A review of rockburst: Experiments, theories, and simulations

He, Manchao; Cheng, Tai Hong; Qiao, Yafei; Li, Hongru

doi:10.1016/j.jrmge.2022.07.014

Cited by 131 publications

(27 citation statements)

References 216 publications

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“…Rock explosion is a significant hazard within underground engineering operations [1][2] , characterized by the sudden release of energy within the rock mass due to high stress conditions induced by excavation, mining activities, or external disturbances 3 . This phenomenon can result in various complex geological disasters such as bursting, stripping, ejection, or even expulsion of rock fragments.…”

Section: Introductionmentioning

confidence: 99%

Long-term prediction modeling of shallow rockburst with small dataset based on machine learning

Rao,

Wan,

Huang

et al. 2024

Preprint

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Rockburst present substantial hazards in both deep underground construction and shallow depths, underscoring the critical need for accurate prediction methods. This study addresses this need by collecting and analyzing 69 real datasets of rockburst occurring within a 500m burial depth, which poses challenges due to the dataset's multi-categorized, unbalanced, and small nature. Through a rigorous comparison and screening process involving 11 machine learning algorithms and optimization with KMeansSMOKE oversampling, the Random Forest algorithm emerged as the most optimal choice. Efficient adjustment of hyperparameters was achieved using the Optuna framework. The resulting KMSORF model, which integrates KMeansSMOKE, Optuna, and Random Forest, demonstrated superior performance compared to mainstream models such as GB, XBG, and ET. Application of the model in a tungsten mine and tunnel project showcased its ability to accurately forecast rockburst levels, thereby providing valuable insights for risk management in underground construction. Overall, this study contributes to the advancement of safety measures in underground construction by offering an effective predictive model for rockburst occurrences.

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Section: Introductionmentioning

confidence: 99%

Long-term prediction modeling of shallow rockburst with small dataset based on machine learning

Rao,

Wan,

Huang

et al. 2024

Preprint

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“…Rockburst is a sudden failure event of excavation-disturbed rock mass with the violent ejection of rock fragments [1,2]. This sudden and violent destruction often causes serious economic losses and casualties.…”

Section: Introductionmentioning

confidence: 99%

Damage Evolution and Energy Catastrophe Behavior during Quasi-static Loading Process of Rockburst

Luo,

Zhao,

Qian

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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Rockburst pose a serious hazard to deep underground engineering. The damage evolution and energy transformation of rockburst under quasi-static load are the key to reveal the mechanism of rockburst. Based on the instability theory and stiffness theory, the burst rock and surrounding rock combination specimens are designed in this study. Then a constitutive model for simulating the whole process of rockburst is established by statistical damage of rock. The law of damage deformation and energy evolution during rockburst is revealed, and the key factors affecting rockburst intensity are analyzed. The results indicate that the damage mechanism of rockburst is related to the sudden change of damage before and after the peak stress of the burst rock, and the volume ratio of surrounding rock to burst rock. The evaluation index of rockburst proneness based on energy evolution can reflect the energy conversion and transmission relationship between the surrounding rock and burst rock in the combination system, which is of great significance for the evaluation of rockburst proneness.

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“…3,4 Strong stress redistribution in deeply buried tunnels leads to frequent tunnel disasters, [5][6][7] such as large deformation 8 and rock bursts. 9,10 Therefore, it is greatly significant for tunnel design and safe construction to accurately reproduce the nonlinear mechanical behavior of surrounding rock (SR) in deeply buried tunnels and the distribution of the plastic zone after tunnel excavation. 11 F I G U R E 1 Calculation diagram of the deeply buried circular tunnel (modified after ref.…”

Section: Introductionmentioning

confidence: 99%

“…The nonlinear mechanical characteristics of rock under high in‐situ stress result in different ground reactions in deeply buried tunnels from that in shallow‐buried tunnels 3,4 . Strong stress redistribution in deeply buried tunnels leads to frequent tunnel disasters, 5–7 such as large deformation 8 and rock bursts 9,10 . Therefore, it is greatly significant for tunnel design and safe construction to accurately reproduce the nonlinear mechanical behavior of surrounding rock (SR) in deeply buried tunnels and the distribution of the plastic zone after tunnel excavation 11 …”

Section: Introductionmentioning

confidence: 99%

Effect of rock nonlinear mechanical behavior on plastic zone around deeply buried tunnel: An efficient semi‐analytical solution

Xiao,

Qiao,

et al. 2023

Num Anal Meth Geomechanics

Self Cite

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Adopting the novel proposed unified strain‐hardening and strain‐softening (UHS) model and finite difference method, an efficient semi‐analytical solution is proposed to study the influence of the nonlinear behavior of rock on ground reaction. The proposed solution eliminates stress vibrations of the classical method that occurred in the strain‐hardening zone, because it judges the elastic or plastic state of the calculation nodes before calculating the ground reaction; compared with the iterative solution, the proposed solution avoids iteratively solving for the plastic internal variables at each calculated node, resulting in that its computational efficiency is improved by more than 10 times. The proposed solution was verified by comparing it with the iterative solution, and numerical solution. Moreover, the effects of initial yield strength, peak strength, residual strength, and supporting pressure on ground reaction after tunnel excavation are studied. The results show that increasing the initial yield strength and residual strength will obviously decrease the plastic zone (PZ) and sub‐zones. The peak strength of rock has limited influence on the radius of PZ, which mainly adjusts the ratio of each sub‐zone in PZ. In addition, increasing the support pressure is an effective means to control the radius of PZ and sub‐zones in deep buried tunnels.

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A review of rockburst: Experiments, theories, and simulations

Cited by 131 publications

References 216 publications

Long-term prediction modeling of shallow rockburst with small dataset based on machine learning

Long-term prediction modeling of shallow rockburst with small dataset based on machine learning

Damage Evolution and Energy Catastrophe Behavior during Quasi-static Loading Process of Rockburst

Effect of rock nonlinear mechanical behavior on plastic zone around deeply buried tunnel: An efficient semi‐analytical solution

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