Rockburst Evaluation Research Articles

Research on rockburst proneness evaluation based on interpretation of drilling parameters

Rockburst is one of the common geological disasters in underground engineering. Rockburst proneness evaluation is the premise of rockburst disaster prevention and control. It is an effective method to evaluate rockburst proneness by brittleness index. The traditional brittleness index testing requires coring the surrounding rock in the field and transporting it to the laboratory for testing. The testing process is inefficient and disconnected from the in-situ environment. The effective in-situ and accurate test of brittleness index has become a challenge. Digital drilling testing of rock mass is a new approach to solve the above problems and future research direction. The study explore a rockburst proneness evaluation method based on the interpretation of real-time drilling parameters. The key of this method is to establish the quantitative relationship model between the brittleness index and drilling parameters. Digital drilling tests on different rock types were conducted using the rock intelligent rotary cutting testing system (RCT system). The quantitative relationship between drilling parameters and rock strength parameters was analyzed. The drilling test model of rock equivalent brittleness index (DP-EBI model) is established. The verification test results show that the difference rate between the rock brittleness index with drilling test and indoor test is 11.8%. On this basis, the testing results of five rockburst evaluation methods, including equivalent brittleness index EBI, energy impact index ACF, potential energy of elastic strain PES, brittleness index modified BIM and dynamic failure time DT were compared. The effectiveness of using drilling parameters to evaluate rockburst proneness is verified. This study can provide a theoretical and methodological basis for the in-situ detection and evaluation of rockburst proneness and grade in underground engineering fields, such as mine roadways, transportation tunnels, and hydraulic tunnels.

Generalized Weighted Mahalanobis Distance Improved VIKOR Model for Rockburst Classification Evaluation

Rockbursts are hazardous phenomena of sudden and violent rock failure in deep underground excavations under high geostress conditions, which poses a serious threat to geotechnical engineering. The occurrence of rockbursts is influenced by a combination of factors. Therefore, it is necessary to find an efficient method to assess rockburst grades. In this paper, we propose a novel method that enhances the VIKOR method using a novel combination of weight and generalized weighted Mahalanobis distance. The combination weights of the evaluation indicators were calculated using game theory by combining subjective experience and objective data statistical characteristics. By introducing the generalized weighted Mahalanobis distance, the VIKOR method is improved to address the issues of inconsistent dimensions, different importance, and inconsistent correlation among indicators. The proposed method can deal with the complexity of the impact factors of rockburst evaluation and classify the rockburst intensity level. The results show that the accuracy of the improved VIKOR method with the distance formula is higher than that of the unimproved VIKOR method; the evaluation accuracy of the improved VIKOR method with the generalized weighted Mahalanobis distance is 91.67%, which outperforms the improved VIKOR methods with the Euclidean and Canberra distances. This assessment method can be easily implemented and does not depend on the discussion of the rockburst occurrence mechanism, making it widely applicable for engineering rockburst evaluation.

Research and Application of Rock Burst Hazard Assessment of the Working Face Based on the CF-TOPSIS Method

Coal mining activities have intensified, and underground mining depths have increased, posing significant challenges for mitigating rock burst hazard. To address this issue, this paper proposes an improved comprehensive weighting prediction (CF-TOPSIS) method that predicts weight and grade indices for rock burst evaluation. The study introduces a novel variable coefficient method to optimize the conflict response problem and employs correlation forward and other techniques to minimize errors caused by large data differences. Based on these, the CRITIC objective weight algorithm model is established, and FAHP is used to optimize weighting factors to make the index weight of rock burst more reasonable, thus enhancing the accuracy of hazard assessment for working faces. Results from engineering examples show that the prediction results combined with field drill cutting methods and microseismic monitoring data verify the accuracy of the proposed method, indicating its feasibility and effectiveness in predicting rock burst hazard in underground coal mines.

Prediction of Grade Classification of Rock Burst Based on PCA-SSA-PNN Architecture

The uncertainty and complexity of rock burst brings great difficulties to the prediction of rock burst grades. In order to estimate the risk grades of rock burst, an integrated method combining principal component analysis (PCA) and sparrow search algorithm (SSA) with probabilistic neural network (PNN) was proposed. Considering that the in situ stress of rock mass, the strength of rock, and the strength of rock mass are the key influencing factors of rock bursts, the maximum in situ stress σ max , maximum tangential stress σ θ , rock strength σ ci , rock mass strength σ cm , and three rock burst evaluation indexes ( σ θ / σ ci , σ ci / σ max , and σ cm / σ max ) were selected to constitute the rock burst grade evaluation index system. Forty-three groups of rock burst engineering data were gathered. After preprocessing the rock burst data using PCA, four of the new linearly independent indexes PCA1, PCA2, PCA3, and PCA4 were obtained for estimating rock burst grades. The SSA was utilized to optimize the smoothing factor in the PNN. Using PCA-SSA-PNN-based architecture, a new multi-index rock burst grade prediction method was proposed. The results from the new multi-index rock burst grade prediction method were compared with those from single- and multi-index prediction methods. It shows that the predictions from the multi-index rock burst prediction methods are closer to the actual rock burst grades than that from the single-index rock burst prediction methods; compared with other multi-index rock burst prediction methods, the prediction accuracy of PCA-SSA-PNN is greater (up to 90%) and more available in the prediction of rock burst grades. The results presented herein may provide reference for the rock burst warning.

Evaluation of rockburst risk in deep tunnels considering structural planes based on energy dissipation rate criterion and numerical simulation

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.

Rockburst tendency prediction based on an integrating method of combination weighting and matter-element extension theory: A case study in the Bayu Tunnel of the Sichuan-Tibet Railway

The Bayu Tunnel is the most problematic tunnel project in the Lhasa-Nyingchi section of the Sichuan-Tibet Railway. Rockbursts have occurred frequently during the construction process, which has seriously threatened the safety of construction workers and equipment. Aiming at the rockburst hazard prediction problem of the Bayu Tunnel, in this paper an integrating method of combination weighting and matter-element extension theory is proposed. This method introduces the rock brittleness evaluation index BICSS, Russenes criterion and rock mass integrity coefficient as the main rockburst evaluation indexes, which characterized the control factors of rock physical and mechanical property, surrounding rock stress and rock mass integrity on rockburst tendency, respectively. Then the rockburst tendency evaluation index system is constructed. The weight of each rockburst control factor is determined by the combination weighting algorithm of triangular fuzzy number analytic hierarchy process (TFN-AHP), criteria importance though intercriteria correlation (CRITIC), and determination of comprehensive weight (MDI). The correlation degree between the rockburst sample and rockburst grade can be calculated using the matter-element extension theory, after which the prediction of rockburst grade is carried out. Finally, the applicability, superiority and the necessity of selected rockburst control factors in this method are verified and discussed further. The research results provide a new analysis method and technical means for rockburst tendency assessment of deep tunnel.

Static creep rockburst mechanism and CT inversion verification of deep thick coal seam roadways

AbstractCompared with the traditional “dynamic‐static” load rockburst induced by working face mining, a new typical disaster with concealment characteristics has appeared in deep thick coal seam roadways, namely, static creep rockburst, the occurrence mechanism of which remains unclear. Through the method of combining theory with practice, this paper elucidated the mechanical mechanism of static creep rockburst of deep thick coal seam roadways, along with the CT inversion of its rockburst risk. Next, by establishing the creep model and three‐dimensional creep formula under static conditions, it was observed that the main conditions for the unstable creep of deep thick coal seam roadway were high stress and thick coal seam. In addition, by analyzing the unstable creep failure process of surrounding rock in static roadways, it was found that the weakening of surrounding rock strength and stress relief were the reasons for starting rockburst and reducing impedance. The mechanical conditions of creep rockburst caused by stress superposition in weak areas of the roadway under static conditions were proposed, and the criterion of rockburst possibility was given. Finally, according to the characteristics of spontaneity and time delay of such a rockburst disaster, the static creep rockburst evaluation of thick coal seam roadway before mining was achieved by CT inversion, and the research conclusions were thoroughly verified.

Rock Burst Evaluation Using the CRITIC Algorithm-Based Cloud Model

Under high-stress conditions, rock burst disasters can significantly impact underground civil engineering construction. For underground metal mines, rock burst evaluations and prevention during mining have become major research topics, and the prediction and prevention of rock burst must be based on the study of rocks and rock burst tendencies. To further prevent the risk of geological disasters and provide timely warnings, a finite-interval cloud model based on the CRITIC algorithm is proposed in this paper to address the uncertainty of rock burst evaluation, the complexity under multi-factor interactions, and the correlations between factors, and it then realizes a preliminary qualitative judgment of rock burst disasters. This paper selects the uniaxial compressive strength σc (I1), ratio of the uniaxial compressive strength to the tensile strength σc/σt (brittleness coefficient, I2), elastic deformation energy index Wet (I3), ratio of the maximum tangential stress to the uniaxial compressive strength σθ /σc (stress coefficient, I4) of the rock, depth of the roadway H (I5), and integrity coefficient of the rock mass Kv (I6) as indicators for rock burst propensity predictions. The CRITIC algorithm is used to consider the relationships between the evaluation indicators, and it is combined with an improved cloud model to verify 20 groups of learning samples. The calculation results obtained by the prediction method are basically consistent with the actual situation. The validity of the model is tested, and then the model is applied to the Dongguashan Copper Mine in Tongling, Anhui Province, China, for rock burst evaluation.

Development of a semi-quantitative risk matrix for strain-burst hazard assessment – A numerical modelling approach in the absence of micro-seismic data

Existing rockburst evaluation techniques are empirical in nature which limit their use to situations where seismic monitoring data is available. The proposed technique outlined herein is intended to be most useful to consider the risk of strain-burst events when seismic data is not available, e.g. during pre-feasibility or feasibility stage studies. As development progresses and seismic data is gathered, the proposed method provides an additional level of detail to confirm/inform the empirical seismic risk assessment techniques. Using the proposed numerical approach, the risk of strain-bursting can be considered for different excavation scenarios in order to choose an optimum solution prior to significant capital expenditure. This consideration of strain-burst events is implemented through a risk assessment matrix that has been developed based on the likelihood of the seismic mechanism manifesting as well as its potential consequence. Four indices have been defined that include 1) Pre-failure Damage Index ID, correlated to the hardening behaviour assessing the rate of damage within the rock mass prior to peak strength; 2) Energy Release Index IE, correlated to a brittleness index characterising in-situ conditions leading to failure; 3) Frequency Index IF, correlated to the size of damaged area indicating the potential re-occurrence of the event; and 4) Vulnerability Index IV, correlated to the damage size and location identifying vulnerability of the personnel exposed to the hazard. Each of these indices, when multiplied provides a risk ranking. A case study example is provided to demonstrate the determination of input parameters from a numerical model and the risk outcome. From the calculated risk, measures may be implemented and/or the effectiveness of alternative designs can be examined.

Rockburst Monitoring in Deep Coalmines with Protective Coal Panels Using Integrated Microseismic and Computed Tomography Methods

In deep coalmines, longwall panels are subject to high static initial geostress andhigh dynamic stress caused by mining and tunnelling activities. Under the action of high static and dynamic stress, rockburst hazards are very likely to occur. To reduce rockburst risks, protective panels are commonly applied in deep coalmines. However, stress concentration in the protective coal panel often causes rockburst hazards in the gateway of the next longwall panel pending mining. To reduce such type of rockburst, this study firstly proposes a mathematic model to analyse the overall static stress distribution in the protective panel based on the mining practice in Longyun coalmine, Shandong Province, China. To evaluate the stress concentration caused by geological defects in the protective panel, a new rockburst evaluation index is proposed based on the computed tomography (CT) method. Finally, the extent of dynamic stress evolution caused by different working face advancing velocities is determined by microseismic monitoring. Results show that the areas with higher rockburst evaluation indexes are highly associated with the areas with large-energy microseismic events, indicating that the static stress concentration can be accurately identified by the CT method. A medium advancing velocity (4.0 m/s) is recommend during mining the longwall panel, which can ensure mining safety and improve mining productivity simultaneously. The integrated microseismic and CT monitoring methods can be used in other underground projects to guarantee construction safety and productivity.

In Deep Mining Working Face Rock Burst Evaluation by Multifactor Coupling Method

The impact of the rock burst to the deep mining working face has been a serious problem for a long time. According to the geological structure and actual production situation in 3201 working face, this paper used the method of multifactor coupling to divide the latent dangerous area and the dangerous level affected by mining and determine the level of rock burst danger. The results of the study show that the red beds will be disturbed during the process of mining, and the red beds may be fractured in the overlying strata of the coal seam, which may lead to the rock burst. The 3201 working faces were affected by the fault FX2, fault F2-2 and the main roof which was fractured, and the 3201working faces were evaluated by the method of multifactor coupling. The conclusion that comes to is the dangerous area at the distance 180 - 250 m to the open-off cut at the process of mining. Through the practice in 3201 working faces, this paper used the technology of micro-seismic monitoring to verify the scientific and practical of the division of the dangerous area and the dangerous level. The study is helpful to the improvement of the accuracy of the forecasting to the rock burst, and finally to realize the safe mining in 3201 working face.

Evaluation of rockburst occurrence and intensity in underground structures using decision tree approach

Based on reported statistics, rockburst phenomenon is the main cause of many casualties and accidents occurred during the construction of deep underground structures. Therefore, its prediction in initial stages of design has a remarkable role on enhancement of safety. In this paper, two models have been developed for rockburst evaluation using the C5.0 decision tree classifier. The first model has been applied for prediction of rockburst occurrence and the second model for prediction of rockburst intensity. These models have been developed based on a database including 174 rockburst case histories. In both models, stress coefficient, rock brittleness coefficient, and the elastic strain energy index are the predictive variables. These models are easy to use and do not require extensive knowledge. Based on decision rules derived from these models, the rockburst occurrence and intensity can be evaluated easily. The results revealed that the proposed approach is a useful and robust technique for long-term prediction of rockburst.

Evaluation of rock burst intensity based on annular grey target decision-making model with variable weight

Rock burst is a dynamic and complex phenomenon caused by numerous factors in underground excavating. It is very difficult to make evaluations accurately, especially under incomplete information. In this paper, a methodology for rock burst intensity evaluation is proposed based on grey target decision-making theory and variable weight synthesis thought. Some main factors that influence rock burst intensity are systematically analyzed to establish the evaluation index system. A balance function is introduced to investigate the variability of attribute weight, and then the weights of contribution factors are determined by utilizing variable weight synthesis, in conjunction with grey entropy algorithm. With respect to incomplete information in reality, the annular grey target theory is first proposed to address risk level of rock burst. Different distribution sets of bull’s eye distance are constructed to quantitatively represent corresponding intensity degree. Eventually, the application and performance comparison are carried out to demonstrate the feasibility and precision of the proposed model. It is demonstrated that the outcomes of the proposed model completely coincide with actual states. Compared with rough set theory and Russenes criterion, the proposed model can efficiently reduce decision ambiguity and produce a distinct risk measurement. It provides a new resolution for the research of rock burst evaluation under limited data.

Prediction of rock burst in underground caverns based on rough set and extensible comprehensive evaluation

In high terrestrial stress regions, rock burst is a major geological disaster influencing underground engineering construction significantly. How to carry out efficient and accurate rock burst prediction is still not resolved. In this paper, a new rock burst evaluation method based on rough set theory and extension theory is proposed. In the method the following seven indexes were selected as indices to evaluate and predict rock bursts: uniaxial compressive strength, ratio of rock strength to in situ stress, ratio of rock compressive strength to tensile strength, ratio of tangential stress and rock compressive strength, elastic strain energy index, depth of tunnel, and rock integrity. According to rough set theory, those indexes influencing rock bursts were investigated through attribute reduction operation to obtain four main influential indexes and the weight coefficients of each evaluation index were acquired by analysing the significance of conditional attribute. Thereafter, the main influential indexes and its weight were taken into the extension theory to predict the practical engineering. This method was applied to a practical case, underground caverns of Jiangbian hydropower station in China’s Sichuan province. It is proved that the evaluation results of the method were well consistent with real conditions.

Microseismic low-frequency precursor effect of bursting failure of coal and rock

Abstract As a tough problem in coal mines, there is not an effective solution to rockburst evaluation and prediction as yet. In this paper, an attempt to investigate a rockburst forecasting method was undertaken by applying small scale, laboratory modeling of the coal mine roof, coal and its floor. According to rockburst danger evaluation and forecasting in deep coal mines on the basis of microseismic (MS) monitoring, the frequency-spectrum evolution was analyzed in detail by the band-stop filter and Fourier transform of MS signals monitored in time. Research results show that a strong mainshock induced by coal and rock sample bursting failure would commonly be introduced when the predominant frequency-spectrum of MS signals begins to move to lower band and the vibration velocity gradually increases, and the signals closed to mainshock, precursor signals, which indicate the tendency of increasing low-amplitude and the decreasing high-frequency. Moreover, it is also found that the rockburst disaster intensity increases with the increase of vibration velocity of precursor signal, and it is opposite with the predominant frequency of precursor signal.

An Improved Comprehensive Index Method for the Evaluation of Rock Burst Risk in Mining

There are uncertainties such as randomicity, vagueness, gray, unsureness in the factors of comprehensive evaluation of rock burst risks due to the complexity of the geological conditions and deficiency of experimental data. In this paper, we apply the mathematic theory of blind information to the comprehensive index method for the assessment of rock burst risks, use blind data to express the uncertainty of the risk index, and put forward blind data form of the comprehensive index. Meanwhile, by use of blind data algorithms, we compute the reliability value in different numerical value intervals of comprehensive index, which consequently provide more comprehensive evidence to judge the rock burst risk levels and overcome the problem of absolutization in traditional methods. The case analysis indicates that the apply for blind data in rock burst evaluation can consider influential factors better and obtain more reliable results. In conclusion, it is a new way of evaluating the rock burst more comprehensively and scientifically.