Natural slopes usually display complicated exposed rock surfaces that are characterized by complex and substantial terrain undulation and ubiquitous undesirable phenomena such as vegetation cover and rockfalls.This st...Natural slopes usually display complicated exposed rock surfaces that are characterized by complex and substantial terrain undulation and ubiquitous undesirable phenomena such as vegetation cover and rockfalls.This study presents a systematic outcrop research of fracture pattern variations in a complicated rock slope,and the qualitative and quantitative study of the complex phenomena impact on threedimensional(3D)discrete fracture network(DFN)modeling.As the studies of the outcrop fracture pattern have been so far focused on local variations,thus,we put forward a statistical analysis of global variations.The entire outcrop is partitioned into several subzones,and the subzone-scale variability of fracture geometric properties is analyzed(including the orientation,the density,and the trace length).The results reveal significant variations in fracture characteristics(such as the concentrative degree,the average orientation,the density,and the trace length)among different subzones.Moreover,the density of fracture sets,which is approximately parallel to the slope surface,exhibits a notably higher value compared to other fracture sets across all subzones.To improve the accuracy of the DFN modeling,the effects of three common phenomena resulting from vegetation and rockfalls are qualitatively analyzed and the corresponding quantitative data processing solutions are proposed.Subsequently,the 3D fracture geometric parameters are determined for different areas of the high-steep rock slope in terms of the subzone dimensions.The results show significant variations in the same set of 3D fracture parameters across different regions with density differing by up to tenfold and mean trace length exhibiting differences of 3e4 times.The study results present precise geological structural information,improve modeling accuracy,and provide practical solutions for addressing complex outcrop issues.展开更多
Rock discontinuities such as joints widely exist in natural rock masses,and wave attenuation through rock masses is mainly caused by discontinuities.The displacement discontinuity model(DDM)has been widely used in the...Rock discontinuities such as joints widely exist in natural rock masses,and wave attenuation through rock masses is mainly caused by discontinuities.The displacement discontinuity model(DDM)has been widely used in theoretical and numerical analysis of wave propagation across rock discontinuity.However,the circumstance under which the DDM is applicable to predict wave propagation across rock discontinuity remains poorly understood.In this study,theoretical analysis and ultrasonic laboratory tests were carried out to examine the theoretical applicability of the DDM for wave propagation,where specimens with rough joints comprising regular rectangular asperities of different spacings and heights were prepared by 3D printing technology.It is found that the theoretical applicability of the DDM to predict wave propagation across rock discontinuity is determined by three joint parameters,i.e.the dimensionless asperity spacing(L),the dimensionless asperity height(H)and the groove density(D).Through theoretical analysis and laboratory tests,the conditions under which the DDM is applicable are derived as follows:and,.With increase in the groove density,the thresholds of the dimensionless asperity spacing and the dimensionless asperity height show a decreasing trend.In addition,the transmission coefficient in the frequency domain decreases with increasing groove density,dimensionless asperity spacing or dimensionless asperity height.The findings can facilitate our understanding of DDM for predicting wave propagation across rock discontinuity.展开更多
To investigate the long-term stability of deep rocks,a three-dimensional(3D)time-dependent model that accounts for excavation-induced damage and complex stress state is developed.This model comprises three main compon...To investigate the long-term stability of deep rocks,a three-dimensional(3D)time-dependent model that accounts for excavation-induced damage and complex stress state is developed.This model comprises three main components:a 3D viscoplastic isotropic constitutive relation that considers excavation damage and complex stress state,a quantitative relationship between critical irreversible deformation and complex stress state,and evolution characteristics of strength parameters.The proposed model is implemented in a self-developed numerical code,i.e.CASRock.The reliability of the model is validated through experiments.It is indicated that the time-dependent fracturing potential index(xTFPI)at a given time during the attenuation creep stage shows a negative correlation with the extent of excavationinduced damage.The time-dependent fracturing process of rock demonstrates a distinct interval effect of the intermediate principal stress,thereby highlighting the 3D stress-dependent characteristic of the model.Finally,the influence of excavation-induced damage and intermediate principal stress on the time-dependent fracturing characteristics of the surrounding rocks around the tunnel is discussed.展开更多
Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transp...Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time complexity.Network modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is established.This paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety.展开更多
Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results ca...Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.展开更多
It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimens...It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimensional(3D)models are relatively straightforward but time-consuming.One potential solution to enhance this process is to use machine learning algorithms to detect the 3D traces.In this study,a unique pixel-wise texture mapper algorithm generates a dense point cloud representation of an outcrop with the precise resolution of the original textured 3D model.A virtual digital image rendering was then employed to capture virtual images of selected regions.This technique helps to overcome limitations caused by the surface morphology of the rock mass,such as restricted access,lighting conditions,and shading effects.After AI-powered trace detection on two-dimensional(2D)images,a 3D data structuring technique was applied to the selected trace pixels.In the 3D data structuring,the trace data were structured through 2D thinning,3D reprojection,clustering,segmentation,and segment linking.Finally,the linked segments were exported as 3D polylines,with each polyline in the output corresponding to a trace.The efficacy of the proposed method was assessed using a 3D model of a real-world case study,which was used to compare the results of artificial intelligence(AI)-aided and human intelligence trace detection.Rosette diagrams,which visualize the distribution of trace orientations,confirmed the high similarity between the automatically and manually generated trace maps.In conclusion,the proposed semi-automatic method was easy to use,fast,and accurate in detecting the dominant jointing system of the rock mass.展开更多
Deep learning, especially through convolutional neural networks (CNN) such as the U-Net 3D model, has revolutionized fault identification from seismic data, representing a significant leap over traditional methods. Ou...Deep learning, especially through convolutional neural networks (CNN) such as the U-Net 3D model, has revolutionized fault identification from seismic data, representing a significant leap over traditional methods. Our review traces the evolution of CNN, emphasizing the adaptation and capabilities of the U-Net 3D model in automating seismic fault delineation with unprecedented accuracy. We find: 1) The transition from basic neural networks to sophisticated CNN has enabled remarkable advancements in image recognition, which are directly applicable to analyzing seismic data. The U-Net 3D model, with its innovative architecture, exemplifies this progress by providing a method for detailed and accurate fault detection with reduced manual interpretation bias. 2) The U-Net 3D model has demonstrated its superiority over traditional fault identification methods in several key areas: it has enhanced interpretation accuracy, increased operational efficiency, and reduced the subjectivity of manual methods. 3) Despite these achievements, challenges such as the need for effective data preprocessing, acquisition of high-quality annotated datasets, and achieving model generalization across different geological conditions remain. Future research should therefore focus on developing more complex network architectures and innovative training strategies to refine fault identification performance further. Our findings confirm the transformative potential of deep learning, particularly CNN like the U-Net 3D model, in geosciences, advocating for its broader integration to revolutionize geological exploration and seismic analysis.展开更多
In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for ...In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for acquiring discontinuity measurements from 3D models,such as point clouds generated using laser scanning or photogrammetry.However,even with numerous automated and semiautomated methods presented in the literature,there is not one single method that can automatically characterize discontinuities accurately in a minimum of time.In this paper,we critically review all the existing methods proposed in the literature for the extraction of discontinuity characteristics such as joint sets and orientations,persistence,joint spacing,roughness and block size using point clouds,digital elevation maps,or meshes.As a result of this review,we identify the strengths and drawbacks of each method used for extracting those characteristics.We found that the approaches based on voxels and region growing are superior in extracting joint planes from 3D point clouds.Normal tensor voting with trace growth algorithm is a robust method for measuring joint trace length from 3D meshes.Spacing is estimated by calculating the perpendicular distance between joint planes.Several independent roughness indices are presented to quantify roughness from 3D surface models,but there is a need to incorporate these indices into automated methodologies.There is a lack of efficient algorithms for direct computation of block size from 3D rock mass surface models.展开更多
In this research, a method called ANNMG is presented to integrate Artificial Neural Networks and Geostatistics for optimum mineral reserve evaluation. The word ANNMG simply means Artificial Neural Network Model integr...In this research, a method called ANNMG is presented to integrate Artificial Neural Networks and Geostatistics for optimum mineral reserve evaluation. The word ANNMG simply means Artificial Neural Network Model integrated with Geostatiscs, In this procedure, the Artificial Neural Network was trained, tested and validated using assay values obtained from exploratory drillholes. Next, the validated model was used to generalize mineral grades at known and unknown sampled locations inside the drilling region respectively. Finally, the reproduced and generalized assay values were combined and fed to geostatistics in order to develop a geological 3D block model. The regression analysis revealed that the predicted sample grades were in close proximity to the actual sample grades, The generalized grades from the ANNMG show that this process could be used to complement exploration activities thereby reducing drilling requirement. It could also be an effective mineral reserve evaluation method that could oroduce optimum block model for mine design.展开更多
Fetr6 is an underground mine in which chromite is extracted using stope and pillar mining method. Despite of all improving works such as roof supporting and replacing of ore pillars with concrete pillars, pillar No. 1...Fetr6 is an underground mine in which chromite is extracted using stope and pillar mining method. Despite of all improving works such as roof supporting and replacing of ore pillars with concrete pillars, pillar No. 19 failed and other pillars failed progressively as a domino effect and 4000 m2 of mine collapsed within a few minutes, consequently. For detail investigation, two 3-D numerical models were developed by 3Dec. The first, a base model, was used for estimation of stress on pillars just before failure and the other for investigation of rock burst in pillar No. 19. The results show that discontinuity parameters such as friction angle and shear stiffness is critical parameters in this pillar failure. In addition, it indicates that W/H ratio equal 0.3, the lack of ore extraction strategy and inadequate roof support are the major reasons for this failure. In this paper, the procedure of study was described.展开更多
To achieve the loading of the stress path of hard rock,the spherical discrete element model(DEM)and the new flexible membrane technology were utilized to realize the transient loading of three principal stresses with ...To achieve the loading of the stress path of hard rock,the spherical discrete element model(DEM)and the new flexible membrane technology were utilized to realize the transient loading of three principal stresses with arbitrary magnitudes and orientations.Furthermore,based on the deep tunnel of China Jinping Underground Laboratory II(CJPL-II),the deformation and fracture evolution characteristics of deep hard rock induced by excavation stress path were analyzed,and the mechanisms of transient loading-unloading and stress rotation-induced fractures were revealed from a mesoscopic perspective.The results indicated that the stressestrain curve exhibits different trends and degrees of sudden changes when subjected to transient changes in principal stress,accompanied by sudden changes in strain rate.Stress rotation induces spatially directional deformation,resulting in fractures of different degrees and orientations,and increasing the degree of deformation anisotropy.The correlation between the degree of induced fracture and the unloading magnitude of minimum principal stress,as well as its initial level is significant and positive.The process of mechanical response during transient unloading exhibits clear nonlinearity and directivity.After transient unloading,both the minimum principal stress and minimum principal strain rate decrease sharply and then tend to stabilize.This occurs from the edge to the interior and from the direction of the minimum principal stress to the direction of the maximum principal stress on theε1-ε3 plane.Transient unloading will induce a tensile stress wave.The ability to induce fractures due to changes in principal stress magnitude,orientation and rotation paths gradually increases.The analysis indicates a positive correlation between the abrupt change amplitude of strain rate and the maximum unloading magnitude,which is determined by the magnitude and rotation of principal stress.A high tensile strain rate is more likely to induce fractures under low minimum principal stress.展开更多
With the increase in mining depth,traditional coal mining methods not only waste coal resources but also seriously impact the stability of the roadway support structure during the collapse of the overburden rock.In co...With the increase in mining depth,traditional coal mining methods not only waste coal resources but also seriously impact the stability of the roadway support structure during the collapse of the overburden rock.In contrast,the top-cutting and depressurization technology utilizes the expansion effect of the rock effectively.This technology allows the rock body to collapse entirely,filling up the mining area through active intervention,which reduces the subsidence height of the overburden rock and significantly improves the coal extraction rate in the mining area.This study utilizes 3D seismic exploration technology to analyze the spatial distribution characteristics of fissure zones and rich zones of the rock strata in the mining area and investigate the movement law of overburdened rock during the coal seam mining process using the 110 mining method.It conducts numerical analysis combined with geomechanical modeling experiments to explore the movement law of the overburden rock under the influence of mining activities at Yuwang Coal Mine.The numerical analysis results indicate that the horizontal and vertical displacements of the rock body on the roof of the roadway are minimal when the angle of the slit is 75°.The overlying rock movement during the test is categorized by modeling the stress and strain fields into the following stages:fracture zone expansion,collapse zone gestation,rapid collapse zone development,and overlying rock stabilization.The rock on the cut side collapses more completely,breaking up and expanding to support the overburden,effectively reducing the depth of crack expansion and the extent of rock settlement and deformation.The integrity of the roadway roof remains intact during the rock collapse under NPR anchors.This study provides a scientific basis for understanding the movement law of overlying rock and for controlling the stability of the roadway perimeter rock in kilometer-deep underground mining.展开更多
In view of the limitations of traditional measurement methods in the field of building information,such as complex operation,low timeliness and poor accuracy,a new way of combining three-dimensional scanning technolog...In view of the limitations of traditional measurement methods in the field of building information,such as complex operation,low timeliness and poor accuracy,a new way of combining three-dimensional scanning technology and BIM(Building Information Modeling)model was discussed.Focused on the efficient acquisition of building geometric information using the fast-developing 3D point cloud technology,an improved deep learning-based 3D point cloud recognition method was proposed.The method optimised the network structure based on RandLA-Net to adapt to the large-scale point cloud processing requirements,while the semantic and instance features of the point cloud were integrated to significantly improve the recognition accuracy and provide a precise basis for BIM model remodeling.In addition,a visual BIM model generation system was developed,which systematically transformed the point cloud recognition results into BIM component parameters,automatically constructed BIM models,and promoted the open sharing and secondary development of models.The research results not only effectively promote the automation process of converting 3D point cloud data to refined BIM models,but also provide important technical support for promoting building informatisation and accelerating the construction of smart cities,showing a wide range of application potential and practical value.展开更多
Discontinuity waviness is one of the most important properties that influence shear strength of jointed rock masses,and it should be incorporated into numerical models for slope stability assessment.However,in most ex...Discontinuity waviness is one of the most important properties that influence shear strength of jointed rock masses,and it should be incorporated into numerical models for slope stability assessment.However,in most existing numerical modeling tools,discontinuities are often simplified into planar surfaces.Discrete fracture network modeling tools such as MoFrac allow the simulation of non-planar discontinuities which can be incorporated into lattice-spring-based geomechanical software such as Slope Model for slope stability assessment.In this study,the slope failure of the south wall at Cadia Hill open pit mine is simulated using the lattice-spring-based synthetic rock mass(LS-SRM)modeling approach.First,the slope model is calibrated using field displacement monitoring data,and then the influence of different discontinuity configurations on the stability of the slope is investigated.The modeling results show that the slope with non-planar discontinuities is comparatively more stable than the ones with planar discontinuities.In addition,the slope becomes increasingly unstable with the increases of discontinuity intensity and size.At greater pit depth with higher in situ stress,both the slope models with planar and non-planar discontinuities experience localized failures due to very high stress concentrations,and the slope model with planar discontinuities is more deformable and less stable than that with non-planar discontinuities.展开更多
The lithofacies classification is essential for oil and gas reservoir exploration and development.The traditional method of lithofacies classification is based on"core calibration logging"and the experience ...The lithofacies classification is essential for oil and gas reservoir exploration and development.The traditional method of lithofacies classification is based on"core calibration logging"and the experience of geologists.This approach has strong subjectivity,low efficiency,and high uncertainty.This uncertainty may be one of the key factors affecting the results of 3 D modeling of tight sandstone reservoirs.In recent years,deep learning,which is a cutting-edge artificial intelligence technology,has attracted attention from various fields.However,the study of deep-learning techniques in the field of lithofacies classification has not been sufficient.Therefore,this paper proposes a novel hybrid deep-learning model based on the efficient data feature-extraction ability of convolutional neural networks(CNN)and the excellent ability to describe time-dependent features of long short-term memory networks(LSTM)to conduct lithological facies-classification experiments.The results of a series of experiments show that the hybrid CNN-LSTM model had an average accuracy of 87.3%and the best classification effect compared to the CNN,LSTM or the three commonly used machine learning models(Support vector machine,random forest,and gradient boosting decision tree).In addition,the borderline synthetic minority oversampling technique(BSMOTE)is introduced to address the class-imbalance issue of raw data.The results show that processed data balance can significantly improve the accuracy of lithofacies classification.Beside that,based on the fine lithofacies constraints,the sequential indicator simulation method is used to establish a three-dimensional lithofacies model,which completes the fine description of the spatial distribution of tight sandstone reservoirs in the study area.According to this comprehensive analysis,the proposed CNN-LSTM model,which eliminates class imbalance,can be effectively applied to lithofacies classification,and is expected to improve the reality of the geological model for the tight sandstone reservoirs.展开更多
To determine the effect of dissolution on pore network development in carbonate rocks, dissolution experiments, X-Ray microtomography, and thin section analysis were conducted on argillaceous limestone and grain limes...To determine the effect of dissolution on pore network development in carbonate rocks, dissolution experiments, X-Ray microtomography, and thin section analysis were conducted on argillaceous limestone and grain limestone samples at different temperatures and constant pH, HCl concentration. The relationship between Ca^(2+) concentration and time was revealed through the experiments; pore size distribution before and after dissolution indicate that there is no correlation between the temperature and pore size variation, but pore size variation in grain limestone is more significant, indicating that the variation is mainly controlled by the heterogeneity of the rock itself(initial porosity and permeability) and the abundance of unstable minerals(related to crystal shape, size and mineral type). At different temperatures, the two kinds of carbonate rocks had very small variation in pore throat radius from 0.003 mm to 0.040 mm, which is 1.3 to 3.5 times more, 1.7 on average of the original pore throat radius. Their pore throat length varied from 0.05 mm to 0.35 mm. The minor changes in the pore throat radius, length and connectivity brought big changes to permeability of up to 1 000×10^(-3) μm^2.展开更多
In this paper,3D-GIS reconstruction and interpolation approach,additional virtual borehole technology and BP network technology are used to explore the concealed ore body.The virtual borehole has same function as real...In this paper,3D-GIS reconstruction and interpolation approach,additional virtual borehole technology and BP network technology are used to explore the concealed ore body.The virtual borehole has same function as reality borehole due to the multi-information check and validation in展开更多
Transparent physical models of real rocks fabricated using three-dimensional(3D)printing technology are used in photoelas-tic experiments to quantify the evolution of the internal stress and deformation fields of rock...Transparent physical models of real rocks fabricated using three-dimensional(3D)printing technology are used in photoelas-tic experiments to quantify the evolution of the internal stress and deformation fields of rocks.Therefore,they are rendered as an emerging powerful technique to quantitatively reveal the intrinsic mechanisms of rock failure.The mechanical behav-ior of natural rocks exhibits a significant size effect;however,limited research has been conducted on whether transparent physical models observe similar size effects.In this study,to make the transparent printed models accurately demonstrate the mechanical behavior of natural rocks and reveal the internal mechanism of the size effect in rock mechanical behavior,the size effect in 3D printed models of fractured and porous rocks under uniaxial compressive loading was investigated.Transparent cylindrical models with different sizes that contained different fractured and porous structures were printed using the fracture and porous characteristics extracted from natural coal and sandstone.The variation in uniaxial compres-sive strength and elastic modulus of fractured and porous models for increasing model sizes were obtained through uniaxial compression experiments.Finally,the influence of internal discontinuous structural features,such as fractures and pores,on the size effect pertaining to the mechanical behavior of the model was analyzed and elaborated by comparing it with the mechanical properties of the continuous homogeneous model without fractures and pores.The findings provided support and reference to analyze the size effect of rock mechanical behavior and the effect of the internal discontinuous structure using 3D printed transparent models.展开更多
Coal rock is a type of dual-porosity medium,which is composed of matrix pores and fracture-cutting matrix.They play different roles in the seepage and storage capacity of coal rock.Therefore,constructing the micropore...Coal rock is a type of dual-porosity medium,which is composed of matrix pores and fracture-cutting matrix.They play different roles in the seepage and storage capacity of coal rock.Therefore,constructing the micropore structure of coal rock is very important in the exploration and development of coalbed methane.In this study,we use a coal rock digital core and three-dimensional modeling to study the pore structure of coal rock.First,the micropore structure of coal rock is quantitatively analyzed using a two-dimensional thin-section image,and the quantitative information of the pore and fracture(cleat)structure in the coal rock is extracted.The mean value and standard deviation of the face porosity and pore radius are obtained using statistical analysis.The number of pores is determined using dichotomy and spherical random-packing methods based on compression.By combining with the results of the petrophysical analysis,the single-porosity structure model of the coal rock is obtained using a nonequal-diameter sphere to represent the pores of the coal rock.Then,an ellipsoid with an aspect ratio that is very much lesser than one is used to represent the fracture(cleat)in the coal rock,and a dual-pore structure model of the coal rock is obtained.On this basis,the relationship between the different pore aspect ratios and porosity is explored,and a fitting relationship is obtained.The results show that a nonlinear relationship exists between them.The relationship model can provide a basis for the prediction of coal rock pore structure and the pore structure parameters and provide a reference for understanding the internal structure of coalbed methane reservoirs.展开更多
Rock avalanches are generally difficult to prevent and control due to their high velocities and the extensive destruction they cause.However,barrier structures constructed along the path of a rock avalanche can partia...Rock avalanches are generally difficult to prevent and control due to their high velocities and the extensive destruction they cause.However,barrier structures constructed along the path of a rock avalanche can partially mitigate the magnitudes and consequences of such catastrophic events.We selected a rock avalanche in Nayong County,Guizhou Province,China as a case to study the effect of the location and height of a retaining wall on the dynamic characteristics of rock avalanche by using both actual terrain-based laboratory-model tests and coupled PFC3D-FLAC3D numerical simulations.Our findings demonstrate that a retaining wall can largely block a rock avalanche and its protective efficacy is significantly influenced by the integrity of the retaining wall.Coupled numerical simulation can serve as a powerful tool for analyzing the interaction between a rock avalanche and a retaining wall,facilitating precise observations of its deformation and destruction.The impact-curve characteristics of the retaining wall depend upon whether or not the rock avalanche-induced destruction is taken into account.The location of the retaining wall exerts a greater influence on the outcome compared to the height and materials of the retaining wall,while implementing a stepped retaining-wall pattern in accordance with the terrain demonstrates optimal efficacy in controlling rock avalanche.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2022YFC3080200)the National Natural Science Foundation of China(Grant No.42022053)the China Postdoctoral Science Foundation(Grant No.2023M731264).
文摘Natural slopes usually display complicated exposed rock surfaces that are characterized by complex and substantial terrain undulation and ubiquitous undesirable phenomena such as vegetation cover and rockfalls.This study presents a systematic outcrop research of fracture pattern variations in a complicated rock slope,and the qualitative and quantitative study of the complex phenomena impact on threedimensional(3D)discrete fracture network(DFN)modeling.As the studies of the outcrop fracture pattern have been so far focused on local variations,thus,we put forward a statistical analysis of global variations.The entire outcrop is partitioned into several subzones,and the subzone-scale variability of fracture geometric properties is analyzed(including the orientation,the density,and the trace length).The results reveal significant variations in fracture characteristics(such as the concentrative degree,the average orientation,the density,and the trace length)among different subzones.Moreover,the density of fracture sets,which is approximately parallel to the slope surface,exhibits a notably higher value compared to other fracture sets across all subzones.To improve the accuracy of the DFN modeling,the effects of three common phenomena resulting from vegetation and rockfalls are qualitatively analyzed and the corresponding quantitative data processing solutions are proposed.Subsequently,the 3D fracture geometric parameters are determined for different areas of the high-steep rock slope in terms of the subzone dimensions.The results show significant variations in the same set of 3D fracture parameters across different regions with density differing by up to tenfold and mean trace length exhibiting differences of 3e4 times.The study results present precise geological structural information,improve modeling accuracy,and provide practical solutions for addressing complex outcrop issues.
基金supported by the National Key R&D Program of China (No.2022YFC3004602)the National Natural Science Foundation of China (No.52325404)the Shenzhen Science and Technology Program (No.JCYJ20220818095605012).
文摘Rock discontinuities such as joints widely exist in natural rock masses,and wave attenuation through rock masses is mainly caused by discontinuities.The displacement discontinuity model(DDM)has been widely used in theoretical and numerical analysis of wave propagation across rock discontinuity.However,the circumstance under which the DDM is applicable to predict wave propagation across rock discontinuity remains poorly understood.In this study,theoretical analysis and ultrasonic laboratory tests were carried out to examine the theoretical applicability of the DDM for wave propagation,where specimens with rough joints comprising regular rectangular asperities of different spacings and heights were prepared by 3D printing technology.It is found that the theoretical applicability of the DDM to predict wave propagation across rock discontinuity is determined by three joint parameters,i.e.the dimensionless asperity spacing(L),the dimensionless asperity height(H)and the groove density(D).Through theoretical analysis and laboratory tests,the conditions under which the DDM is applicable are derived as follows:and,.With increase in the groove density,the thresholds of the dimensionless asperity spacing and the dimensionless asperity height show a decreasing trend.In addition,the transmission coefficient in the frequency domain decreases with increasing groove density,dimensionless asperity spacing or dimensionless asperity height.The findings can facilitate our understanding of DDM for predicting wave propagation across rock discontinuity.
基金supported by the National Natural Science Foundation of China(Grant No.52125903)the China Postdoctoral Science Foundation(Grant No.2023M730367)the Fundamental Research Funds for Central Public Welfare Research Institutes of China(Grant No.CKSF2023323/YT).
文摘To investigate the long-term stability of deep rocks,a three-dimensional(3D)time-dependent model that accounts for excavation-induced damage and complex stress state is developed.This model comprises three main components:a 3D viscoplastic isotropic constitutive relation that considers excavation damage and complex stress state,a quantitative relationship between critical irreversible deformation and complex stress state,and evolution characteristics of strength parameters.The proposed model is implemented in a self-developed numerical code,i.e.CASRock.The reliability of the model is validated through experiments.It is indicated that the time-dependent fracturing potential index(xTFPI)at a given time during the attenuation creep stage shows a negative correlation with the extent of excavationinduced damage.The time-dependent fracturing process of rock demonstrates a distinct interval effect of the intermediate principal stress,thereby highlighting the 3D stress-dependent characteristic of the model.Finally,the influence of excavation-induced damage and intermediate principal stress on the time-dependent fracturing characteristics of the surrounding rocks around the tunnel is discussed.
基金the National Natural Science Foundation of China(Nos.62272063,62072056 and 61902041)the Natural Science Foundation of Hunan Province(Nos.2022JJ30617 and 2020JJ2029)+4 种基金Open Research Fund of Key Lab of Broadband Wireless Communication and Sensor Network Technology,Nanjing University of Posts and Telecommunications(No.JZNY202102)the Traffic Science and Technology Project of Hunan Province,China(No.202042)Hunan Provincial Key Research and Development Program(No.2022GK2019)this work was funded by the Researchers Supporting Project Number(RSPD2023R681)King Saud University,Riyadh,Saudi Arabia.
文摘Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time complexity.Network modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is established.This paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety.
基金supported by the National Key R&D Program of China(No.2023YFC3081200)the National Natural Science Foundation of China(No.42077264)the Scientific Research Project of PowerChina Huadong Engineering Corporation Limited(HDEC-2022-0301).
文摘Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.
基金supported by grants from the Human Resources Development program (Grant No.20204010600250)the Training Program of CCUS for the Green Growth (Grant No.20214000000500)by the Korea Institute of Energy Technology Evaluation and Planning (KETEP)funded by the Ministry of Trade,Industry,and Energy of the Korean Government (MOTIE).
文摘It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimensional(3D)models are relatively straightforward but time-consuming.One potential solution to enhance this process is to use machine learning algorithms to detect the 3D traces.In this study,a unique pixel-wise texture mapper algorithm generates a dense point cloud representation of an outcrop with the precise resolution of the original textured 3D model.A virtual digital image rendering was then employed to capture virtual images of selected regions.This technique helps to overcome limitations caused by the surface morphology of the rock mass,such as restricted access,lighting conditions,and shading effects.After AI-powered trace detection on two-dimensional(2D)images,a 3D data structuring technique was applied to the selected trace pixels.In the 3D data structuring,the trace data were structured through 2D thinning,3D reprojection,clustering,segmentation,and segment linking.Finally,the linked segments were exported as 3D polylines,with each polyline in the output corresponding to a trace.The efficacy of the proposed method was assessed using a 3D model of a real-world case study,which was used to compare the results of artificial intelligence(AI)-aided and human intelligence trace detection.Rosette diagrams,which visualize the distribution of trace orientations,confirmed the high similarity between the automatically and manually generated trace maps.In conclusion,the proposed semi-automatic method was easy to use,fast,and accurate in detecting the dominant jointing system of the rock mass.
文摘Deep learning, especially through convolutional neural networks (CNN) such as the U-Net 3D model, has revolutionized fault identification from seismic data, representing a significant leap over traditional methods. Our review traces the evolution of CNN, emphasizing the adaptation and capabilities of the U-Net 3D model in automating seismic fault delineation with unprecedented accuracy. We find: 1) The transition from basic neural networks to sophisticated CNN has enabled remarkable advancements in image recognition, which are directly applicable to analyzing seismic data. The U-Net 3D model, with its innovative architecture, exemplifies this progress by providing a method for detailed and accurate fault detection with reduced manual interpretation bias. 2) The U-Net 3D model has demonstrated its superiority over traditional fault identification methods in several key areas: it has enhanced interpretation accuracy, increased operational efficiency, and reduced the subjectivity of manual methods. 3) Despite these achievements, challenges such as the need for effective data preprocessing, acquisition of high-quality annotated datasets, and achieving model generalization across different geological conditions remain. Future research should therefore focus on developing more complex network architectures and innovative training strategies to refine fault identification performance further. Our findings confirm the transformative potential of deep learning, particularly CNN like the U-Net 3D model, in geosciences, advocating for its broader integration to revolutionize geological exploration and seismic analysis.
基金funded by the U.S.National Institute for Occupational Safety and Health(NIOSH)under the Contract No.75D30119C06044。
文摘In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for acquiring discontinuity measurements from 3D models,such as point clouds generated using laser scanning or photogrammetry.However,even with numerous automated and semiautomated methods presented in the literature,there is not one single method that can automatically characterize discontinuities accurately in a minimum of time.In this paper,we critically review all the existing methods proposed in the literature for the extraction of discontinuity characteristics such as joint sets and orientations,persistence,joint spacing,roughness and block size using point clouds,digital elevation maps,or meshes.As a result of this review,we identify the strengths and drawbacks of each method used for extracting those characteristics.We found that the approaches based on voxels and region growing are superior in extracting joint planes from 3D point clouds.Normal tensor voting with trace growth algorithm is a robust method for measuring joint trace length from 3D meshes.Spacing is estimated by calculating the perpendicular distance between joint planes.Several independent roughness indices are presented to quantify roughness from 3D surface models,but there is a need to incorporate these indices into automated methodologies.There is a lack of efficient algorithms for direct computation of block size from 3D rock mass surface models.
基金the management of Sierra Rutile Company for providing the drillhole dataset used in this studythe Japanese Ministry of Education Science and Technology (MEXT) Scholarship for academic funding
文摘In this research, a method called ANNMG is presented to integrate Artificial Neural Networks and Geostatistics for optimum mineral reserve evaluation. The word ANNMG simply means Artificial Neural Network Model integrated with Geostatiscs, In this procedure, the Artificial Neural Network was trained, tested and validated using assay values obtained from exploratory drillholes. Next, the validated model was used to generalize mineral grades at known and unknown sampled locations inside the drilling region respectively. Finally, the reproduced and generalized assay values were combined and fed to geostatistics in order to develop a geological 3D block model. The regression analysis revealed that the predicted sample grades were in close proximity to the actual sample grades, The generalized grades from the ANNMG show that this process could be used to complement exploration activities thereby reducing drilling requirement. It could also be an effective mineral reserve evaluation method that could oroduce optimum block model for mine design.
文摘Fetr6 is an underground mine in which chromite is extracted using stope and pillar mining method. Despite of all improving works such as roof supporting and replacing of ore pillars with concrete pillars, pillar No. 19 failed and other pillars failed progressively as a domino effect and 4000 m2 of mine collapsed within a few minutes, consequently. For detail investigation, two 3-D numerical models were developed by 3Dec. The first, a base model, was used for estimation of stress on pillars just before failure and the other for investigation of rock burst in pillar No. 19. The results show that discontinuity parameters such as friction angle and shear stiffness is critical parameters in this pillar failure. In addition, it indicates that W/H ratio equal 0.3, the lack of ore extraction strategy and inadequate roof support are the major reasons for this failure. In this paper, the procedure of study was described.
基金the financial support from the National Natural Science Foundation of China(Grant No.51839003)Liaoning Revitalization Talents Program(Grant No.XLYCYSZX 1902)Hubei Key Laboratory for Efficient Utilization and Agglomeration of Metallurgic Mineral Resources(Grant No.2023zy002).
文摘To achieve the loading of the stress path of hard rock,the spherical discrete element model(DEM)and the new flexible membrane technology were utilized to realize the transient loading of three principal stresses with arbitrary magnitudes and orientations.Furthermore,based on the deep tunnel of China Jinping Underground Laboratory II(CJPL-II),the deformation and fracture evolution characteristics of deep hard rock induced by excavation stress path were analyzed,and the mechanisms of transient loading-unloading and stress rotation-induced fractures were revealed from a mesoscopic perspective.The results indicated that the stressestrain curve exhibits different trends and degrees of sudden changes when subjected to transient changes in principal stress,accompanied by sudden changes in strain rate.Stress rotation induces spatially directional deformation,resulting in fractures of different degrees and orientations,and increasing the degree of deformation anisotropy.The correlation between the degree of induced fracture and the unloading magnitude of minimum principal stress,as well as its initial level is significant and positive.The process of mechanical response during transient unloading exhibits clear nonlinearity and directivity.After transient unloading,both the minimum principal stress and minimum principal strain rate decrease sharply and then tend to stabilize.This occurs from the edge to the interior and from the direction of the minimum principal stress to the direction of the maximum principal stress on theε1-ε3 plane.Transient unloading will induce a tensile stress wave.The ability to induce fractures due to changes in principal stress magnitude,orientation and rotation paths gradually increases.The analysis indicates a positive correlation between the abrupt change amplitude of strain rate and the maximum unloading magnitude,which is determined by the magnitude and rotation of principal stress.A high tensile strain rate is more likely to induce fractures under low minimum principal stress.
基金financially supported by the State Key Laboratory for Geomechanics and Deep Underground Engineering (SKLGDUEK2020)Huaneng Group headquarters science and technology project (HNKJ21-H07)the Coal Burst Research Center of China Jiangsu.
文摘With the increase in mining depth,traditional coal mining methods not only waste coal resources but also seriously impact the stability of the roadway support structure during the collapse of the overburden rock.In contrast,the top-cutting and depressurization technology utilizes the expansion effect of the rock effectively.This technology allows the rock body to collapse entirely,filling up the mining area through active intervention,which reduces the subsidence height of the overburden rock and significantly improves the coal extraction rate in the mining area.This study utilizes 3D seismic exploration technology to analyze the spatial distribution characteristics of fissure zones and rich zones of the rock strata in the mining area and investigate the movement law of overburdened rock during the coal seam mining process using the 110 mining method.It conducts numerical analysis combined with geomechanical modeling experiments to explore the movement law of the overburden rock under the influence of mining activities at Yuwang Coal Mine.The numerical analysis results indicate that the horizontal and vertical displacements of the rock body on the roof of the roadway are minimal when the angle of the slit is 75°.The overlying rock movement during the test is categorized by modeling the stress and strain fields into the following stages:fracture zone expansion,collapse zone gestation,rapid collapse zone development,and overlying rock stabilization.The rock on the cut side collapses more completely,breaking up and expanding to support the overburden,effectively reducing the depth of crack expansion and the extent of rock settlement and deformation.The integrity of the roadway roof remains intact during the rock collapse under NPR anchors.This study provides a scientific basis for understanding the movement law of overlying rock and for controlling the stability of the roadway perimeter rock in kilometer-deep underground mining.
文摘In view of the limitations of traditional measurement methods in the field of building information,such as complex operation,low timeliness and poor accuracy,a new way of combining three-dimensional scanning technology and BIM(Building Information Modeling)model was discussed.Focused on the efficient acquisition of building geometric information using the fast-developing 3D point cloud technology,an improved deep learning-based 3D point cloud recognition method was proposed.The method optimised the network structure based on RandLA-Net to adapt to the large-scale point cloud processing requirements,while the semantic and instance features of the point cloud were integrated to significantly improve the recognition accuracy and provide a precise basis for BIM model remodeling.In addition,a visual BIM model generation system was developed,which systematically transformed the point cloud recognition results into BIM component parameters,automatically constructed BIM models,and promoted the open sharing and secondary development of models.The research results not only effectively promote the automation process of converting 3D point cloud data to refined BIM models,but also provide important technical support for promoting building informatisation and accelerating the construction of smart cities,showing a wide range of application potential and practical value.
基金Ontario Trillium Scholarship for supporting the doctorate program at Laurentian UniversityFinancial supports from the Natural Sciences and Engineering Research Council of Canada(NSERC CRD 470490-14)of Canada+1 种基金Nuclear Waste Management Organization(NWMO)Rio Tinto。
文摘Discontinuity waviness is one of the most important properties that influence shear strength of jointed rock masses,and it should be incorporated into numerical models for slope stability assessment.However,in most existing numerical modeling tools,discontinuities are often simplified into planar surfaces.Discrete fracture network modeling tools such as MoFrac allow the simulation of non-planar discontinuities which can be incorporated into lattice-spring-based geomechanical software such as Slope Model for slope stability assessment.In this study,the slope failure of the south wall at Cadia Hill open pit mine is simulated using the lattice-spring-based synthetic rock mass(LS-SRM)modeling approach.First,the slope model is calibrated using field displacement monitoring data,and then the influence of different discontinuity configurations on the stability of the slope is investigated.The modeling results show that the slope with non-planar discontinuities is comparatively more stable than the ones with planar discontinuities.In addition,the slope becomes increasingly unstable with the increases of discontinuity intensity and size.At greater pit depth with higher in situ stress,both the slope models with planar and non-planar discontinuities experience localized failures due to very high stress concentrations,and the slope model with planar discontinuities is more deformable and less stable than that with non-planar discontinuities.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.300102278402)。
文摘The lithofacies classification is essential for oil and gas reservoir exploration and development.The traditional method of lithofacies classification is based on"core calibration logging"and the experience of geologists.This approach has strong subjectivity,low efficiency,and high uncertainty.This uncertainty may be one of the key factors affecting the results of 3 D modeling of tight sandstone reservoirs.In recent years,deep learning,which is a cutting-edge artificial intelligence technology,has attracted attention from various fields.However,the study of deep-learning techniques in the field of lithofacies classification has not been sufficient.Therefore,this paper proposes a novel hybrid deep-learning model based on the efficient data feature-extraction ability of convolutional neural networks(CNN)and the excellent ability to describe time-dependent features of long short-term memory networks(LSTM)to conduct lithological facies-classification experiments.The results of a series of experiments show that the hybrid CNN-LSTM model had an average accuracy of 87.3%and the best classification effect compared to the CNN,LSTM or the three commonly used machine learning models(Support vector machine,random forest,and gradient boosting decision tree).In addition,the borderline synthetic minority oversampling technique(BSMOTE)is introduced to address the class-imbalance issue of raw data.The results show that processed data balance can significantly improve the accuracy of lithofacies classification.Beside that,based on the fine lithofacies constraints,the sequential indicator simulation method is used to establish a three-dimensional lithofacies model,which completes the fine description of the spatial distribution of tight sandstone reservoirs in the study area.According to this comprehensive analysis,the proposed CNN-LSTM model,which eliminates class imbalance,can be effectively applied to lithofacies classification,and is expected to improve the reality of the geological model for the tight sandstone reservoirs.
基金sponsored by PETRONAS and YUTP (Yayasan Universiti Teknologi PETRONAS)
文摘To determine the effect of dissolution on pore network development in carbonate rocks, dissolution experiments, X-Ray microtomography, and thin section analysis were conducted on argillaceous limestone and grain limestone samples at different temperatures and constant pH, HCl concentration. The relationship between Ca^(2+) concentration and time was revealed through the experiments; pore size distribution before and after dissolution indicate that there is no correlation between the temperature and pore size variation, but pore size variation in grain limestone is more significant, indicating that the variation is mainly controlled by the heterogeneity of the rock itself(initial porosity and permeability) and the abundance of unstable minerals(related to crystal shape, size and mineral type). At different temperatures, the two kinds of carbonate rocks had very small variation in pore throat radius from 0.003 mm to 0.040 mm, which is 1.3 to 3.5 times more, 1.7 on average of the original pore throat radius. Their pore throat length varied from 0.05 mm to 0.35 mm. The minor changes in the pore throat radius, length and connectivity brought big changes to permeability of up to 1 000×10^(-3) μm^2.
文摘In this paper,3D-GIS reconstruction and interpolation approach,additional virtual borehole technology and BP network technology are used to explore the concealed ore body.The virtual borehole has same function as reality borehole due to the multi-information check and validation in
基金the National Natural Science Foundation of China(51727807,52121003)Innovation Teams of Ten-Thousand Talents Program sponsored by the Ministry of Science and Technology of China(2016RA4067).
文摘Transparent physical models of real rocks fabricated using three-dimensional(3D)printing technology are used in photoelas-tic experiments to quantify the evolution of the internal stress and deformation fields of rocks.Therefore,they are rendered as an emerging powerful technique to quantitatively reveal the intrinsic mechanisms of rock failure.The mechanical behav-ior of natural rocks exhibits a significant size effect;however,limited research has been conducted on whether transparent physical models observe similar size effects.In this study,to make the transparent printed models accurately demonstrate the mechanical behavior of natural rocks and reveal the internal mechanism of the size effect in rock mechanical behavior,the size effect in 3D printed models of fractured and porous rocks under uniaxial compressive loading was investigated.Transparent cylindrical models with different sizes that contained different fractured and porous structures were printed using the fracture and porous characteristics extracted from natural coal and sandstone.The variation in uniaxial compres-sive strength and elastic modulus of fractured and porous models for increasing model sizes were obtained through uniaxial compression experiments.Finally,the influence of internal discontinuous structural features,such as fractures and pores,on the size effect pertaining to the mechanical behavior of the model was analyzed and elaborated by comparing it with the mechanical properties of the continuous homogeneous model without fractures and pores.The findings provided support and reference to analyze the size effect of rock mechanical behavior and the effect of the internal discontinuous structure using 3D printed transparent models.
基金sponsored by the National Natural Science Foundation of China(No.41274129)National Science and Technology Major Project(No.2016ZX05026001-004)+2 种基金Key Research and Development Program of Sichuan Province(No.2020YFG0157)the 2018 Central Supporting Local Coconstruction Fund(No.80000-18Z0140504)the Construction and Development of Universities in 2019-Joint Support for Geophysics(Double First-Class center,80000-19Z0204).
文摘Coal rock is a type of dual-porosity medium,which is composed of matrix pores and fracture-cutting matrix.They play different roles in the seepage and storage capacity of coal rock.Therefore,constructing the micropore structure of coal rock is very important in the exploration and development of coalbed methane.In this study,we use a coal rock digital core and three-dimensional modeling to study the pore structure of coal rock.First,the micropore structure of coal rock is quantitatively analyzed using a two-dimensional thin-section image,and the quantitative information of the pore and fracture(cleat)structure in the coal rock is extracted.The mean value and standard deviation of the face porosity and pore radius are obtained using statistical analysis.The number of pores is determined using dichotomy and spherical random-packing methods based on compression.By combining with the results of the petrophysical analysis,the single-porosity structure model of the coal rock is obtained using a nonequal-diameter sphere to represent the pores of the coal rock.Then,an ellipsoid with an aspect ratio that is very much lesser than one is used to represent the fracture(cleat)in the coal rock,and a dual-pore structure model of the coal rock is obtained.On this basis,the relationship between the different pore aspect ratios and porosity is explored,and a fitting relationship is obtained.The results show that a nonlinear relationship exists between them.The relationship model can provide a basis for the prediction of coal rock pore structure and the pore structure parameters and provide a reference for understanding the internal structure of coalbed methane reservoirs.
基金Hunan Provincial key Laboratory of key Technology on Hydropower Development Open Research Fund (PKLHD202203)
文摘Rock avalanches are generally difficult to prevent and control due to their high velocities and the extensive destruction they cause.However,barrier structures constructed along the path of a rock avalanche can partially mitigate the magnitudes and consequences of such catastrophic events.We selected a rock avalanche in Nayong County,Guizhou Province,China as a case to study the effect of the location and height of a retaining wall on the dynamic characteristics of rock avalanche by using both actual terrain-based laboratory-model tests and coupled PFC3D-FLAC3D numerical simulations.Our findings demonstrate that a retaining wall can largely block a rock avalanche and its protective efficacy is significantly influenced by the integrity of the retaining wall.Coupled numerical simulation can serve as a powerful tool for analyzing the interaction between a rock avalanche and a retaining wall,facilitating precise observations of its deformation and destruction.The impact-curve characteristics of the retaining wall depend upon whether or not the rock avalanche-induced destruction is taken into account.The location of the retaining wall exerts a greater influence on the outcome compared to the height and materials of the retaining wall,while implementing a stepped retaining-wall pattern in accordance with the terrain demonstrates optimal efficacy in controlling rock avalanche.
