Rockbursts were frequently encountered in the construction of deeply buried tunnels at the Jinping-II hydropower station, Southwest China. In those cases, the existence of large structural planes, such as faults, was ...Rockbursts were frequently encountered in the construction of deeply buried tunnels at the Jinping-II hydropower station, Southwest China. In those cases, the existence of large structural planes, such as faults, was usually observed near the excavation boundaries. The formation mechanism of the “11·28” rockburst, which was a typical rockburst and occurred in a drainage tunnel under a deep burial depth, high in-situ stress state and complex geological conditions, has been difficult to explain. Realistic failure process analysis(RFPA3D) software was adopted to numerically simulate the whole failure process of the surrounding rock mass around the tunnel subjected to excavation. The spatial distribution of acoustic emission derived from numerical simulation contributed to explaining the mechanical responses of the process. Analyses of the stress, safety reserve coefficient and damage degree were performed to reveal the effect of faults on the formation of rockbursts in the deep tunnel. The existence of faults results in the formation of stress anomaly areas between the tunnel and the fault. The surrounding rock mass failure propagates toward the fault from the initial failure, to different degrees. The relative positions and angles of faults play significant roles in the extent and development of surrounding rock mass failure, respectively. The increase in the lateral stress coefficient leads to the aggravation of the surrounding rock mass damage, especially in the roof and floor of the tunnel. Moreover, as the rock strength-stress ratio increases, the failure mode of the near-fault tunnel gradually changes from the stress-controlled type to the compound-controlled type. These findings were consistent with the microseismic monitoring results and field observations, which was helpful to understand the mechanical behavior of tunnel excavation affected by faults. The achievements of this study can provide some references for analysis of the failure mechanisms of similar deep tunnels.展开更多
Microseismic monitoring system is one of the effective methods for deep mining geo-stress monitoring.The principle of microseismic monitoring system is to analyze the mechanical parameters contained in microseismic ev...Microseismic monitoring system is one of the effective methods for deep mining geo-stress monitoring.The principle of microseismic monitoring system is to analyze the mechanical parameters contained in microseismic events for providing accurate information of rockmass.The accurate identification of microseismic events and blasts determines the timeliness and accuracy of early warning of microseismic monitoring technology.An image identification model based on Convolutional Neural Network(CNN)is established in this paper for the seismic waveforms of microseismic events and blasts.Firstly,the training set,test set,and validation set are collected,which are composed of 5250,1500,and 750 seismic waveforms of microseismic events and blasts,respectively.The classified data sets are preprocessed and input into the constructed CNN in CPU mode for training.Results show that the accuracies of microseismic events and blasts are 99.46%and 99.33%in the test set,respectively.The accuracies of microseismic events and blasts are 100%and 98.13%in the validation set,respectively.The proposed method gives superior performance when compared with existed methods.The accuracies of models using logistic regression and artificial neural network(ANN)based on the same data set are 54.43%and 67.9%in the test set,respectively.Then,the ROC curves of the three models are obtained and compared,which show that the CNN gives an absolute advantage in this classification model when the original seismic waveform are used in training the model.It not only decreases the influence of individual differences in experience,but also removes the errors induced by source and waveform parameters.It is proved that the established discriminant method improves the efficiency and accuracy of microseismic data processing for monitoring rock instability and seismicity.展开更多
Rock mass large deformation in underground powerhouse caverns has been a severe hazard in hydropower engineering in Southwest China.During the development of rock mass large deformation,a sequence of fractures was gen...Rock mass large deformation in underground powerhouse caverns has been a severe hazard in hydropower engineering in Southwest China.During the development of rock mass large deformation,a sequence of fractures was generated that can be monitored using microseismic(MS)monitoring techniques.Two MS monitoring systems were established in two typical underground powerhouse caverns featuring distinct geostress levels.The MS b-values associated with rock mass large deformation and their temporal variation are analysed.The results showed that the MS bvalue in course of rock mass deformation was less than 1.0 in the underground powerhouse caverns at a high stress level while larger than 1.5 at a low stress level.Prior to the rock mass deformation,the MS b-values derived from both the high-stress and low-stress underground powerhouse caverns show an incremental decrease over 10%within 10 d.The results contribute to understanding the fracturing characteristics of MS sources associated with rock mass large deformation and provide a reference for early warning of rock mass large deformation in underground powerhouse caverns.展开更多
Rock burst is one of the most catastrophic dynamic hazards in coal mining. A static and dynamic stresses superposition-based(SDSS-based) risk evaluation method of rock burst was proposed to pre-evaluate rock burst ris...Rock burst is one of the most catastrophic dynamic hazards in coal mining. A static and dynamic stresses superposition-based(SDSS-based) risk evaluation method of rock burst was proposed to pre-evaluate rock burst risk. Theoretical basis of this method is the stress criterion incurring rock burst and rock burst risk is evaluated according to the closeness degree of the total stress(due to the superposition of static stress in the coal and dynamic stress induced by tremors) with the critical stress. In addition, risk evaluation criterion of rock burst was established by defining the "Satisfaction Degree" of static stress. Furthermore,the method was used to pre-evaluate rock burst risk degree and prejudge endangered area of an insular longwall face in Nanshan Coal Mine in China. Results show that rock burst risk is moderate at advance extent of 97 m, strong at advance extent of 97-131 m,and extremely strong(i.e. inevitable to occur) when advance extent exceeds 131 m(mining is prohibited in this case). The section of two gateways whose floor abuts 15-3 coal seam is a susceptible area prone to rock burst. Evaluation results were further compared with rock bursts and tremors detected by microseismic monitoring. Comparison results indicate that evaluation results are consistent with microseismic monitoring, which proves the method's feasibility.展开更多
To investigate the stability of rock mass in high geostress underground powerhouse caverns subjected to excavation,a microseismic(MS)monitoring system was established and the discrete element method(DEM)-based numeric...To investigate the stability of rock mass in high geostress underground powerhouse caverns subjected to excavation,a microseismic(MS)monitoring system was established and the discrete element method(DEM)-based numerical simulation was carried out.The tempo-spatial damage characteristics of rock mass were analyzed.The evolution laws of MS source parameters during the formation of a rock collapse controlled by high geostress and geological structure were investigated.Additionally,a three-dimensional DEM model of the underground powerhouse caverns was built to reveal the deformation characteristics of rock mass.The results indicated that the MS events induced by excavation of high geostress underground powerhouse caverns occurred frequently.The large-stake crown of the main powerhouse was the main damage area.Prior to the rock collapse,the MS event count and accumulated energy release increased rapidly,while the apparent stress sharply increased and then decreased.The amount and proportion of shear and mixed MS events remarkably increased.The maximum displacement was generally located near the spandrel areas.The MS monitoring data and numerical simulation were in good agreement,which can provide significant references for damage evaluation and disaster forecasting in high geostress underground powerhouse caverns.展开更多
The stability of the surrounding rock mass around cross tunnel in the right bank slope of Dagangshan hydropower station, in the southwestern China, was analyzed by microseismic monitoring as well as numerical simulati...The stability of the surrounding rock mass around cross tunnel in the right bank slope of Dagangshan hydropower station, in the southwestern China, was analyzed by microseismic monitoring as well as numerical simulations. The realistic failure process analysis code （abbreviated as RFPA3D） was employed to reproduce the initiation, propagation, coalescence and interactions of micro-fractures, the evolution of associated stress fields and acoustic emission （AE） activities during the whole failure processes of the surrounding rock mass around cross tunnel. Combined with microseismic activities by microseismic monitoring on the fight bank slope, the spatial-temporal evolution and the micro-fracture precursor characteristics during the complete process of progressive failure of the surrounding rock mass around cross tunnel were discussed and the energy release law of the surrounding rock mass around the cross tunnel was obtained. The result shows that the precursor characteristic of microfractures occurring in rock mass is an effective approach to early warn catastrophic damage of rock mass around cross tunnel. Moreover, the heterogeneity of rock mass is the source and internal cause of the failure precursor of rock mass.展开更多
基金Project(42177143) supported by the National Natural Science Foundation of ChinaProject(2020JDJQ0011) supported by the Science Foundation for Distinguished Young Scholars of Sichuan Province,China。
文摘Rockbursts were frequently encountered in the construction of deeply buried tunnels at the Jinping-II hydropower station, Southwest China. In those cases, the existence of large structural planes, such as faults, was usually observed near the excavation boundaries. The formation mechanism of the “11·28” rockburst, which was a typical rockburst and occurred in a drainage tunnel under a deep burial depth, high in-situ stress state and complex geological conditions, has been difficult to explain. Realistic failure process analysis(RFPA3D) software was adopted to numerically simulate the whole failure process of the surrounding rock mass around the tunnel subjected to excavation. The spatial distribution of acoustic emission derived from numerical simulation contributed to explaining the mechanical responses of the process. Analyses of the stress, safety reserve coefficient and damage degree were performed to reveal the effect of faults on the formation of rockbursts in the deep tunnel. The existence of faults results in the formation of stress anomaly areas between the tunnel and the fault. The surrounding rock mass failure propagates toward the fault from the initial failure, to different degrees. The relative positions and angles of faults play significant roles in the extent and development of surrounding rock mass failure, respectively. The increase in the lateral stress coefficient leads to the aggravation of the surrounding rock mass damage, especially in the roof and floor of the tunnel. Moreover, as the rock strength-stress ratio increases, the failure mode of the near-fault tunnel gradually changes from the stress-controlled type to the compound-controlled type. These findings were consistent with the microseismic monitoring results and field observations, which was helpful to understand the mechanical behavior of tunnel excavation affected by faults. The achievements of this study can provide some references for analysis of the failure mechanisms of similar deep tunnels.
基金Projects(51822407,51774327,51664016)supported by the National Natural Science Foundation of China。
文摘Microseismic monitoring system is one of the effective methods for deep mining geo-stress monitoring.The principle of microseismic monitoring system is to analyze the mechanical parameters contained in microseismic events for providing accurate information of rockmass.The accurate identification of microseismic events and blasts determines the timeliness and accuracy of early warning of microseismic monitoring technology.An image identification model based on Convolutional Neural Network(CNN)is established in this paper for the seismic waveforms of microseismic events and blasts.Firstly,the training set,test set,and validation set are collected,which are composed of 5250,1500,and 750 seismic waveforms of microseismic events and blasts,respectively.The classified data sets are preprocessed and input into the constructed CNN in CPU mode for training.Results show that the accuracies of microseismic events and blasts are 99.46%and 99.33%in the test set,respectively.The accuracies of microseismic events and blasts are 100%and 98.13%in the validation set,respectively.The proposed method gives superior performance when compared with existed methods.The accuracies of models using logistic regression and artificial neural network(ANN)based on the same data set are 54.43%and 67.9%in the test set,respectively.Then,the ROC curves of the three models are obtained and compared,which show that the CNN gives an absolute advantage in this classification model when the original seismic waveform are used in training the model.It not only decreases the influence of individual differences in experience,but also removes the errors induced by source and waveform parameters.It is proved that the established discriminant method improves the efficiency and accuracy of microseismic data processing for monitoring rock instability and seismicity.
基金Projects(51809221,51679158)supported by the National Natural Science Foundation of ChinaProject(KFJJ20-06M)supported by the State Key Laboratory of Explosion Science and Technology(Beijing Institute of Technology),China。
文摘Rock mass large deformation in underground powerhouse caverns has been a severe hazard in hydropower engineering in Southwest China.During the development of rock mass large deformation,a sequence of fractures was generated that can be monitored using microseismic(MS)monitoring techniques.Two MS monitoring systems were established in two typical underground powerhouse caverns featuring distinct geostress levels.The MS b-values associated with rock mass large deformation and their temporal variation are analysed.The results showed that the MS bvalue in course of rock mass deformation was less than 1.0 in the underground powerhouse caverns at a high stress level while larger than 1.5 at a low stress level.Prior to the rock mass deformation,the MS b-values derived from both the high-stress and low-stress underground powerhouse caverns show an incremental decrease over 10%within 10 d.The results contribute to understanding the fracturing characteristics of MS sources associated with rock mass large deformation and provide a reference for early warning of rock mass large deformation in underground powerhouse caverns.
基金Project(51174285)supported by the National Natural Science Foundation of China and the Shenhua Group Corporation Limited,ChinaProject(CXZZ12_0949)supported by the Research and Innovation Project for College Graduates of Jiangsu Province,ChinaProject(SZBF2011-6-B35)supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions,China
文摘Rock burst is one of the most catastrophic dynamic hazards in coal mining. A static and dynamic stresses superposition-based(SDSS-based) risk evaluation method of rock burst was proposed to pre-evaluate rock burst risk. Theoretical basis of this method is the stress criterion incurring rock burst and rock burst risk is evaluated according to the closeness degree of the total stress(due to the superposition of static stress in the coal and dynamic stress induced by tremors) with the critical stress. In addition, risk evaluation criterion of rock burst was established by defining the "Satisfaction Degree" of static stress. Furthermore,the method was used to pre-evaluate rock burst risk degree and prejudge endangered area of an insular longwall face in Nanshan Coal Mine in China. Results show that rock burst risk is moderate at advance extent of 97 m, strong at advance extent of 97-131 m,and extremely strong(i.e. inevitable to occur) when advance extent exceeds 131 m(mining is prohibited in this case). The section of two gateways whose floor abuts 15-3 coal seam is a susceptible area prone to rock burst. Evaluation results were further compared with rock bursts and tremors detected by microseismic monitoring. Comparison results indicate that evaluation results are consistent with microseismic monitoring, which proves the method's feasibility.
基金Project(2017YFC1501100)supported by the National Key R&D Program of ChinaProjects(51809221,51679158)supported by the National Natural Science Foundation of China。
文摘To investigate the stability of rock mass in high geostress underground powerhouse caverns subjected to excavation,a microseismic(MS)monitoring system was established and the discrete element method(DEM)-based numerical simulation was carried out.The tempo-spatial damage characteristics of rock mass were analyzed.The evolution laws of MS source parameters during the formation of a rock collapse controlled by high geostress and geological structure were investigated.Additionally,a three-dimensional DEM model of the underground powerhouse caverns was built to reveal the deformation characteristics of rock mass.The results indicated that the MS events induced by excavation of high geostress underground powerhouse caverns occurred frequently.The large-stake crown of the main powerhouse was the main damage area.Prior to the rock collapse,the MS event count and accumulated energy release increased rapidly,while the apparent stress sharply increased and then decreased.The amount and proportion of shear and mixed MS events remarkably increased.The maximum displacement was generally located near the spandrel areas.The MS monitoring data and numerical simulation were in good agreement,which can provide significant references for damage evaluation and disaster forecasting in high geostress underground powerhouse caverns.
基金Projects(50820125405, 51004020, 51174039, 4112265) supported by the National Natural Science Foundation of ChinaProject(201104563) supported by the China Postdoctoral Science Foundation+3 种基金Project(2011CB013503) supported by the National Basic Research Program of ChinaProject(51274053) supported by the Fundamental Research Funds for the Central Universities of ChinaProject(200960) supported by the Foundation for the Author of National Excellent Doctoral Dissertation of ChinaProject(NECT-09-0258) supported by the New Century Excellent Talents in University of China
文摘The stability of the surrounding rock mass around cross tunnel in the right bank slope of Dagangshan hydropower station, in the southwestern China, was analyzed by microseismic monitoring as well as numerical simulations. The realistic failure process analysis code （abbreviated as RFPA3D） was employed to reproduce the initiation, propagation, coalescence and interactions of micro-fractures, the evolution of associated stress fields and acoustic emission （AE） activities during the whole failure processes of the surrounding rock mass around cross tunnel. Combined with microseismic activities by microseismic monitoring on the fight bank slope, the spatial-temporal evolution and the micro-fracture precursor characteristics during the complete process of progressive failure of the surrounding rock mass around cross tunnel were discussed and the energy release law of the surrounding rock mass around the cross tunnel was obtained. The result shows that the precursor characteristic of microfractures occurring in rock mass is an effective approach to early warn catastrophic damage of rock mass around cross tunnel. Moreover, the heterogeneity of rock mass is the source and internal cause of the failure precursor of rock mass.
