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Managing rockbursting conditions in mine development and operational environments is a complex and difficult challenge. The hazard and the associated risks can be managed based on local experience, monitoring, and informed data-rich analysis. On the other hand, blind development for deep tunnelling is being carried out around the world at depths in...
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... are explosive failures of rock which occur when very high stress concentrations are induced around underground openings. The problem is particularly acute in deep level mining in hard brittle rock. Figure 3 shows the damage resulting from a rockburst in an underground mine. The deep level gold mines in the Witwatersrand area in South Africa, the Kolar gold mines in India, the nickel mines centred on Sudbury in Canada, the mines in the Coeur d'Alene area in Idaho in the USA and the gold mines in the Kalgoorlie area in Australia, are amongst the mines which have suffered from rockburst problems. The results of a rockburst in an underground mine in brittle rock subjected to very high ...
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... To meet the increasing energy demand, energy extraction is moving toward deeper levels, posing new challenges [1][2][3][4][5]. Rockburst, an abrupt and instantaneous engineering disaster, is triggered by deep construction, releasing energy along the free face, causing severe brittle damage and deformation [6][7][8]. These disasters threaten the safety of construction personnel, disrupt construction progress, and shorten equipment lifespan, posing a significant limitation to deep tunnel construction [9]. ...
To investigate the influence of water content on the rockburst phenomena in tunnels with horizontal joints, experiments were conducted on simulated rock specimens exhibiting five distinct levels of water absorption. Real-time monitoring of the entire blasting process was facilitated through a high-speed camera system, while the microscopic structure of the rockburst debris was analyzed using scanning electron microscopy (SEM) and a particle size analyzer. The experimental findings revealed that under varying degrees of water absorption, the specimens experienced three stages: debris ejection; rockburst; and debris spalling. As water content increased gradually, the intensity of rockburst in the specimens was mitigated. This was substantiated by a decline in peak stress intensity, a decrease in elastic modulus, delayed manifestation of pre-peak stress drop, enhanced amplitude, diminished elastic potential energy, and augmented dissipation energy, resulting in an expanded angle of rockburst debris ejection. With increasing water content, the bond strength between micro-particles was attenuated, resulting in the disintegration of the bonding material. Deformation failure was defined by the expansion of minuscule pores, gradual propagation of micro-cracks, augmentation of fluffy fine particles, exacerbation of structural surface damage akin to a honeycomb structure, diminishment of particle diameter, and a notable increase in quantity. Furthermore, the augmentation of secondary cracks and shear cracks, coupled with the enlargement of spalling areas, signified the escalation of deformation failure. Simultaneously, the total mass of rockburst debris gradually diminished, accompanied by a corresponding decrease in the proportion of micro and fine particles within the debris.
... The research results are significant for rockburst support and risk assessment. [13] 、Weng等 [14] 基于数值模拟，使用能量 释放指标对岩爆进行分析预测. Diederichs [ [17−19] 提出了与塑性应变相关的CWFS模型，用 来描述脆性岩石加卸载破坏过程中各强度组分与 [20] . ...
Rockburst disasters pose an increasing threat to the construction safety of deep-buried engineering; thus, rockburst prediction is crucial for ensuring construction safety. However, due to the spatial variation in mechanical properties of rock mass, the actual results of rockburst prediction remain uncertain to some extent. In this study, rockburst tendency and its probability were studied to explore a more suitable evaluation method for rockburst tendency in engineering practice. First, an improved cohesion weakening-friction strengthening model was developed considering the dynamic change of rock dilatancy strength, and the rockburst tendency analysis was combined with the energy index. The point estimation-finite element analysis method was used to analyze rockburst tendency based on the Dahongshan copper mine project buried at a depth greater than 1,000 m. A finite element model was constructed, in which initial cohesion, residual cohesion, residual friction angle, viscous plastic strain critical value, critical value of
... In the last decades, techniques based on numerical models have shown their potential to investigate in depth the phenomenon of rockburst and its triggering mechanisms. There are different authors that have developed empirical methods based on historical cases [2], [3] and analytical methods using numerical modeling [4] to relate and determine the depth of failure in deep excavations. On the other hand, different authors have studied this phenomenon (many of them using numerical modeling) with respect to determining its occurrence's mechanism [5], how to assess its magnitude [2], [3], [6] and how to prevent them [7]. ...
... They determined that when σ max σ c ⁄ is greater than 0.4, instability occurs. Diederichs [4] proposes a depth of failure prediction graph that is more rigorous (Figure 1.b), based on numerical modeling analysis using the Damage Initiation Spalling Limit (DISL) approach [8]. The DISL approach was developed to simulate the brittle failure of the rock mass in conventional engineering software. ...
... Peak and Residual parameter proposed by Diederichs[4]. ...
As a result of the intense exploitation of mineral resources on the surface, mining excavations must migrate to deeper environments. At greater depths, in-situ stresses increase along with the probability of rockburst occurrence. Different authors have studied this phenomenon in depth, however, the influence of the variability of en- vironmental parameters on rockburst potencial has not been studied in detail. This paper proposes to respond to this limit. More than 300 numerical models have been ran using Rocscience’s RS3 software to perform a sensitivity analysis of the main geomechanical parameters of the environment such as UCS, GSI, rock density and the elastic parameters (Young and Poisson’s modulus). Moreover, various depths have been considered to vary the in-situ stress. The Damage Initiation Spalling Limit (DISL) approach proposed by Diederichs (2007) has been considered to simulate the brittle failure of the rock mass and estimate the depth of failure around the excavation in all simulations. This work high- lights the influence of the uniaxial compressive strength (UCS) and the in-situ stresses over the rest of the parameters. The elastic parameters of the rock mass do not influence excavation instability. Moreover, the GSI has no influence in our study, which seems to show that it is underestimated using the DISL approach. Based on this work, a series of recommendation when simulating deep excavation is provided.
... To address dynamic instability issues, the core element is the risk management strategy, which is an extension of the control strategy. Notably, Diederichs (2018) introduced the well-known ''Butterfly" risk management strategy for rockburst in hard rock excavations (refer to Fig. 15). The butterfly risk management consists of two components: the propensity to disaster and its resulting consequences. ...
The technical challenges associated with deep underground space activities have become increasingly significant. Among these challenges, one major concern is the assessment of rockburst risks and the instability of rock masses. Extensive research has been conducted by numerous scholars to mitigate the risks and prevent occurrences of rockburst through various assessment methods. Rockburst incidents commonly occur during the excavation of hard rock in underground environments, posing severe threats to personnel safety, equipment integrity, and operational continuity. Thus, it is crucial to systematically document real cases of rockburst, allowing for a comprehensive understanding of the underlying mechanisms and triggering conditions. This understanding will contribute to the advancement of rockburst prediction and prevention methods. Proper selection of an appropriate rockburst assessment method is a fundamental aspect in underground operations. However, there is a limited number of studies that summarize and compare different prediction and prevention methods of rockburst. This paper aims to address this gap by analyzing global trends using CiteSpace software since 1990. It discusses rockburst classification and characteristics, comprehensively reviews research findings related to rockburst prediction, including empirical, simulation, mathematical modeling, and microseismic monitoring methods. Additionally, the paper presents a compilation of current rockburst prevention measures. Notably, the paper emphasizes the significance of control strategies, which provide key insights into the effective utilization of stored energy within rock. Finally, the paper concludes by suggesting six directions for implementing intelligent management techniques to mitigate hazards during underground operations and reduce the probability of rockburst incidents.
... While work has been done to assess the rockburst hazard better [3,18,32], and improve the rock support system and preconditioning measures currently implemented [7,25,28,33,34], the effect of mitigation measures on strain burst hazard potential is unclear. This paper studies the influence of the implementation of shotcrete and rockbolts support and destress blasting in tunnels on strain burst potential. ...
... Deep underground mining and civil tunnels are associated with high stress magnitudes that can lead to serious ground control problems [1,2]. One of these main problems are the rockbursts, which are explosive failures of rock that occur when high stress concentrations are induced around underground openings in brittle rock masses [3]. Usually, rockbursts are divided into three categories based on their mechanism of occurrence [4][5][6]: ...
... However, due to the complex nature of the rockburst phenomenon, rockburst prediction is quite difficult. Over the years, various methods have been developed based on empirical knowledge [9][10][11], numerical modeling [3,[12][13][14] or statistical analysis [15][16][17]. A comprehensive review of some of these methods and others can be found in the work of Zhou et al. [18]. ...
Strain burst hazard is one of the main challenges that faces deep underground environments. To manage it, it is needed to assess its probability occurrence (or potential). Various methods have been proposed over the years to assess the phenomenon early on. However, due to uncertainties in rock mass properties and the physical processes of the phenomenon, mitigation measures are an additional important line of defense to ensure workplace safety. While work has been carried out to assess the rockburst hazard better and improve support systems, the effect of mitigation measures on strain burst hazard potential is unclear. This paper studies the influence of the implementation of shotcrete and rockbolts support and destress blasting in tunnels on strain burst potential, based on two-dimensional numerical models of circular tunnels. The results highlight that, as expected, the use of mitigation measures allows the strain burst occurrence to decrease. However, the strain burst hazard level does not decrease easily, even when using mitigation measures. In the case of serious overbreak hazards, only a combination of system support and destress blasting seems to have an impact on these events, and not for all the simulated cases.
... The mechanical properties of the intact rocks are important for studying strainburst. Slabbing can be the precursor of strainburst [44], and when the rock masses suddenly release a lot of energy, slabbing can develop into strainburst [45]. As for squeezing, the critical strain had been proposed to quantify the potential of the rock masses to the degree of squeezing, which mainly relies on the properties of intact rock [46]. ...
Squeezing, slabbing, and strainburst are typical failure modes of overstressed rock masses in deep rock excavation engineering. This study considered intact rock properties to evaluate squeezing, slabbing, and strainburst, owing to the effectiveness and availability of these parameters. Hybrid models combining the Jaya algorithm and support vector machine (JA-SVM) were proposed to predict the failure modes of overstressed rock masses based on the collected database. JA-SVM model achieved a training accuracy of 0.970 and a testing accuracy of 0.875. Ranking system and Taylor diagrams showed that the developed hybrid model was superior to other machine learning (ML) models, including SVM, artificial neural network, etc. Receiver operator characteristic curves suggested that JA-SVM had a more powerful ability to predict strainburst and slabbing compared to other widely applied ML techniques. Performed sensitive analysis revealed that the brittleness index and elastic modulus were vital factors in estimating failure modes. The developed model can be applied to identify failure modes of overstressed rock masses in the initial phases of a deep underground project, and appropriate support measures can be prepared beforehand based on estimation results.
... Using observations from deep civil tunneling projects, Diederichs (2018) proposed the dynamic rupture potential (DRP), based on the UCS and brittleness of the rock, as an indicator for higher energy strainbursting over lower energy spalling. Stronger and more brittle rocks tend to have a higher DRP as they store more elastic strain energy in the pre-peak phase of loading and fracture more suddenly and energetically during the post-peak phase of unloading. ...
... Because of the evolving understanding of rockburst damage mechanisms and the unique characteristics of cave mining, the existing empirical tools used for rockburst assessments are often not fully applicable. For example, qualitative scales are commonly used to describe the severity of rockburst damage in databases (e.g., Kaiser et al. 1992Kaiser et al. , 1996Heal et al. 2006;Hudyma and Potvin 2010;Diederichs 2018). For simplicity, the rockburst damage is sometimes considered as a point source and the damage is described based on an estimate of the total mass of rock that was displaced and the condition of the support systems. ...
Mass mining methods such as block and panel caving are more commonly being utilized to generate value from deep, low-grade ore deposits. In addition to mining deeper and encountering higher in situ stresses, these projects are also mining larger volumes in more competent rock masses, increasing their exposure to brittle rock failure mechanisms such as spalling and rockbursting. Rockbursting presents a health and safety risk for mine personnel, a financial risk for mine operators, and a significant design challenge for engineers. A methodology is proposed for recording, databasing, and performing data-driven assessments of rockbursting in cave mines with the goal of correctly identifying the damage mechanisms, the triggers, and important controlling factors. Novel databasing techniques and new indices are introduced that are specifically tailored to cave mining operations where the damage from rockbursts may be widespread across a large extraction-level footprint. A case study of the Deep Mill Level Zone (DMLZ) panel cave mine is presented to demonstrate the data-driven analysis techniques. Using the proposed indices and data analysis techniques, strainbursting was identified as the dominant rockburst damage mechanism in the DMLZ, with load redistribution from blasting and advance of the undercut and mining of the cave being identified as the main triggers. Contributing factors for the rockbursting in the DMLZ are discussed including the mining sequence, the mine geometry, and the geology. Evidence for veining heterogeneity contributing to increased susceptibility to strainbursting is presented, a key finding with practical implications for future mass mines.
... [2]; and, b. Stress path approach for determining burst potential based on energy storage release [8]. ...
... For the horseshoe tunnel, granite rock mass at K=4 shows slabbing for all points and bursting at point 15 m. Many researchers suggested that the failure occurs when the major principal stress ranges from 40% to 60% of the intact UCS [2], [8]. Comparing the depth of failure from the empirical formulas by [4], [12] with the numerically observed depth of the failure by the strength factor approach, it can be stated that the numerical models provide good precision at K equal to 4. The extent of failure estimated from the strength factor approach showed variations especially with different surfaces of the horseshoe tunnel. ...
Strain bursting is a phenomenon associated with deep underground excavations and tunnelling in brittle hard rocks that result in a sudden and violent failure, posing high risks and damage. This work aims to assess the strain bursting and the energy response characteristics and develop a guideline that can be utilized in the preliminary investigation stage. The obtained results are intended to enable predicting different brittle behaviours in deep geological environments. Elastic stress analysis using the DISL approach based on boundary element method is established (EX3-software) for the assessment of two tunnel geometries (circular, horseshoe) in granitic rock mass. Two different stress states are modelled to simulate the potential stress regime. The analysis’ results demonstrate that different geometries affect the energy storage capacity and result in different behaviour regarding the bursting potential of the rock mass.
... Generally, rockburst can be classified into two types: remotely triggered and self-initiated (Kaiser et al. 1996). Studies have shown that many rockbursts in mining environments are caused by the combination of a remote seismic event triggered by large-scale mining activities and high static stress, while the primary source of rockbursts is the rock mass itself around the tunnel in civil engineering projects (Diederichs 2018;Mutke et al. 2015). This research specifically focuses on the evaluation of the performance of yielding rockbolts during remotely triggered rockbursts. ...
The assessment of yielding rockbolt performance during rockbursts with actual seismic loading is essential for rockburst supporting designs. In this paper, two types of yielding rockbolts (D-bolt and Roofex) and the fully resin-grouted rebar bolt are modeled via the “rockbolt” element in universal distinct element code (UDEC) after an exact calibration procedure. A two-dimensional (2D) model of a deep tunnel is built to fully evaluate the performance (e.g., capacity of energy-absorption and control of rock damage) of yielding and traditional rockbolts based on the simulated rockbursts. The influence of different rockburst magnitudes is also studied. The results suggest that the D-bolt can effectively control and mitigate rockburst damage during a weak rockburst because of its high strength and deformation capacity. The Roofex is too “soft” or “smooth” to limit the movement of ejected rocks and restrain the large deformation, although it has an excellent deformation capacity. The resin-grouted rebar bolt can maintain a high axial force level during rockbursts but is easy to break during dynamic shocks, which fails to control rapid rock bulking or ejection. Three types of rockbolts cannot control the large deformation and mitigate rockburst damage effectively during violent rockbursts. The rockburst damage severity can be significantly reduced by additional support with cable bolts. This study highlights the effectiveness of numerical modeling methods in assessing the complex performance of yielding rockbolts during rockbursts, which can provide some references to improve and optimize the design of rock supporting in burst-prone grounds.
... Cai and Kaiser (2018) define strainburst as a sudden and violent failure of rock near an excavation boundary caused by excessive straining of an un-fractured or partially fractured volume of stiff and strong rock. The primary source of seismicity is the rock mass around the tunnel itself, and not a remote seismic event (Diederichs 2018). Strainbursts are, therefore, a specific kind of rockburst. ...
... The potential for energy storage and rapid release must be accounted for in order to understand the burst potential early in the basic design stage. Considerations of rock petrology, fabric, mechanical parameters, and structure allow an estimate of brittle response (Diederichs 2018). ...
... The Dynamic Rupture Potential (DRP) (Diederichs 2018) expands the approach of Zhang et al. (2012). Thereby it is possible to rank rock types based on their brittle character and the capacity for energy storage, represented by unconfined compressive strength. ...
As mining and tunnelling projects advance to deeper areas, strainbursts occur more frequently. This failure mode is extremely dangerous, as the rock mass fails abruptly, releasing high amounts of energy. This poses a high risk to the life of workers and equipment used. For a robust strainburst risk assessment many factors have to be taken into account. Besides geological features, overburden, excavation method, etc., rocks’ intrinsic proneness to strainburst plays a major role. Whether a rock tends to this failure behaviour depends strongly on the rocks’ mechanical and structural characteristics at the grain-level, especially on its heterogeneity. The authors demonstrate this based on different rock-like sample sets, consisting of a very fine-grained fibreless ultra-high-performance concrete (UHPC) and a constant volumetric fraction of coarse aggregates. Thereby, the heterogeneity aspect was introduced by the different properties of the aggregates. A laboratory program was performed, taking into account uniaxial compression tests (including post-failure tests to evaluate the failure energy) and Acoustic Emission Testing (to monitor the cracking activity). The study underlines the high suitability of using Acoustic Emission Testing (AET) in strainburst risk assessment. In addition, the authors analyse empirical parameters commonly used to evaluate rocks’ intrinsic proneness to strainburst, and give recommendations regarding their application. Overall, the study substantiates former research and emphasises the usefulness of petrographic information within strainburst risk analysis. It also sets the base for future research on real rock, which will hopefully lead to more specific recommendations for practitioners on how to include rocks’ grain-scale characteristics in strainburst risk analysis.
