal sludge. To further understand the drainage and consolidation characteristics of the conditioning sludge during vacuum preloading, a large deformation nonlinear numerical simulation model based on the equal strain condition was developed to simulate and analyze the pilot and field tests, whereas the simulation results were not satisfactory. The results of the numerical analysis of the pilot test showed that the predicted consolidation degree was greater than that measured by the field tests, which is attributed to the relatively low permeability layer formed during the preloading process of the prefabricated vertical drain. To better reflect the consolidation process of the conditioned sludge, a simplified analysis method considering the low permeability layer around the prefabricated vertical drain was proposed. The initial permeability coefficient of the low permeability layer is determined via numerical simulations using finite difference method. The predicted settlement curve was in good agreement with the measured results, which indicated that the numerical simulation based on the equal strain condition considering the relatively low permeability layer can better analyze the consolidation process of ferric chloride-conditioning sludge with vacuum preloading. [ABSTRACT FROM AUTHOR]

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]

The study focuses on a failure in the form of heaving and sliding at the external Overburden (OB) dump in the Open-cast Mine site. Through a unique approach, the Monte Carlo Simulation technique was used to conduct a probabilistic back and slope stability analysis to assess the dump sections. The study considered the water table level and dumps shear strength parameters as random variables. The results provide valuable insights into understanding the factors influencing the OB dump over weak strata. As preventive measures, gabion walls and rockfill trench were used to reduce the probability of failure (P f) of dumps that increased in height to 75 m and 90 m. The maximum percentage reduction in the P f for the gabion wall was 51.49% and 27.43% for 75 m and 90 m dump sections. For the rock-fill trench, the maximum percentage reduction in the P f was 61.28% and 57.31% for 75 m and 90 m dump sections. • Groundwater table as random variable accounts for water variability realistically. • The severity of the on-site dump can be analyzed using the unique probabilistic methodology helpful in predetermining failure. • Sensitivity study of random variable effect was analyzed. • The effect of a weak soil layer in the ground on dump stability was examined. • Preventive measure's effect on increasing the stability of the dump was studied. [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]

In complex mountainous terrains, tunnel construction faces unique challenges from high-temperature water inrush hazards, a systemic risk arising from the interplay of stress, seepage, and temperature fields. Traditional simulation methods, focusing on isolated disaster scenarios, fall short in addressing the multifaceted nature of these risks due to geological ambiguity and data incompleteness. Digital twin technology presents an effective solution to these challenges; however, its core challenge lies in how to utilize digital twin technology for data-model-co-driven simulation analysis of coupled multi-physical fields in situations of incomplete data. This paper introduces a digital twin paradigm for the simulation analysis of water inrush, which significantly enhances efficiency and accuracy through the integration of advanced machine learning and finite element analysis techniques. Specifically, this is achieved by combining a high-precision geological modeling method based on Gaussian Processes (GP) with a parameter calibration method through Gaussian Process-Differential Evolution (GP-DE) back-analysis. Firstly, a voxel structure is utilized to integrate the multi-field attribute features of the tunnel environment. Secondly, through the integration of multi-source advanced geological prediction data, we construct a dynamic digital twin model of the tunnel environment leveraging machine learning techniques. To overcome the issue of low modeling accuracy, the GP is employed, enhancing the exploitation of latent information within multi-source geophysical data. Lastly, we utilize the GP-DE back-analysis method to calibrate the parameters of the tunnel environment, thereby enhancing the precision and reliability of water inrush simulations. The method has been validated through application to a section of an ultra-high-temperature water inrush tunnel in China, featuring a burial depth of 230 meters. The accuracy of the method is corroborated by the monitoring data from the tunnel, supporting dynamic optimization design and safety prevention measures during construction. • Introduces a digital twin for simulating high-temperature water inrush in tunnels. • Enhances geological modeling by integrating multi-source data and machine learning. • Calibrates tunnel parameters efficiently using the GP-GE back-analysis with a THM model. • The method was validated in a ultra-high-temperature water inrush tunnel in China. [Display omitted] [ABSTRACT FROM AUTHOR]

Design codes and recommended practices for geotechnical structures generally include some conservatism to take into account any possible source of uncertainty, with conservative design being generally accepted as safe. Such approaches are not appropriate for offshore wind turbines where both over-and-under designs would result in a sub-optimal performance in terms of structural dynamics. The soil surrounding wind turbines is a main contributor to their stiffness, it is also one of the major sources of uncertainty, which makes an accurate prediction of the structural dynamics a rather difficult task. Monitoring data on wind turbines can provide useful insight into their real in-situ behaviour, allowing designers to examine the validity of design assumptions further. In this paper, the bending moments of five monitored wind turbine monopiles are back analysed, using 3D FEM and 1D beam–column models in which the soil is modelled according to API RP2 GEO recommendations, and the rule-based PISA reaction curves. It is found that despite the efforts to get an as accurate soil response as possible, the monitored bending moments are overestimated by the 3D FEM models at some locations, reflecting a mismatch between the simulated and monitored wind turbine monopiles. The possible effect of scour protection is highlighted. The API-based 1D beam–column models overestimate bending moments, rotations, and displacements and underestimate the wind turbine stiffness, while the PISA models are able to give satisfactory results. • Five site-specific wind turbine models are established. The calibration of advanced soil constitutive models is presented. • Bending moments on five wind turbines are computed using both 3D and 1D models and are compared to the monitoring data. • A clear mismatch is shown between the simulated and the monitored bending moments. • One of the possible reasons for this mismatch is the missing contribution of the scour protection in the simulations. • The API RP2 GEO recommendations overpredict the wind turbine's bending moments, rotations and displacements. [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]

In this article, the ability of the artificial neural network-genetic algorithm (ANN-GA) to perform back analysis and predict maximum surface settlement in mechanised tunnelling is investigated. The required data of the ANN meta-model was generated using 150 three-dimensional finite-difference simulations. The global sensitivity analysis was performed on 19 parameters, including 17 geotechnical parameters of soil layers and 2 operational parameters of face pressure and grouting pressure. The predicted results using ANN were in good agreement with the numerical simulations so that R = 99% and rRMSE = 1.5% are obtained. Then, back analysis was performed using the ANN-GA hybrid algorithm and the geotechnical data of the monitoring point were updated using the maximum surface settlement monitored at this point. Also, for the geotechnical parameters considered in the design phase, using the same algorithm, the number of operational parameters required for optimal settlement was predicted. [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.

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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]

Many significant landslide movements are often observed in the upper weathering zone of flysch, which constitutes the most critical landslide-prone geological formation in Western Greece. In this article, a laboratory approach is adopted to investigate the behavior of highly weathered and tectonically decomposed flysch for slope stability analyses with the performance of large shear testing in reconstituted soil specimens. The testing program included several reconstituted flysch specimens derived from three representative landslides. Tests under large direct shearing (300 × 300 × 120 mm) were conducted in moisture- and density-controlled conditions and ring shear tests were conducted in the finer material. The test results revealed that the values of the effective angle of friction in the flysch material decrease with the increasing water content. Moreover, dense specimens showed curved failure envelopes due to dilatancy, especially in dry conditions. A comparison of laboratory test results with those obtained by performing back-analyses under saturated conditions has shown that the sliding of the weathered and decomposed flysch mainly depends on its residual angle of friction which was found to be 1°–6° lower than the ultimate angle of friction as it was estimated by the large shear tests. [ABSTRACT FROM AUTHOR]

During tunnel construction, the ground properties, initially evaluated, are continuously assessed and verified through back analysis. This procedure generally requires many numerical analyses, so a metamodel based on artificial neural networks has been used to reduce the number of analyses. More datasets can be used to create more reliable metamodels. However, there are no established rules regarding the optimum number of datasets for a reliable metamodel. Metamodels predicting the vertical displacement of the tunnel crown using five ground parameters (unit weight (γ), uniaxial compressive strength (UCS), material constant mi, geological strength index (GSI), and coefficient of lateral pressure (K)), with 3, 4, 6, 8, and 10 values per property, were created to confirm the reliability of the metamodel based on the number of datasets in this study. Metamodels using 6 and 8 values for each property showed 5% and 1% mean absolute percent errors, respectively. These numbers of each of the properties would be appropriate for developing the metamodel. Among the five parameters, only the results of the global sensitivity analyses of GSI and K are higher than 0.9. According to these results, it is verified that assessments based only on these parameters are sufficient in the back analysis. [ABSTRACT FROM AUTHOR]

Downhole dynamic compaction (DDC) has been commonly used in China to stabilize collapsible soil through the application of construction and demolition waste material (CDW). DDC basically forms a column inside the soil stratum which is similar to a stone column except DDC materials are put in sequence and then compacted by using DDC hammer. Due to its attractive features such as its big diameter, feasibility of using oversized material particles, rapid and simple construction technique, it is used as one of the ground improvement methods for an airport project in Indonesia. Despite of all the advantages provided by DDC, it is difficult to obtain DDC parameters from laboratory tests as it is difficult to replicate the compaction effort induced by the DDC hammer and laboratory tests are not commonly employed for oversized materials. Hence, alternative method is required to evaluate DDC parameters. In this study, static load test is conducted to determine load-deformation curve of the DDC pile. Soil parameters are first determined through soil test data such as standard penetration test (SPT), laboratory test and also pressure meter tests. Correlation between pressure meter tests and SPT test result is also carried in order to interpret the soil parameter at the site. Axisymmetric finite element analysis is then carried by using MIDAS GTS NX in order to back analyses DDC parameters by matching the simulation curve with load settlement curve of the DDC. In this paper, it is shown that back analysis using hardening soil model for DDC material can be used to match simulation curve with the load-deformation curve.

In this research, three- dimension finite difference method was applied to simulate the tunnel excavation by earth pressure balance (EPB) boring machine of Tehran Metro Line 7 tunnel in Iran. Sensitivity analysis and parameter identification was carried out by Morris Elementary Effect method to evaluate the relative sensitivity of model for each input parameter. Then, artificial neural network (ANN) was used as a meta model to predict model response for the dataset of selected sensitive parameters. For this purpose, 100 numerical simulation has carried that a database including 1500 data was compiled for using in ANN. Thereafter, PSO algorithm was employed as a parameter identification technique to find the optimized values of the parameters according to monitoring surface settlement. Also, after material identification, the same PSO-ANN algorithm was used to optimize operation parameter (face pressure). The results showed that ANN prediction and numerical simulation with initial set of parameters has more than 98% concordance with about 2.4% RMSE and 0.014 MAE for all dataset. The optimized parameters gained via back analysis enable the meta model to well predict the ground settlement in the about 15 seconds. [ABSTRACT FROM AUTHOR]

Slope failures in the southwestern region of India in the state of Karnataka are induced by prolonged heavy rainfall during the monsoon season. Due to damage to livestock, infrastructure, and economy, slope failure incidences are a cause of concern and throw light on the need for landslide hazard assessment. There is a necessity for faster determination of landslide hazard and provision of an early warning system using geotechnical data that is limited due to the inaccessibility of the terrain. This study presents an attempt to demarcate areas prone to rainfall-induced landslide events using Transient rainfall infiltration and grid-based slope stability (TRIGRS) model and rainfall threshold. Slope failure events from 2013 to 2018 for the Kodagu district of Karnataka, India, are used to derive rainfall thresholds. Intensity–duration–frequency (IDF) curves of rainfall are derived to determine the return period of rainfall events which trigger slope failures in the region. Due to the paucity of data, back analysis is conducted using the TRIGRS model to determine the soil properties and initial water table depth. The return period of rainfall threshold in association with susceptibility mapping using the TRIGRS model facilitates estimation of landslide hazard at the regional scale. The results of this study could potentially be used as an early warning system and the basis for the design of slopes in this region. [ABSTRACT FROM AUTHOR]

Bodovalle is an iron carbonate mine located in Gallarta (near Bilbao, northern Spain), which is currently in the closure stage. The deposit was first exploited as an open-pit mine and later as an underground mine. The underground mine currently has 40 large rooms with rib pillars, occupying an area of 2,000 m long by 600 m wide. Room depth is around 200 m. The main geotechnical incident occurred in the NW1N zone, where an over-exploited rib pillar in poor condition was partially removed, leaving a 70-m roof span that eventually collapsed in 1999, resulting in a surface crater measuring 60 m in diameter. The collapse was preceded by noises and movements detected outside the mine. The subsidence was improved by means of infilling and monitoring. In 2014, residents living in homes built over the abandoned mine rooms detected very loud noises similar to those of 1999. The article describes a stability review carried out using advanced numerical methods (finite element method and boundary element method) and the geomechanical parameters obtained from a back analysis of the 1999 collapse.