Classification of mine workings according to their rockburst proneness

doi:10.1016/S0167-9031(89)90404-0

Mining Science and Technology

Volume 8, Issue 3, May 1989, Pages 253-262

Mining Science and T...

https://doi.org/10.1016/S0167-9031(89)90404-0 Get rights and content

Abstract

The development of an approach to define the rockburst-prone areas in mines is discussed. The role of bursting indices, in-situ approaches, geological features, mining conditions and observations in identifying the burst-prone mine workings is outlined.

In addition, a laboratory investigation was conducted on rock specimens from Sudbury Nickel Belt in Canada to determine the important indices and rock properties. It has been observed that the decrease modulus index depends on the burst-proneness index, strength, brittleness and the strain energy stored in the rock specimens. The burst-proneness index exhibited reasonable correlation with the Schmidt rebound hardness number and shear wave velocity. The use of the decrease modulus index and burst-proneness index to assess the burst-tendency of hard rocks is also described.

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The natural property of rock material, whether impact occurs, is the key influencing factor of the occurrence of rock burst disaster. To accurately assess rock burst proneness, this study focuses on typical sandstone as the research object. Uniaxial cyclic loading and unloading tests were conducted to measure the elastic strain energy accumulated in sandstone under different stress levels and a relationship between elastic strain energy and stress level was established. The results show that: (1) The peak stress under cyclic loading and unloading conditions is slightly lower than the uniaxial compressive strength. With an increase in the number of cycles, the internal damage of sandstone continues to accumulate, and the mechanical properties such as compressive strength continue to deteriorate; (2) With an increase in stress, the input strain energy, elastic strain energy, and dissipated strain energy also increase; (3) When the stress is low, the increase in elastic strain energy is large and shows a steady growth; with an increase in stress, the increase of elastic strain energy decreases; (4) The square of stress at any time has a good linear relationship with elastic strain energy. According to the relationship obtained from the test, the elastic strain energy at the peak stress time can be obtained; (5) A new criterion for assessing rock burst proneness is proposed: residual energy release rate index $W_{T}$ , which characterizes the energy release per unit time when the rock burst occurs. The intervals for evaluating the rock burst proneness of the residual energy release rate index $W_{T}$ are as follows: $W_{T}$ <0.025, indicating no rock burst proneness; 0.025≤ $W_{T}$ <0.15, indicating weak rock burst proneness; 0.15≤ $W_{T}$ <2, indicating medium rock burst proneness; $W_{T}$ >2, indicating strong rock burst proneness; and (6) The rationality of the proposed residual energy release rate index $W_{T}$ is verified by the multi-index method and the multi-sample method, and the proposed residual energy release rate index is used to determine the rock burst proneness of 10 kinds of rock samples. The evaluation accuracy is shown to be high, and it can reflect the actual rock burst proneness
True-triaxial experimental study on the brittle failure of granite conditioned by the TBM disc cutter
2023, International Journal of Rock Mechanics and Mining Sciences
The brittle failure induced by high in-site stress occurring at the tunnel face significantly affect the TBM performance. To study the rock mass failure mechanism under the combined effect of high stress and TBM cutters, three groups of true-triaxial rockburst tests were conducted, simulating the failure processes using the loading scheme “one-single face free and the remaining five surfaces loaded”. Conditioned granite specimens previously cut by the TBM cutter were prepared, and the different stressed conditions were determined based on the in-situ stress field of the Yinhan water conveyance tunnel. As the confining stress increased, the peak strength of the rock specimen also increased, and the final rupture was more violent, leading to a rockburst. The failure process recorded by the high-speed camera and the failure pattern showed a clear change. The rock conditioned by the TBM cutter was more susceptible to brittle failure under high stress, and the failure depth was greater. The stress-strain curves in the $σ_{1}$ direction and the AE characteristics indicated that as the loading stress increased, the damage in the rock changed from a dominant tensile failure to a dominant shear failure, gradually extending to deeper areas of the rock. This alteration changed the rock mass mechanical behavior of the tunnel face, i.e., its stability and boreability, consequently influencing the rock breakage process by TBM cutters. As the severity of failure increased, the TBM performance shifted from a low efficiency rock-breaking performance limited by the cutter thrust to a high efficiency rock-breaking performance limited by the muck capacity and safety control.
Evaluation of rockburst risk in deep tunnels considering structural planes based on energy dissipation rate criterion and numerical simulation
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Risk evaluation of rockbursts is crucial for ensuring the safety and stability of deep-tunnel construction. Structural planes play an important role in the potential for rockbursts to occur, and more related studies are needed. In this paper, a new rockburst criterion based on energy dissipation rate (EDR) index was developed and the role of structural planes in rockburst potential was studied. Firstly, a method of generating structural planes and a viscoplastic constitutive model with internal variables were introduced for numerical simulation using FLAC3D. Then, tunnelling under different hydrostatic pressures was simulated to obtain the values of EDR index and stress-strength/strength-stress ratio indices, and EDR criterion was estimated based on stress-strength/strength-stress ratio criteria. The results show that EDR criterion is: 0∼1 Pa/s (no risk), 1∼3 Pa/s (low risk), 3∼6 Pa/s (medium risk), >6 Pa/s (high risk). Subsequently, the case study of rockbursts in the drainage tunnel of Jinping II hydropower station was conducted considering a nearby fault to validate EDR criterion. The simulation results using EDR are basically consistent with actual rockbursts in terms of the potential location, intensity and time. Finally, the numerical simulations of tunnel excavation considering a joint set with different dip angles were implemented, and the influences of joints on rockbursts were investigated using EDR. Analysis results show that rockbursts are prone to occur on tunnel walls parallel and perpendicular to joints; potential rockburst locations are controlled by local joints and are less affected by geostress distribution. Joints may increase the intensity, delay the occurrence time, and control the pit boundaries of rockbursts. Obtained EDR contours can be used to infer damaged zones of strainbursts and strain-structure slip rockbursts and understand inducing mechanism of rockbursts in Jinping II drainage tunnel. The findings of this study provide insight into the role of structural planes on rockbursts. The presented methodology can be applied to rockburst evaluation and prevention during the construction of deep tunnels.
A review of rockburst: Experiments, theories, and simulations
2023, Journal of Rock Mechanics and Geotechnical Engineering
Citation Excerpt :
Brittleness can be evaluated using strength parameters, mineral compositions, and the stress–strain curve (Kuang et al., 2021). The most commonly used brittleness indices for rockburst are the ratio of the compressive strength to tensile strength (Qiao and Tian, 1998; Feng et al., 2000; Li et al., 2001) and deformation indices based on the stress–strain curve (e.g. DMI and Ku (Singh, 1989; Li et al., 2001)). Tarasov and Randolph (2011) found that the brittleness of hard rock will be significantly activated under high stress.
Rockburst is becoming a huge challenge for the utilization of deep underground space. Extensive efforts have been devoted to investigating the rockburst behavior and mechanism experimentally, theoretically, and numerically. The aim of this review is to discuss the novel development and the state-of-the-art in experimental techniques, theories, and numerical approaches proposed for rockburst. The definition and classification of rockburst are first summarized with an in-depth comparison among them. Then, the available laboratory experimental technologies for rockburst are reviewed in terms of indirect and direct approaches, with the highlight of monitoring technologies and data analysis methods. Some key rockburst influencing factors (i.e. size and shape, rock types, stress state, water content, and temperature) are analyzed and discussed based on collected data. After that, rockburst theories and mechanisms are discussed and evaluated, as well as the microscopic observation. The simulation approaches of rockburst are also summarized with the highlight of optional novel numerical methods. The accuracy, stability, and reliability of different experimental, theoretical and numerical approaches are also compared and assessed in each part. Finally, a summary and some aspects of prospective research are presented.
A rockburst prediction model based on extreme learning machine with improved Harris Hawks optimization and its application
2023, Tunnelling and Underground Space Technology
As sudden, random, and uncertain rock dynamic disasters, rockbursts often threaten the lives of construction workers. Therefore, developing new rockburst intensity prediction methods is particularly important for the design and construction of hard rock geotechnical engineering projects. In this paper, a rockburst prediction method based on extreme learning machine (ELM) with improved Harris Hawks optimization (IHHO) was proposed for more accurate rockburst intensity predictions. First, 136 sets of typical rockburst case data were selected and subjected to normalization to get dimensionless data. Then, chaotic mapping and crossover and mutation operators were used to improve the Harris hawks optimization (HHO) and enhance its global search capability. Then 9 test functions were used to test, compare, and analyze the performance of genetic algorithm (GA), particle swarm optimization (PSO), HHO, and IHHO. Finally, a system was built based on the constructed rockburst intensity level prediction model and MATLAB programming. The comprehensive rockburst intensity level prediction system was applied to the headrace tunnels of Jinping-II Hydropower Station, contrasting the results of IHHO-ELM rockburst prediction model with those of FCM-MFIS model, six conventional machine learning models and the single-index rockburst criterion. The results show that its accuracy was as high as 94.12%, and has a higher convergence speed and higher prediction accuracy and may prove a new way of rockburst intensity level prediction.
Rockburst in underground excavations: A review of mechanism, classification, and prediction methods
2022, Underground Space (China)
Technical challenges have always been part of underground mining activities, however, some of these challenges grow in complexity as mining occurs in deeper and deeper settings. One such challenge is rock mass stability and the risk of rockburst events. To overcome these challenges, and to limit the risks and impacts of events such as rockbursts, advanced solutions must be developed and best practices implemented. Rockbursts are common in underground mines and substantially threaten the safety of personnel and equipment, and can cause major disruptions in mine development and operations. Rockbursts consist of violent wall rock failures associated with high energy rock projections in response to the instantaneous stress release in rock mass under high strain conditions. Therefore, it is necessary to develop a good understanding of the conditions and mechanisms leading to a rockburst, and to improve risk assessment methods. The capacity to properly estimate the risks of rockburst occurrence is essential in underground operations. However, a limited number of studies have examined and compared yet different empirical methods of rockburst. The current understanding of this important hazard in the mining industry is summarized in this paper to provide the necessary perspective or tools to best assess the risks of rockburst occurrence in deep mines. The various classifications of rockbursts and their mechanisms are discussed. The paper also reviews the current empirical methods of rockburst prediction, which are mostly dependent on geomechanical parameters of the rock such as uniaxial compressive strength of the rock, as well as its tensile strength and elasticity modulus. At the end of this paper, some current achievements and limitations of empirical methods are discussed.

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Classification of mine workings according to their rockburst proneness

Abstract

Min. Sci. Technol.

Assessment of the rockburst proneness in hard rock mines

The mechanism and control of rockbursts

Coal Mine Ground Control

Bursting liability indices of coal

Int. J. Rock Mech. Min. Sci.

Dynamic phenomena in mines and characteristics of rocks

Burst energy release index

Roc. Mech. Rock Eng.

A study into the mechanical properties of rocks with special reference to their bearing on the occurrence of rockbursts

S. Afr. Mech. Eng.

Energetic indicator of liability of rocks to bursts determined during shock loading with Hopkin's bar

Growth and development of microseismics applied to ground control and mine safety

Min. Eng.