Rockburst Risk Research Articles

Theoretical study and application of energy extreme value discrimination method of softening zone for bursting hazard.

Considering the current situation that it's difficult to quantify the discrimination of rockburst hazard, an analytical solution for the softening zone energy of surrounding rock under rockburst in a circular roadway is obtained theoretically based on the elastoplastic softening model of a circular roadway. The critical softening zone energy, critical softening zone radius, critical roadway shrinkage displacement, and critical roadway shrinkage rate are determined. An energy extreme value discrimination method of softening zone for bursting hazard is proposed. The critical softening zone energy is taken as the evaluation basis of the bursting liability of the coal seam where the roadway (a full coal roadway) is located. The uniform energy index, which is the ratio of the external disturbance energy of the surrounding rock softening zone to the critical softening zone energy, is used as the evaluation basis for bursting hazards. Theoretical analysis shows that the smaller the critical softening zone energy of the roadway surrounding rock is, the stronger the bursting liability of the coal seam is, and the greater the uniform bursting hazard index is, the stronger the bursting hazard of the roadway. Subsequently, based on the critical softening zone energy and the uniform energy index, a classification standard of bursting liability and an evaluation method of bursting hazard are proposed. The reliability of the softening zone energy extremum criterion, the bursting liability classification standard, and the bursting hazard evaluation method was verified through indoor and field tests. The energy extreme value discrimination method of softening zone for bursting hazard considers the internal and external factors of roadway rockburst comprehensively and can judge the rockburst risk through field real-time observation, which is a more scientific and reasonable method to predict the risk of roadway rockburst. The research work has important theoretical guiding significance for the prevention and control of roadway rockbursts.

Predicting Rock Bursts in Rock Mass Blocks Using Acoustic Emission

Geophysical methods for local rock burst prediction are currently being developed along two lines: improving recording equipment and improving data processing methods. Progress in developing processing methods is constrained by the lack of informative prognostic models that describe the condition of rock mass, the process of rock mass fracturing, and the phenomena that can substantiate the choice of both criteria and test parameters of the condition of rock mass and give an estimate of the time remaining until rock pressure manifestation. In particular, despite achievements in hardware design, researchers using the seismo-acoustic method to predict rock bursts measure the acoustical activity or energy capacity of elastic wave scattering after a man-made explosion and are faced with the dependence of forecast results on destabilizing factors. To solve this problem, we applied an information and kinetic approach to forecasting. In this article, we discuss the principles of selecting test parameters that are resistant to destabilizing factors. We propose a micromechanical model of fracture accumulation in a rock mass block that reflects the dependence of acoustic emission (AE) parameters on time, which makes it possible to detect the influence of various factors on forecast data and filter the signals. We also propose criteria and a methodology for rock burst risk assessment. The results were tested in analyzing the seismo-acoustic phenomena caused by man-made explosions at the Taimyrsky and Oktyabrsky mines in Norilsk. The article gives examples of using the proposed criteria. The effectiveness of their application is compared with traditional methods for assessing rock burst risks and evaluating the stress–strain parameters of rock mass in terms of their being informative, stable, and representative by means of statistical processing of experimental data.

Mechanism Study and Tendency Judgement of Rockburst in Deep-Buried Underground Engineering

Rockburst is a type of dynamic instability failure phenomenon and frequently brings huge losses to underground engineering projects such as mines and tunnels. In order to explore rockburst mechanisms and predict rockbursts better, relying on the background of Wulaofeng deep-buried highway tunnel, in situ stress measurement was performed using new wireless devices, and mechanics tests of surrounding rock samples taken from different burial depths were carried out. The rockburst mechanism was explored from the microscopic perspective based on the analysis of scanning electron microscopy (SEM). Rockburst tendency was judged comprehensively by a tendency analysis, grade prediction and numerical simulation. The result showed that the mechanical parameters of granite rocks in the deep-buried section were larger than those in the entrance section, and the fractured morphology mainly comprised sheet and monolithic block, corresponding to transgranular fracture and intergranular fracture. Rocks with few types of mineral cementation, good crystallization and small particle size differences had better energy storage and release characteristics. There was little difference in the rockburst tendency of rocks with different buried depths, but there were obvious differences in the rockburst grade. In the deep-buried section of the tunnel, the rockburst grade was of a moderate–heavy level and the rockburst risk at the vault and right spandrel of the cross section was more severe, which was basically consistent with the situation at the tunnel site. This study can provide a theoretical basis for the prevention and control of rockbursts in Wulaofeng tunnel and other similar engineering projects.

Mechanism and Safety Mining Technology of Overall Instability-Induced Rockbursts of Multi-Coal Seam Spatially Isolated Working Face

The isolated working face has always been the hardest hit area for the occurrence of rockburst, and the spatially isolated working face with multiple coal seams is often easily overlooked due to its hidden nature, which leads to the occurrence of rockburst accidents. This paper takes the Liuhuanggou coal mine (9–15) 08 isolated working face as the engineering background, used field research, theoretical analysis, numerical simulation, and field monitoring, investigated the coal body stress evolution law during mining, and revealed the overall instability rockburst mechanism of the working face and deduced the limit advance distance when the working face was in a state of boundary instability. The research results show the following: (1) with the increase of advancement, the overlying strata on the working face are dynamically transformed from the “C” spatial structure with hollowing on both sides to the “θ” spatial structure with coal body support in the middle; (2) when the dynamic load stress on the coal body of the working face exceeds 1.5 times its integrated compressive strength, there is a risk of overall instability rockburst; (3) when the working face advances to 430 m from the open cutting, the superimposed stress on the coal body exceeds its comprehensive compressive strength and reaches a critical instability state, which is verified by numerical simulation. Based on the analysis of the mechanics and mechanism of the overall instability rockburst of the working face, this paper proposes a set of targeted safe mining solutions: (1) The joint monitoring system of microseism-stress-drilling cutting is adopted to monitor and warn the dangerous rockburst areas. (2) The “rockburst-gas” drilling technique is used to unload the pressure on both sides of the working face and the coal wall. (3) The mining speed shall not exceed 3.2 m/d when the working face is mined before 350 m, and shall not exceed 2.4 m/d when the working face enters the influence area of mined-out LW(4-5)02 (350∼550 m). The microseismic monitoring results and field practice confirmed the reasonableness and effectiveness of the safe mining technology plan.

Bagged Ensemble of Gaussian Process Classifiers for Assessing Rockburst Damage Potential with an Imbalanced Dataset

The evaluation of rockburst damage potential plays a significant role in managing rockburst risk and guaranteeing the safety of personnel. However, it is still a challenging problem because of its complex mechanisms and numerous influencing factors. In this study, a bagged ensemble of Gaussian process classifiers (GPCs) is proposed to assess rockburst damage potential with an imbalanced dataset. First, a rockburst dataset including seven indicators and four levels is collected. To address classification problems with an imbalanced dataset, a novel model that integrates the under-sampling technique, Gaussian process classifier (GPC) and bagging method is constructed. Afterwards, the comprehensive performance of the proposed model is evaluated using the values of accuracy, precision, recall, and F1. Finally, the methodology is applied to assess rockburst damage potential in the Perseverance nickel mine. Results show that the performance of the proposed bagged ensemble of GPCs is acceptable, and the integration of data preprocessing, under-sampling technique, GPC, and bagging method can improve the model performance. The proposed methodology can provide an effective reference for the risk management of rockburst.

Continuous three-dimensional stress monitoring in roof of coal mines for investigating the rockburst control effect with hydraulic fracturing

The occurrence of rockburst in coal mines is closely related to the stress in coal and rock mass. Through hydraulic fracturing measurements in roof, the three-dimensional stress in roof before and after hydraulic fracturing as well as during working face advancing was monitored, and the effect of hydraulic fracturing in roof on controlling rockburst was studied. The test results show that (1) after hydraulic fracturing, the three principal stresses in roof decreased remarkably, whose maximum reduction was about 20%, while the elastic strain energy in roof decreased by about 31% as well; (2) as the working face advanced, the three principal stresses in roof in front of the working face would increase continuously until reaching peaks and induce the strata fracture, and the variation of the elastic strain energy in roof was basically consistent with that of the magnitude of the stress; (3) with hydraulic fracturing, the position of the peak stress moved from 11 to 21 m in front of the working face, the peaks of the three principal stresses decreased, whose maximum reduction was about 32%, and the peak of the elastic strain energy in roof also significantly decreased by about 51%. The field investigation shows that hydraulic fracturing in roof can release the stress and elastic strain energy in coal and rock mass instantaneously, and will reduce the risk of rockburst; hydraulic fracturing in roof can be an effective pre-destressing method to reduce the stress and energy concentration in coal and rock mass during mining, and will prevent the risk of rockburst.

Optimization of Anti-Impact Energy Absorption Structure of Hydraulic Support

Rock bursts are a frequent occurrence in deep coal mining, and reducing the risk of rock bursts is necessary for the safe and efficient mining of coal. As honeycomb structures have good impact resistance, the design suggests that a honeycomb structure is adopted in the roof. A mechanical model of the hydraulic support is established, and the influence of geometric parameters on the impact resistance of the honeycomb structure is studied. Finally, the orthogonal test method was used to analyze the influence and weight of the geometric parameters on the anti-impact performance of the honeycomb structure with hydraulic leg stress and roof displacement as the evaluation indexes. This paper provides a new design idea for the research and development of an impact resistance hydraulic support in the underground coal mine, which is significant in ensuring coal mine safety.

Research on Rockburst Risk Level Prediction Method Based on LightGBM−TCN−RF

Rockburst hazards pose a severe threat to mine safety. To accurately predict the risk level of rockburst, a LightGBM−TCN−RF prediction model is proposed in this paper. The correlation coefficient heat map combined with the LightGBM feature selection algorithm is used to screen the rockburst characteristic variables and establish rockburst predicted characteristic variables. Then, the TCN prediction model with a better prediction performance is selected to predict the rockburst characteristic variables at time t + 1. The RF classification model of rockburst risk level with a better classification effect is used to classify the risk level of rockburst characteristic variables at time t + 1. The comparison experiments show that the rockburst characteristic variables after screening allow a more accurate prediction. The overall RMSE and MAE of the TCN prediction model are 0.124 and 0.079, which are better than those of RNN, LSTM, and GRU by about 0.1–2.5%. The accuracy of the RF classification model for the rockburst risk level is 96.17%, which is about 20% higher than that of KNN and SVM, and the model accuracy is improved by 1.62% after parameter tuning by the PSO algorithm. The experimental results show that the LightGBM−TCN−RF model can better classify and predict rockburst risk levels at future moments, which has a certain reference value for rockburst monitoring and early warning.

Precursor of microseismic energy and stress evolution induced by rockburst in coal mining: a case study from Xiashijie, Shannxi, China

Rockburst has become one of the most frequent dynamic disasters in coal mines when mining activities proceed towards greater depths. The goaf near the working face is the dominant factor, resulting in a high risk of rockburst and seriously threatening the safe production of coal mines. In this paper, to systematically analyze the stress and energy evolution of surrounding rock in the stope and reveal the rockburst precursory characteristics of the working face adjacent to the goaf, the microseismic (MS) monitoring technique and numerical simulation method were utilized based on the case of the Xiashijie Coal Mine in Shaanxi Province, China. The results indicated that the presence of the nearby goaf could lead to a dense high-energy event distribution in the overlying rocks owing to the fracturing of the hard main roof, which is closely related to periodic weighting and could be manifested as a periodic trend. Based on the source parameters of the energy index (EI) and cumulative apparent volume (CAV), lgCAV/lgEI could effectively evaluate the risk of rockburst and exhibits the advantages of convenience and thresholding. The risk of rockburst tended to increase with increasing lgCAV/lgEI. In particular, rockburst was prone to occur when lgCAV/lgEI exceeds 10. The distribution of the elastic strain energy derived via numerical simulation agrees well with that of the microseismic energy density measured via MS monitoring. The simulation results further indicated that when rockburst occurs, the average maximum principal stress in the main roof of the working face sharply dropped, while the average maximum principal strain significantly increased. Affected by the adjacent goaf, the advanced abutment stress of the roof and floor of the working face was distributed asymmetrically, with the characteristics of high stress concentration close to the goaf. Therefore, under dynamic disturbance due to notable energy release in the hard main roof, rockburst easily induced.

Experimental investigation of mechanical properties, impact tendency, and brittleness characteristics of coal mass under different gas adsorption pressures

Understanding the mechanical properties of coal after gas and coal interaction can better guide the mining technology of gas-bearing coal seams and drainage technology of coalbed methane. In this study, triaxial compression tests of coal mass under different gas adsorption pressures are carried out to evaluate the mechanical properties, impact tendency, and brittleness of coal with different gas adsorption pressures. Results show that due to the adsorption of gas, the mechanical parameters, such as elastic modulus and strength of coal are significantly decreased. In addition to the effect of fluid pressure, the decrease of elastic energy absorbed by coal, the increase of ductile deformation and the change of molecular structure of coal particles caused by gas adsorption also significantly affect the mechanical properties of coal. The influence of gas adsorption pressure on energy input becomes gradually evident when the coal enters the stage of plastic deformation and yield failure. Then the deformation and stress bearing capacity of coal are affected, and the energy accumulation and dissipation process of coal are further affected. The gas adsorption pressure generally develops the energy absorption density and elastic energy density of three characteristic points (initial damage point, volume expansion point and peak stress point), but reduces the dissipation energy density of these points. Gas adsorption reduces the storage of deformation energy of coal, strengthens the energy dissipation, and develops the plastic failure characteristics of coal. It is not prone to appear sudden brittle failure in coal mass. Although high pressure reduces the risk of rock burst, it increases the risk of gas outburst. The chemical effects of pore/fracture fluid caused by the combined action of adsorbed and free gas lead to the further decline in coal brittleness, thus changing the deformation and failure mode of coal.

Precursor Information Recognition of Rockburst in the Coal-Rock Mass of Meizoseismal Area Based on Multiplex Microseismic Information Fusion and Its Application: A Case Study of Wudong Coal Mine

Abstract In recent years, the rockburst induced by steeply inclined coal seam mining in the Urumqi mining area has become serious. In this paper, the evolution law of multiplex microseismic information before and after the rockburst is obtained through in-depth mining of the field microseismic data. In addition, the evolution characteristics of microseismic activities before and after the rockburst of steeply inclined coal-rock mass in the meizoseismal area are revealed from three important scales: time, space, and strength. The results show the following: (1) The microseismic activity of the Wudong Coal Mine is mainly of stress migration type. The sandwiched rock pillar is the primary inducement of rockburst, and the b value decreases greatly with the mining progresses (by 23.9%). It indicates that the risk of rockburst induced by the local failure of rock mass in this area is increasing. (2) From the time scale and strength index, the precursory indexes of rockburst are put forward, respectively: ① the daily total energy and the frequency of microseisms suddenly rise and fall rapidly at the same time in the shock start-up period (5 days before rockburst), and the daily total energy of microseisms decreases to the abnormal valley value within 30 days. ② The abnormal growth rate of microseismic events exceeded 60% in a certain stage, and “induced shock events” appeared. (3) The shock risk is positively correlated with the decline rate of energy index, the growth rate of cumulative apparent volume, and Schmidt. It is determined that the rockburst will occur within 19 days after entering the shock early warning period. The results of prediction examples show that this method has a good prediction effect on rockburst in strong meizoseismal areas, which can provide a reference for rockburst prevention in the mining process in strong meizoseismal areas.

Research on Temporal and Spatial Distribution Characteristics of Microseismic Events of Slip-Type Rockburst

Based on the microseismic monitoring data of underground cavern of Shuangjiangkou Hydropower Station, the internal relationship between rockburst and microseismic events is analyzed and the occurrence mechanism of slip-type rockburst in underground cavern of Shuangjiangkou Hydropower Station is analyzed through the change of microseismic monitoring b value to warn the risk level of rockburst. The results show that microseismic events are closely related to excavation activities, and the change of b value reflects the rockburst risk level. The smaller the b value of microseismic events is, the more large magnitude events is and the greater the possibility of rockburst is. The slip-type rockburst was mainly affected by structural plane; it is due to the accumulation of elastic strain energy at the structural plane and the sudden release under the action of unloading or disturbance, driving the block on the structure surface fast slide, mainly manifested as the sliding of large blocks of surrounding rock, and forming a “V” shape pit blasting or cuneate blasting crater, as well as destruction with crackle. Compared with the strained rockburst, the damage is more serious. The research results can provide reference for rockburst prediction and prevention in similar deep rock engineering.

Rock burst mechanism induced by stress anomaly in roof thickness variation zone: a case study

The variation of hard roof thickness is an essential contributor in triggering rock bursts during longwall mining. Case analysis and numerical modeling were used to study the stress and energy characteristics of the coal and rock mass and its fracture behaviour in the roof thickness variation zone (RTVZ). The results show that the coal seam has higher initial stress if overlain by a thicker hard roof, whose stress monitoring value is 1.8–2.6 times that of the thin zone. The increasing variation in the roof thickness or the roof properties causes a greater initial stress change in the coal seam. In the thick roof zones, the superposition of the advanced abutment pressure and the increased initial stress will result in a high-stress concentration area, where the stress mutation coefficient value can be up to 1.08–1.15. A higher rock burst risk might thus present in the roadway near the longwall in the thick roof zone, where more intensive elastic energy was released in the coal/rock mass. Also, it is more likely to have a significant dynamic load in the thin roof zone due to the higher possibility of roof breakage, and the total microseismic energy can reach 1.8–3.2E + 08J. Highlights Case analysis and numerical modelling were used to study the formation mechanism of stress anomaly in coal seams, energy evolution characteristics of the coal/rock mass and its fracture behaviour in the RTVZ. The mechanism of rock bursts induced by coal mining in the RTVZ is determined. The thick roof zone has high-stress concentration, where more intensive elastic energy is released in the coal/rock mass. Due to easier roof breakage, it is more likely to have a significant dynamic load in the thin roof zone. The prevention and control method of rock bursts in the RTVZ is put forward. The rock bursts can be relieved by reducing the initial stress increased in the thick roof zone. Strengthening roadway support can reduce the influence of dynamic load on the roadway.

An Effective Denoising Method Based on Cumulative Distribution Function Thresholding and its Application in the Microseismic Signal of a Metal Mine With High Sampling Rate (6 kHz)

Microseismic events can be used to analyze the risk of tunnel collapse, rock burst, and other mine hazards in space and time. In practice, the artificial activities and other signals at the mining site can seriously interfere with the microseismic waveforms, reducing the signal-to-noise ratio. In this study, we propose a denoising method based on the threshold of the cumulative distribution function (CDF) of the wavelet coefficients in the wavelet domain using synchrosqueezed continuous wavelet transform (SS-CWT). First, the ratio of microseismic signal variance between two adjacent time windows is used to determine the range of background noise. Then, the microseismic signal is transformed into a wavelet domain using SS-CWT, and the threshold of wavelet coefficients at each scale is estimated based on the cumulative distribution function (CDF) of background noise. At last, a post-processing step is applied by utilizing an amplitude smoothing function, to further suppress the noise. The proposed denoising method is tested by both synthetic and filed microseismic data recorded in a metal mine. The results show that the method is effective in denoising and can improve the SNR of mine microseismic data with a high sampling rate.

Risk Prediction of Rock Bursts and Large Deformations in YL Tunnel of the Chongqing–Kunming High-Speed Railway

The YL Tunnel of the Chongqing–Kunming high-speed railway project, a key project of the whole line, is a typical ultra-long deep tunnel facing geologic problems, such as rock bursts, large deformation, water inrush, and toxic or harmful gas leakage, among which high ground stress results in the most serious damage. This study incorporates existing studies and materials, as well as data on ground stress obtained through tests using the hydrofracturing technique. The areas with rock bursts and large deformations were divided accordingly, and preventive measures were expounded. The results showed that the areas predicted as high risk of severe rock burst were D1K338 + 945–D1K339 + 025 and D1K339 + 075–D1K339 + 220, which is of significance when constructing the whole Chongqing–Kunming high-speed railway and may even be instructive in railway construction in the southwest region of China.

Numerical and Machine learning modeling of hard rock failure induced by structural planes around deep tunnels

The Rockburst phenomenon is one of the hazards in deep underground mines and tunnels that can be exacerbated by faults or structural features. An accurate understanding of this phenomenon can control or reduce its destructive impacts. Using methods that can accurately estimate or predict this phenomenon is a critical issue for experts in the field. Since studying rockburst with the help of laboratory and numerical methods is a complex issue and, at the same time, requires high time and cost, in this paper, the machine learning method of extreme gradient boosting (XGBoost) was used for predicting this phenomenon. For this purpose, numerical modelling was used in the Abaqus software environment to generate 300 datasets. A fault around the modelled tunnel was considered to show the impact of faults on the phenomenon of rockburst in tunnels. The datasets included 13 effective input parameters on the rockburst phenomenon. Among the 300 datasets, 250 data were used for training and 50 data for the test. The comprehensive results indicated that the XGBoost model has the potential ability to estimate the rockburst phenomenon that may occur during deep tunnelling near fault zones. The results revealed that faults around deep tunnels could significantly increase the risk of rockburst if the fault is positioned and oriented in such a way that it promotes high stress. The MIT method revealed that, among the 13 input parameters considered in this study, fault length and density have the most and least impact on the rockburst phenomenon, respectively. Finally, to have good knowledge of the rockburst phenomenon in tunnelling projects, this article recommends using the XGBoost method to predict the rockburst in deep tunnels near the fault zones. The importance of the proposed model is that it can provide a reasonable estimate of the rockburst phenomenon in the deep tunnels, based on which geotechnical engineers can take the necessary measures to deal with it in the pre-construction designs.

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.

Numerical simulation method for the process of rockburst

Due to the large buried depth and active geological structure, dynamic disasters such as rockburst posed a severe threat to the Sichuan-Tibet railway tunnel's safety during construction. The prediction and prevention of rockburst has become a major research topic in the Sichuan-Tibet railway tunnel engineering community. Recent studies on rockburst propose numerous numerical simulation methods. These methods are based on static and quantitative calculations to make a qualitative assessment of the risk of rockburst. However, such methods cannot simulate and predict the rockburst process adequately. This research offered a novel numerical simulation method for the rockburst process. The method considered the main factors that affect the occurrence of rockburst, including the high geostress hard rock mechanics model, the rockburst discrimination index, underground excavation methods, and new boundary conditions during rockburst. The rationality of this method is verified by the calculation and analysis of different types of rockburst engineering cases. Compared to traditional rockburst prediction approaches, this method can quantitatively predict the time, location, and degree of damage caused by the rockburst, allowing for the rational selection of support parameters and timing in rockburst prevention.

Use of machine learning algorithms to assess the state of rockburst hazard in underground coal mine openings

The risk of rockbursts is one of the main threats in hard coal mines. Compared to other underground mines, the number of factors contributing to the rockburst at underground coal mines is much greater. Factors such as the coal seam tendency to rockbursts, the thickness of the coal seam, and the stress level in the seam have to be considered, but also the entire coal seam–surrounding rock system has to be evaluated when trying to predict the rockbursts. However, in hard coal mines, there are stroke or stress-stroke rockbursts in which the fracture of a thick layer of sandstone plays an essential role in predicting rockbursts. The occurrence of rockbursts in coal mines is complex, and their prediction is even more difficult than in other mines. In recent years, the interest in machine learning algorithms for solving complex nonlinear problems has increased, which also applies to geosciences. This study attempts to use machine learning algorithms, i.e. neural network, decision tree, random forest, gradient boosting, and extreme gradient boosting (XGB), to assess the rockburst hazard of an active hard coal mine in the Upper Silesian Coal Basin. The rock mass bursting tendency index W TG that describes the tendency of the seam–surrounding rock system to rockbursts and the anomaly of the vertical stress component were applied for this purpose. Especially, the decision tree and neural network models were proved to be effective in correctly distinguishing rockbursts from tremors, after which the excavation was not damaged. On average, these models correctly classified about 80% of the rockbursts in the testing datasets.

An Extended ORESTE Approach for Evaluating Rockburst Risk under Uncertain Environments

Rockburst is a severe geological disaster accompanied with the violent ejection of rock debris, which greatly threatens the safety of underground workers and equipment. This study aims to propose a novel multi-criteria decision-making (MCDM) approach for evaluating rockburst risk under uncertain environments. First, considering the heterogeneity of rock mass and complexity of geological environments, trapezoidal fuzzy numbers (TrFNs) are adopted to express initial indicator information. Thereafter, the superiority linguistic ratings of experts and a modified entropy weights model with TrFNs are used to calculate the subjective and objective weights, respectively. Then, comprehensive weights can be determined by integrating subjective and objective weights based on game theory. After that, the organísation, rangement et synthèse de données relarionnelles (ORESTE) approach is extended to obtain evaluation results in a trapezoidal fuzzy circumstance. Finally, the proposed approach is applied to assess rockburst risk in the Kaiyang phosphate mine. In addition, the evaluation results are compared with empirical methods and other trapezoidal fuzzy MCDM approaches. Results show that the proposed extended ORESTE approach is reliable for evaluating rockburst risk, and provides an effective reference for the design of prevention techniques.