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Experimental study on the effect of unloading rate on gneiss rockburst 被引量:1
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作者 Dongqiao Liu Jie Sun +4 位作者 Ran Li Manchao He binghao cao Chongyuan Zhang Wen Meng 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第6期2064-2076,共13页
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
关键词 ROCKBURST Unloading rate Crack propagation Influence mechanisms
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Experimental study on the effect of water absorption level on rockburst occurrence of sandstone 被引量:1
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作者 Dongqiao Liu Jie Sun +3 位作者 Pengfei He Manchao He binghao cao Yuanyuan Yang 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第1期136-152,共17页
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
关键词 ROCKBURST Water Prevention effect Crack evolution
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Experimental investigation on acoustic emission precursor of rockburst based on unsupervised machine learning method
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作者 Jie Sun Dongqiao Liu +4 位作者 Pengfei He Longji Guo binghao cao Lei Zhang Zhe Li 《Rock Mechanics Bulletin》 2024年第2期63-77,共15页
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
关键词 Rockburst Acoustic emission Precursor Machine learning
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