Rockburst disasters occur frequently during deep underground excavation,yet traditional concepts and methods can hardly meet the requirements for support under high geo-stress conditions.Consequently,rockburst control...Rockburst disasters occur frequently during deep underground excavation,yet traditional concepts and methods can hardly meet the requirements for support under high geo-stress conditions.Consequently,rockburst control remains challenging in the engineering field.In this study,the mechanism of excavation-induced rockburst was briefly described,and it was proposed to apply the excavation compensation method(ECM)to rockburst control.Moreover,a field test was carried out on the Qinling Water Conveyance Tunnel.The following beneficial findings were obtained:Excavation leads to changes in the engineering stress state of surrounding rock and results in the generation of excess energy DE,which is the fundamental cause of rockburst.The ECM,which aims to offset the deep excavation effect and lower the risk of rockburst,is an active support strategy based on high pre-stress compensation.The new negative Poisson’s ratio(NPR)bolt developed has the mechanical characteristics of high strength,high toughness,and impact resistance,serving as the material basis for the ECM.The field test results reveal that the ECM and the NPR bolt succeed in controlling rockburst disasters effectively.The research results are expected to provide guidance for rockburst support in deep underground projects such as Sichuan-Xizang Railway.展开更多
Rockburst are often encountered in tunnel construction due to the complex geological conditions.To study the influence of unloading rate on rockburst,gneiss rockburst experiments were conducted under three groups of u...Rockburst are often encountered in tunnel construction due to the complex geological conditions.To study the influence of unloading rate on rockburst,gneiss rockburst experiments were conducted under three groups of unloading rates.A high-speed photography system and acoustic emission(AE)system were used to monitor the entire process of rockburst process in real-time.The results show that the intensity of gneiss rockburst decreases with decrease of unloading rate,which is manifested as the reduction of AE energy and fragments ejection velocity.The mechanisms are proposed to explain this effect:(i)The reduction of unloading rate changes the crack propagation mechanism in the process of rockburst.This makes the rockbursts change from the tensile failure mechanism at high unloading rate to the tension-shear mixed failure mechanism at low unloading rate,and more energy released in the form of shear crack propagation.Then,less strain energy is converted into kinetic energy of fragments ejection.(ii)Less plate cracking degree of gneiss has taken shape due to decrease of unloading rate,resulting in the destruction of rockburst incubation process.The enlightenments of reducing the unloading rate for the project are also described quantitatively.The rockburst magnitude is reduced from the medium magnitude at the unloading rate of 0.1 MPa/s to the slight magnitude at the unloading rate of 0.025 MPa/s,which was judged by the ejection velocity.展开更多
To investigate the mechanism of rockburst prevention by spraying water onto the surrounding rocks,15 experiments are performed considering different water absorption levels on a single face.High-speed photography and ...To investigate the mechanism of rockburst prevention by spraying water onto the surrounding rocks,15 experiments are performed considering different water absorption levels on a single face.High-speed photography and acoustic emission(AE)system are used to monitor the rockburst process.The effect of water on sandstone rockburst and the prevention mechanism of water on sandstone rockburst are analyzed from the perspective of energy and failure mode.The results show that the higher the ab-sorption degree,the lower the intensity of the rockburst after absorbing water on single side of sand-stone.This is reflected in the fact that with the increase in the water absorption level,the ejection velocity of rockburst fragments is smaller,the depth of the rockburst pit is shallower,and the AE energy is smaller.Under the water absorption level of 100%,the magnitude of rockburst intensity changes from medium to slight.The prevention mechanism of water on sandstone rockburst is that water reduces the capacity of sandstone to store strain energy and accelerates the expansion of shear cracks,which is not conducive to the occurrence of plate cracking before rockburst,and destroys the conditions for rockburst incubation.展开更多
A new rockburst classification, innovative works in developing a ‘‘strainburst test machine" and an‘‘impact-induced rockburst test machine" that can reproduce rockbursts in laboratory were researched.New...A new rockburst classification, innovative works in developing a ‘‘strainburst test machine" and an‘‘impact-induced rockburst test machine" that can reproduce rockbursts in laboratory were researched.New concepts were proposed regarding the stress paths that take into account both the static and dynamic stresses analogous to that at excavation boundaries for generating artificially-induced strainburst and impact-induced rockburst. As an important method for rockburst control, a novel energyabsorbing bolt was developed, which has a constant-resistance under both static and impact loadings and a large-elongation capacity for containing large deformations of rock masses under burst-prone conditions.展开更多
Rocks in underground works usually experience rather complex stress disturbance.For this,their fracture mechanism is significantly different from rocks subjected to conventional triaxial compression conditions.The eff...Rocks in underground works usually experience rather complex stress disturbance.For this,their fracture mechanism is significantly different from rocks subjected to conventional triaxial compression conditions.The effects of stress disturbances on rock geomechanical behaviors under fatigue loading conditions and triaxial unloading conditions have been reported in previous studies.However,little is known about the dependence of the unloading rate on fatigue loading and confining stress unloading(FL-CSU)conditions that influence rock failure.In this paper,we aimed at investigating the fracture behaviors of marble under FL-CSU conditions using the post-test X-ray computed tomography(CT)scanning technique and the GCTS RTR 2000 rock mechanics system.Results show that damage accumulation at the fatigue stage can influence the final fracture behaviors of marble.The stored elastic energy for rock samples under FL-CSU tests is relatively larger compared to those under conventional triaxial tests,and the dissipated energy used to drive damage evolution and crack propagation is larger for FL-CSU tests.In FL-CSU tests,as the unloading rate increases,the dissipated energy grows and elastic energy reduces.CT scanning after the test reveals the impacts of the unloading rate on the crack pattern and a fracture degree index is therein defined in this context to represent the crack dimension.It shows that the crack pattern after FL-CSU tests depends on the unloading rate,and the fracture degree is in agreement with the analysis of both the energy dissipation and the amount of energy released.The effect of unloading rate on fracture evolution characteristics of marble is revealed by a series of FL-CSU tests.展开更多
Impact rockburst test on sandstone samples with a central hole is carried out under true triaxial static loads and vertical dynamic load conditions, and rock fragments after the test are collected. The fragments of sa...Impact rockburst test on sandstone samples with a central hole is carried out under true triaxial static loads and vertical dynamic load conditions, and rock fragments after the test are collected. The fragments of sandstone generated from strain rockburst test and uniaxial compression test are also collected. The fragments are weighed and the length, width and thickness of each piece of fragments are measured respectively. The fragment quantities with coarse, medium, fine and micro grains in different size ranges, mass and particles distributions are also analyzed. Then, the fractal dimension of fragments is calculated by the methods of size-frequency, mass-frequency and length-to-thickness ratio-frequency. It is found that the crushing degree of impact rockburst fragments is higher, accompanied with blocky character- istics observably. The mass percentage of small grains, including fine and micro grains, in impact rock- burst test is higher than those in strain rockburst test and uniaxial compression test. Energy dissipation from rockburst tests is more than that from uniaxial compression test, as the quantity of micro grains generated does.展开更多
Rockburst is a phenomenon where sudden,catastrophic failure of the rock mass occurs in underground deep regions or areas with high tectonic stress during the excavation process.Rockburst disasters endanger the safety ...Rockburst is a phenomenon where sudden,catastrophic failure of the rock mass occurs in underground deep regions or areas with high tectonic stress during the excavation process.Rockburst disasters endanger the safety of people's lives and property,national energy security,and social interests,so it is very important to accurately predict rockburst.Traditional rockburst prediction has not been able to find an effective prediction method,and the study of the rockburst mechanism is facing a dilemma.With the development of artificial intelligence(AI)techniques in recent years,more and more experts and scholars have begun to introduce AI techniques into the study of the rockburst mechanism.In previous research,several scholars have attempted to summarize the application of AI techniques in rockburst prediction.However,these studies either are not specifically focused on reviews of the application of AI techniques in rockburst prediction,or they do not provide a comprehensive overview.Drawing on the advantages of extensive interdisciplinary research and a deep understanding of AI techniques,this paper conducts a comprehensive review of rockburst prediction methods leveraging AI tech-niques.Firstly,pertinent definitions of rockburst and its associated hazards are introduced.Subsequently,the applications of both traditional prediction methods and those rooted in AI techniques for rockburst prediction are summarized,with emphasis placed on the respective advantages and disadvantages of each approach.Finally,the strengths and weaknesses of prediction methods leveraging AI are summarized,alongside forecasting future research trends to address existing challenges,while simultaneously proposing directions for improvement to advance the field and meet emerging demands effectively.展开更多
The key to achieving rockburst warning lies in the understanding of rockburst precursors.Considering the cor-relation characteristics of rockburst acoustic emission(AE)parameters,a self-organizing map neural network(S...The key to achieving rockburst warning lies in the understanding of rockburst precursors.Considering the cor-relation characteristics of rockburst acoustic emission(AE)parameters,a self-organizing map neural network(SOMNN)based method for rockburst precursor inversion was proposed.The feature of this method lies in a cyclic data segmentation iteration process based on the thinking of“interference signal screening”,“key signal extraction”,and“precursor signal inversion”.The rationality of this method has been verified in three groups of rockburst experiments.The results revealed that rockburst AE precursor signals consist of a series of signals characterized by long duration,high energy,low average frequency,high energy amplitude,and low peak fre-quency.Subsequently,potential value in long term rockburst warning of the precursor obtained in this study was shown via the comparison of conventional precursors.Finally,a preliminary interpretation for rockburst pre-cursor was proposed under the framework of AE parameters physical significance,and it is revealed that AE precursor signals are likely linked to the creation of large-scale tensile cracks before rockburst.展开更多
基金supported by the National Natural Science Foundation of China (41941018)the Foundation of State Key Laboratory for Geomechanics and Deep Underground Engineering (SKLGDUEK 2217)the Foundation of Collaborative Innovation Center for Prevention and Control of Mountain Geological Hazards of Zhejiang Province (PCMGH-2022-03).
文摘Rockburst disasters occur frequently during deep underground excavation,yet traditional concepts and methods can hardly meet the requirements for support under high geo-stress conditions.Consequently,rockburst control remains challenging in the engineering field.In this study,the mechanism of excavation-induced rockburst was briefly described,and it was proposed to apply the excavation compensation method(ECM)to rockburst control.Moreover,a field test was carried out on the Qinling Water Conveyance Tunnel.The following beneficial findings were obtained:Excavation leads to changes in the engineering stress state of surrounding rock and results in the generation of excess energy DE,which is the fundamental cause of rockburst.The ECM,which aims to offset the deep excavation effect and lower the risk of rockburst,is an active support strategy based on high pre-stress compensation.The new negative Poisson’s ratio(NPR)bolt developed has the mechanical characteristics of high strength,high toughness,and impact resistance,serving as the material basis for the ECM.The field test results reveal that the ECM and the NPR bolt succeed in controlling rockburst disasters effectively.The research results are expected to provide guidance for rockburst support in deep underground projects such as Sichuan-Xizang Railway.
基金The financial support from the National Natural Science Foundation of China(Grant Nos.41941018 and 52074299)the Fundamental Research Funds for the Central Universities of China(Grant No.2023JCCXSB02)。
文摘Rockburst are often encountered in tunnel construction due to the complex geological conditions.To study the influence of unloading rate on rockburst,gneiss rockburst experiments were conducted under three groups of unloading rates.A high-speed photography system and acoustic emission(AE)system were used to monitor the entire process of rockburst process in real-time.The results show that the intensity of gneiss rockburst decreases with decrease of unloading rate,which is manifested as the reduction of AE energy and fragments ejection velocity.The mechanisms are proposed to explain this effect:(i)The reduction of unloading rate changes the crack propagation mechanism in the process of rockburst.This makes the rockbursts change from the tensile failure mechanism at high unloading rate to the tension-shear mixed failure mechanism at low unloading rate,and more energy released in the form of shear crack propagation.Then,less strain energy is converted into kinetic energy of fragments ejection.(ii)Less plate cracking degree of gneiss has taken shape due to decrease of unloading rate,resulting in the destruction of rockburst incubation process.The enlightenments of reducing the unloading rate for the project are also described quantitatively.The rockburst magnitude is reduced from the medium magnitude at the unloading rate of 0.1 MPa/s to the slight magnitude at the unloading rate of 0.025 MPa/s,which was judged by the ejection velocity.
基金The financial support from the National Natural Science Foun-dation of China(Grant Nos.52074299 and 41941018)the Fundamental Research Funds for the Central Universities of China(Grant No.2023JCCXSB02)are gratefully acknowledged.
文摘To investigate the mechanism of rockburst prevention by spraying water onto the surrounding rocks,15 experiments are performed considering different water absorption levels on a single face.High-speed photography and acoustic emission(AE)system are used to monitor the rockburst process.The effect of water on sandstone rockburst and the prevention mechanism of water on sandstone rockburst are analyzed from the perspective of energy and failure mode.The results show that the higher the ab-sorption degree,the lower the intensity of the rockburst after absorbing water on single side of sand-stone.This is reflected in the fact that with the increase in the water absorption level,the ejection velocity of rockburst fragments is smaller,the depth of the rockburst pit is shallower,and the AE energy is smaller.Under the water absorption level of 100%,the magnitude of rockburst intensity changes from medium to slight.The prevention mechanism of water on sandstone rockburst is that water reduces the capacity of sandstone to store strain energy and accelerates the expansion of shear cracks,which is not conducive to the occurrence of plate cracking before rockburst,and destroys the conditions for rockburst incubation.
基金Financial support from the National Key Research and Development Program (No.2016YFC0600901)the National Natural Science Foundation of China (No.51704298)
文摘A new rockburst classification, innovative works in developing a ‘‘strainburst test machine" and an‘‘impact-induced rockburst test machine" that can reproduce rockbursts in laboratory were researched.New concepts were proposed regarding the stress paths that take into account both the static and dynamic stresses analogous to that at excavation boundaries for generating artificially-induced strainburst and impact-induced rockburst. As an important method for rockburst control, a novel energyabsorbing bolt was developed, which has a constant-resistance under both static and impact loadings and a large-elongation capacity for containing large deformations of rock masses under burst-prone conditions.
基金The authors would like to thank the editors and the anonymous reviewers for their helpful and constructive comments.This study was supported by National Key Technologies Research&Development Program(Grant No.2018YFC0808402)State Key Laboratory for GeoMechanics and Deep Underground Engineering,China University of Mining and Technology(Grant No.SKLGDUEK1824)the Fundamental Research Funds for the Central Universities(Grant No.FRF-TP-20-004A2).
文摘Rocks in underground works usually experience rather complex stress disturbance.For this,their fracture mechanism is significantly different from rocks subjected to conventional triaxial compression conditions.The effects of stress disturbances on rock geomechanical behaviors under fatigue loading conditions and triaxial unloading conditions have been reported in previous studies.However,little is known about the dependence of the unloading rate on fatigue loading and confining stress unloading(FL-CSU)conditions that influence rock failure.In this paper,we aimed at investigating the fracture behaviors of marble under FL-CSU conditions using the post-test X-ray computed tomography(CT)scanning technique and the GCTS RTR 2000 rock mechanics system.Results show that damage accumulation at the fatigue stage can influence the final fracture behaviors of marble.The stored elastic energy for rock samples under FL-CSU tests is relatively larger compared to those under conventional triaxial tests,and the dissipated energy used to drive damage evolution and crack propagation is larger for FL-CSU tests.In FL-CSU tests,as the unloading rate increases,the dissipated energy grows and elastic energy reduces.CT scanning after the test reveals the impacts of the unloading rate on the crack pattern and a fracture degree index is therein defined in this context to represent the crack dimension.It shows that the crack pattern after FL-CSU tests depends on the unloading rate,and the fracture degree is in agreement with the analysis of both the energy dissipation and the amount of energy released.The effect of unloading rate on fracture evolution characteristics of marble is revealed by a series of FL-CSU tests.
文摘Impact rockburst test on sandstone samples with a central hole is carried out under true triaxial static loads and vertical dynamic load conditions, and rock fragments after the test are collected. The fragments of sandstone generated from strain rockburst test and uniaxial compression test are also collected. The fragments are weighed and the length, width and thickness of each piece of fragments are measured respectively. The fragment quantities with coarse, medium, fine and micro grains in different size ranges, mass and particles distributions are also analyzed. Then, the fractal dimension of fragments is calculated by the methods of size-frequency, mass-frequency and length-to-thickness ratio-frequency. It is found that the crushing degree of impact rockburst fragments is higher, accompanied with blocky character- istics observably. The mass percentage of small grains, including fine and micro grains, in impact rock- burst test is higher than those in strain rockburst test and uniaxial compression test. Energy dissipation from rockburst tests is more than that from uniaxial compression test, as the quantity of micro grains generated does.
基金supported by the Institute for Deep Underground Science and Engineering(XD2021021)the BUCEA Post Graduate Innovation Project(PG2024099).
文摘Rockburst is a phenomenon where sudden,catastrophic failure of the rock mass occurs in underground deep regions or areas with high tectonic stress during the excavation process.Rockburst disasters endanger the safety of people's lives and property,national energy security,and social interests,so it is very important to accurately predict rockburst.Traditional rockburst prediction has not been able to find an effective prediction method,and the study of the rockburst mechanism is facing a dilemma.With the development of artificial intelligence(AI)techniques in recent years,more and more experts and scholars have begun to introduce AI techniques into the study of the rockburst mechanism.In previous research,several scholars have attempted to summarize the application of AI techniques in rockburst prediction.However,these studies either are not specifically focused on reviews of the application of AI techniques in rockburst prediction,or they do not provide a comprehensive overview.Drawing on the advantages of extensive interdisciplinary research and a deep understanding of AI techniques,this paper conducts a comprehensive review of rockburst prediction methods leveraging AI tech-niques.Firstly,pertinent definitions of rockburst and its associated hazards are introduced.Subsequently,the applications of both traditional prediction methods and those rooted in AI techniques for rockburst prediction are summarized,with emphasis placed on the respective advantages and disadvantages of each approach.Finally,the strengths and weaknesses of prediction methods leveraging AI are summarized,alongside forecasting future research trends to address existing challenges,while simultaneously proposing directions for improvement to advance the field and meet emerging demands effectively.
基金support from the National Natural Science Foundation of China(No.52074299,No.41941018)the Fundamental Research Funds for the Central Universities(No.2023JCCXSB02)the China Geological Survey projects(No.DD20200319)are gratefully acknowledged.
文摘The key to achieving rockburst warning lies in the understanding of rockburst precursors.Considering the cor-relation characteristics of rockburst acoustic emission(AE)parameters,a self-organizing map neural network(SOMNN)based method for rockburst precursor inversion was proposed.The feature of this method lies in a cyclic data segmentation iteration process based on the thinking of“interference signal screening”,“key signal extraction”,and“precursor signal inversion”.The rationality of this method has been verified in three groups of rockburst experiments.The results revealed that rockburst AE precursor signals consist of a series of signals characterized by long duration,high energy,low average frequency,high energy amplitude,and low peak fre-quency.Subsequently,potential value in long term rockburst warning of the precursor obtained in this study was shown via the comparison of conventional precursors.Finally,a preliminary interpretation for rockburst pre-cursor was proposed under the framework of AE parameters physical significance,and it is revealed that AE precursor signals are likely linked to the creation of large-scale tensile cracks before rockburst.