Rock fragmentation is an important indicator for assessing the quality of blasting operations.However,accurate prediction of rock fragmentation after blasting is challenging due to the complicated blasting parameters ...Rock fragmentation is an important indicator for assessing the quality of blasting operations.However,accurate prediction of rock fragmentation after blasting is challenging due to the complicated blasting parameters and rock properties.For this reason,optimized by the Bayesian optimization algorithm(BOA),four hybrid machine learning models,including random forest,adaptive boosting,gradient boosting,and extremely randomized trees,were developed in this study.A total of 102 data sets with seven input parameters(spacing-to-burden ratio,hole depth-to-burden ratio,burden-to-hole diameter ratio,stemming length-to-burden ratio,powder factor,in situ block size,and elastic modulus)and one output parameter(rock fragment mean size,X_(50))were adopted to train and validate the predictive models.The root mean square error(RMSE),the mean absolute error(MAE),and the coefficient of determination(R^(2))were used as the evaluation metrics.The evaluation results demonstrated that the hybrid models showed superior performance than the standalone models.The hybrid model consisting of gradient boosting and BOA(GBoost-BOA)achieved the best prediction results compared with the other hybrid models,with the highest R^(2)value of 0.96 and the smallest values of RMSE and MAE of 0.03 and 0.02,respectively.Furthermore,sensitivity analysis was carried out to study the effects of input variables on rock fragmentation.In situ block size(XB),elastic modulus(E),and stemming length-to-burden ratio(T/B)were set as the main influencing factors.The proposed hybrid model provided a reliable prediction result and thus could be considered an alternative approach for rock fragment prediction in mining engineering.展开更多
Percussion drilling is a promising approach for hot dry rock(HDR)fragmentation.However,understanding of HDR fragmentation mechanism under multi-dimensional percussion remains limited and hinders the corresponding dril...Percussion drilling is a promising approach for hot dry rock(HDR)fragmentation.However,understanding of HDR fragmentation mechanism under multi-dimensional percussion remains limited and hinders the corresponding drilling performance.Herein,an innovative true triaxial multi-dimensional percussion device was developed for the study of HDR fragmentation mechanism under in-situ temperature and stress conditions.Multi-dimensional percussion,involving both axial and torsional components,was applied to drilling in granite and carbonatite rocks sampled from the typical HDR target areas.Multiscale visualization techniques and a whale optimization-variational mode decomposition algorithm were employed to investigate the rock failure patterns and drilling energy characteristics.Results indicated that multi-dimensional percussion enhances brittle-ductile mixed failure in granite,characterized by transgranular,intergranular,and combined fracture patterns that promote rock cracking.In contrast,carbonatite drillhole displays enhanced brittle fragmentation and tortuous failure surface dominated by transgranular fracture pattern.Frequency-domain characteristics of penetration force signals for multidimensional percussion,especially the significant dominant frequency,amplitude,and high-frequency dissipation,indicate an increase in net energy for drilling into HDR and intensified rock fragmentation.Further,the effect of impact frequency on rock fragmentation performance was emphasized to maximize drilling efficiency.The optimal regulation schemes between axial and torsional impact frequencies are identified as 15 Hz+15 Hz for granite and 30 Hz+15 Hz for carbonatite.The reliability of the optimization approach was validated through a field test that employed a novel impactor in the geothermal well Fushen-1.展开更多
Aiming at the problems of the traditional method of assessing distribution of particle size in bench blasting, a support vector machines （SVMs） regression methodology was used to predict the mean particle size （X50...Aiming at the problems of the traditional method of assessing distribution of particle size in bench blasting, a support vector machines （SVMs） regression methodology was used to predict the mean particle size （X50） resulting from rock blast fragmentation in various mines based on the statistical learning theory. The data base consisted of blast design parameters, explosive parameters, modulus of elasticity and in-situ block size. The seven input independent variables used for the SVMs model for the prediction of X50 of rock blast fragmentation were the ratio of bench height to drilled burden （H/B）, ratio of spacing to burden （S/B）, ratio of burden to hole diameter （B/D）, ratio of stemming to burden （T/B）, powder factor （Pf）, modulus of elasticity （E） and in-situ block size （XB）. After using the 90 sets of the measured data in various mines and rock formations in the world for training and testing, the model was applied to 12 another blast data for validation of the trained support vector regression （SVR） model. The prediction results of SVR were compared with those of artificial neural network （ANN）, multivariate regression analysis （MVRA） models, conventional Kuznetsov method and the measured X50 values. The proposed method shows promising results and the prediction accuracy of SVMs model is acceptable.展开更多
The blasting operation plays a pivotal role in the overall economics of opencast mines.The blasting subsystem affects all the other associated sub-systems,i.e.loading,transport,crushing and milling operations.Fragment...The blasting operation plays a pivotal role in the overall economics of opencast mines.The blasting subsystem affects all the other associated sub-systems,i.e.loading,transport,crushing and milling operations.Fragmentation control through effective blast design and its effect on productivity are the challenging tasks for practicing blasting engineer due to inadequate knowledge of actual explosive energy released in the borehole,varying initiation practice in blast design and its effect on explosive energy release characteristic.This paper describes the result of a systematic study on the impact of blast design parameters on rock fragmentation at three mines in India.The mines use draglines and shoveledumper combination for removal of overburden.Despite its pivotal role in controlling the overall economics of a mining operation,the expected blasting performance is often judged almost exclusively on the basis of poorly defined parameters such as powder factor and is often qualitative which results in very subjective assessment of blasting performance.Such an approach is very poor substitutes for accurate assessment of explosive and blasting performance.Ninety one blasts were conducted with varying blast designs and charging patterns,and their impacts on the rock fragmentation were documented.A high-speed camera was deployed to record the detonation sequences of the blasts.The efficiency of the loading machines was also correlated with the mean fragment size obtained from the fragmentation analyses.展开更多
This investigation aims to explore the effects of stress conditions and rock cutting rates on hard rock fragmentation through indentation tests on a newly designed triaxial testing apparatus.This apparatus was designe...This investigation aims to explore the effects of stress conditions and rock cutting rates on hard rock fragmentation through indentation tests on a newly designed triaxial testing apparatus.This apparatus was designed to realize a triaxial loading and indentation test of cylindrical specimens using inserted tooth cutter.The boreability and crushing efficiency of granite rock was investigated by analyzing the change rules of the thrusting force,penetration depth,characteristics of chippings and failure patterns.Several quantitative indexes were used to evaluate rock boreability in this investigation.The granite rock samples all had a chiselled pit and a crushed rock core.Under initial stress conditions,only flat-shape chippings were stripped from the rock surface when the thrusting force reached 20 kN.The rock cutting special energy had a close correlation with the initial stress conditions and inserted tooth shape.Moreover,a thrusting force prediction model was proposed in this paper.The contribution of this study is that for the first time the influence mechanism of the initial triaxial stress conditions on rock fragmentation is investigated using an inserted tooth and the newly designed testing apparatus.This study has a crucial importance for practical underground hard rock crushing in geoengineering.展开更多
High-voltage pulse discharge(HVPD)rock fragmentation controls a plasma channel forming inside the rock by adjusting the electrical parameters,electrode type,etc.In this work,an HVPD rock fragmentation test platform wa...High-voltage pulse discharge(HVPD)rock fragmentation controls a plasma channel forming inside the rock by adjusting the electrical parameters,electrode type,etc.In this work,an HVPD rock fragmentation test platform was built and the test waveforms were measured.Considering the effects of temperature,channel expansion and electromagnetic radiation,the impedance model of the plasma channel in the rock was established.The parameters and initial values of the model were determined by an iterative computational process.The model calculation results can reasonably characterize the development of the plasma channel in the rock and estimate the shock wave characteristics.Based on the plasma channel impedance model,the temporal and spatial distribution characteristics of the radial stress and tangential stress in the rock were calculated,and the rock fragmentation effect of the HVPD was analyzed.展开更多
The fragmentation test of granite subjected to strain rate of 10~010~2s~ -1 was carried out using split Hopkinson pressure bar(SHPB) whose diameter is 75 mm, where half-sine loading waveform was performed. The sieving...The fragmentation test of granite subjected to strain rate of 10~010~2s~ -1 was carried out using split Hopkinson pressure bar(SHPB) whose diameter is 75 mm, where half-sine loading waveform was performed. The sieving statistics results of the fragments show that the distribution of the fragments is a fractal, and the fractal dimension values fall into the range of 1.22.4. The correlation analysis between the fractal dimension and the logarithm of the energy density shows that they have approximately linear relation. Finally, based on damage theory and scale invariant principle, the fragmentation model with renormalization method was put forward, and the fractal dimension value predicted with the model was compared with the test results. It is found that the fractal dimension value obtained from the improved fragmentation model is more reasonable.展开更多
In the mining industry,precise forecasting of rock fragmentation is critical for optimising blasting processes.In this study,we address the challenge of enhancing rock fragmentation assessment by developing a novel hy...In the mining industry,precise forecasting of rock fragmentation is critical for optimising blasting processes.In this study,we address the challenge of enhancing rock fragmentation assessment by developing a novel hybrid predictive model named GWO-RF.This model combines the grey wolf optimization(GWO)algorithm with the random forest(RF)technique to predict the D_(80)value,a critical parameter in evaluating rock fragmentation quality.The study is conducted using a dataset from Sarcheshmeh Copper Mine,employing six different swarm sizes for the GWO-RF hybrid model construction.The GWO-RF model’s hyperparameters are systematically optimized within established bounds,and its performance is rigorously evaluated using multiple evaluation metrics.The results show that the GWO-RF hybrid model has higher predictive skills,exceeding traditional models in terms of accuracy.Furthermore,the interpretability of the GWO-RF model is enhanced through the utilization of SHapley Additive exPlanations(SHAP)values.The insights gained from this research contribute to optimizing blasting operations and rock fragmentation outcomes in the mining industry.展开更多
Based on the simplification of cutting process,a series of numerical simulations were conducted using a 2-D discrete element method to explore the effects of embedded cracks with different dip angles on the rock fragm...Based on the simplification of cutting process,a series of numerical simulations were conducted using a 2-D discrete element method to explore the effects of embedded cracks with different dip angles on the rock fragmentation process,cutting characteristics and breaking efficiency.The results show that the simulated results are in a good agreement with previous theoretical study.The main crack propagates to the top tip of embedded crack,except when the dip angle is 90°.Side cracks which are more fully developed in the rocks containing embedded cracks tend to propagate towards the free surface.According to the history of vertical cutting force,it is shown that the peak force is decreased by embedded cracks.The study on cutting efficiency was conducted by combining the quantity of crack and cutting energy.And the results show that breaking efficiency can be treated as a decreasing or a increasing function when the dip angle is less or larger than 30°,respectively.Breaking efficiency is higher than that in intact rock when the dip angle is larger than 45°.展开更多
In blasting operation,the aim is to achieve proper fragmentation and to avoid undesirable events such as backbreak.Therefore,predicting rock fragmentation and backbreak is very important to arrive at a technically and...In blasting operation,the aim is to achieve proper fragmentation and to avoid undesirable events such as backbreak.Therefore,predicting rock fragmentation and backbreak is very important to arrive at a technically and economically successful outcome.Since many parameters affect the blasting results in a complicated mechanism,employment of robust methods such as artificial neural network may be very useful.In this regard,this paper attends to simultaneous prediction of rock fragmentation and backbreak in the blasting operation of Tehran Cement Company limestone mines in Iran.Back propagation neural network（BPNN） and radial basis function neural network（RBFNN） are adopted for the simulation.Also,regression analysis is performed between independent and dependent variables.For the BPNN modeling,a network with architecture 6-10-2 is found to be optimum whereas for the RBFNN,architecture 636-2 with spread factor of 0.79 provides maximum prediction aptitude.Performance comparison of the developed models is fulfilled using value account for（VAF）,root mean square error（RMSE）,determination coefficient（R2） and maximum relative error（MRE）.As such,it is observed that the BPNN model is the most preferable model providing maximum accuracy and minimum error.Also,sensitivity analysis shows that inputs burden and stemming are the most effective parameters on the outputs fragmentation and backbreak,respectively.On the other hand,for both of the outputs,specific charge is the least effective parameter.展开更多
This paper puts forward a new rock fragmentation loading method of dual-cutter head combined dynamic and static loads. By applying the numerical simulation software - RFPA2D, we have done numerical experiment about th...This paper puts forward a new rock fragmentation loading method of dual-cutter head combined dynamic and static loads. By applying the numerical simulation software - RFPA2D, we have done numerical experiment about the sihstone＇ s crushing effect by dynamic load on single cutter head without confining pressure, dynamic load on single cut- ter head with confining pressure 10 MPa and different dual-cutter heads spacing by combined dynamic and static loads with confining pressure 10 MPa. Experimental results show that the confining pressure can obviously affect the rock frag- mentation effect. Combined dynamic and static loads can greatly improve the rock fragmentation effect. There exists an optimal spacing of dual-cutter head that can make the rock fragmentation achieve the desired effect. Through analyzing the acoustic emission accumulative energy and quantity, the authors make a conclusion that the optimum spacing is 30 mm.展开更多
Hydraulic-electric rock fragmentation(HERF)plays a significant role in improving the efficiency of high voltage pulse rock breaking.However,the underlying mechanism of HERF remains unclear.In this study,considering th...Hydraulic-electric rock fragmentation(HERF)plays a significant role in improving the efficiency of high voltage pulse rock breaking.However,the underlying mechanism of HERF remains unclear.In this study,considering the heterogeneity of the rock,microscopic thermodynamic properties,and shockwave time domain waveforms,based on the shockwave model,digital imaging technology and the discrete element method,the cyclic loading numerical simulations of HERF is achieved by coupling electrical,thermal,and solid mechanics under different formation temperatures,confining pressure,initial peak voltage,electrode bit diameter,and loading times.Meanwhile,the HERF discharge system is conducive to the laboratory experiments with various electrical parameters and the resulting broken pits are numerically reconstructed to obtain the geometric parameters.The results show that,the completely broken area consists of powdery rock debris.In the pre-broken zone,the mineral cementation of the rock determines the transition of type CⅠcracks to type CⅡand type CⅢcracks.Furthermore,the peak pressure of the shockwave increased with initial peak voltage but decreased with electrode bit diameter,while the wave front time reduced.Moreover,increasing well depth,formation temperature and confining pressure augment and inhibit HERF,but once confining pressure surpassed the threshold of 60 MPa for 152.40,215.90,and 228.60 mm electrode bits,and 40 MPa for 309.88 mm electrode bits,HERF is promoted.Additionally,for the same kind of rock,the volume and width of the broken pit increase with higher initial peak voltage and rock fissures will promote HERF.Eventually,the electrode drill bit with a 215.90 mm diameter is more suitable for drilling pink granite.This research contributes to a better microscopic understanding of HERF and provides valuable insights for electrode bit selection,as well as the optimization of circuit parameters for HERF technology.展开更多
A new multifunctional testing device for rock fragmentation was introduced, which can conduct many experiments such as single cutting under static load, crushing under impact load, thrusting under static load and cutt...A new multifunctional testing device for rock fragmentation was introduced, which can conduct many experiments such as single cutting under static load, crushing under impact load, thrusting under static load and cutting-impact test under the dynamic and static load. The results of granite and concrete抯 experiments with polycrystalline diamond compact (PDC) flat cutters and carbide alloy cutters under different loadings show that the device has good performance, and the characteristics of broken rock under the combined loads are similar to that under the single static pressure or impact crushing the rock, and the combined loads can increase the effect of rock fragmentation obviously. The experimental methods and effects have the important meaning for studying new drill-ing tool on hard rock fragmentation.展开更多
Spontaneous combustion of coal increases the temperature in adjoining overburden strata of coal seams and poses a challenge when loading blastholes.This condition,known as hot-hole blasting,is dangerous due to the inc...Spontaneous combustion of coal increases the temperature in adjoining overburden strata of coal seams and poses a challenge when loading blastholes.This condition,known as hot-hole blasting,is dangerous due to the increased possibility of premature explosions in loaded blastholes.Thus,it is crucial to load the blastholes with an appropriate amount of explosives within a short period to avoid premature detonation caused by high temperatures of blastholes.Additionally,it will help achieve the desired fragment size.This study tried to ascertain the most influencial variables of mean fragment size and their optimum values adopted for blasting in a fiery seam.Data on blast design,rock mass,and fragmentation of 100 blasts in fiery seams of a coal mine were collected and used to develop mean fragmentation prediction models using soft computational techniques.The coefficient of determination(R^(2)),root mean square error(RMSE),mean absolute error(MAE),mean square error(MSE),variance account for(VAF)and coefficient of efficiency in percentage(CE)were calculated to validate the results.It indicates that the random forest algorithm(RFA)outperforms the artificial neural network(ANN),response surface method(RSM),and decision tree(DT).The values of R^(2),RMSE,MAE,MSE,VAF,and CE for RFA are 0.94,0.034,0.027,0.001,93.58,and 93.01,respectively.Multiple parametric sensitivity analyses(MPSAs)of the input variables showed that the Schmidt hammer rebound number and spacing-to-burden ratio are the most influencial variables for the blast fragment size.The analysis was finally used to define the best blast design variables to achieve optimum fragment size from blasting.The optimum factor values for RFA of S/B,ld/B and ls/ld are 1.03,1.85 and 0.7,respectively.展开更多
The rock fragmentation involves the inter-block and the intra-block fracture.A simulation method for rock fragmentation is developed by coupling Voronoi diagram(VD)and discretized virtual internal bond(DVIB).The DVIB ...The rock fragmentation involves the inter-block and the intra-block fracture.A simulation method for rock fragmentation is developed by coupling Voronoi diagram(VD)and discretized virtual internal bond(DVIB).The DVIB is a lattice model that consists of bonds.The VD is used to generate the potential block structure in the DVIB mesh.Each potential block may contain any number of bond cells.To characterize the inter-block fracture,a hyperelastic bond potential is employed for the bond cells that are cut by the VD edges.While to characterize the intra-block fracture,an elastobrittle bond potential is adopted for the bonds in a block.By this method,both the inter-block and intra-block fracture can be well simulated.The simulation results suggest that this method is a simple and efficient approach to rock fragmentation simulation with block smash.展开更多
To optimize the excavation of rock using underground blasting techniques,a reliable and simplified approach for modeling rock fragmentation is desired.This paper presents a multistep experimentalnumerical methodology ...To optimize the excavation of rock using underground blasting techniques,a reliable and simplified approach for modeling rock fragmentation is desired.This paper presents a multistep experimentalnumerical methodology for simplifying the three-dimensional(3D)to two-dimensional(2D)quasiplane-strain problem and reducing computational costs by more than 100-fold.First,in situ tests were conducted involving single-hole and free-face blasting of a dolomite rock mass in a 1050-m-deep mine.The results were validated by laser scanning.The craters were then compared with four analytical models to calculate the radius of the crushing zone.Next,a full 3D model for single-hole blasting was prepared and validated by simulating the crack length and the radius of the crushing zone.Based on the stable crack propagation zones observed in the 3D model and experiments,a 2D model was prepared.The properties of the high explosive(HE)were slightly reduced to match the shape and number of radial cracks and crushing zone radius between the 3D and 2D models.The final methodology was used to reproduce various cut-hole blasting scenarios and observe the effects of residual cracks in the rock mass on further fragmentation.The presence of preexisting cracks was found to be crucial for fragmentation,particularly when the borehole was situated near a free rock face.Finally,an optimization study was performed to determine the possibility of losing rock continuity at different positions within the well in relation to the free rock face.展开更多
Efficient hard-rock fragmentation remains a critical challenge in mechanized mining.This study designed an adjustable-spacing mold and conducted double cutting pick indentation tests on granite.Mechanical responses an...Efficient hard-rock fragmentation remains a critical challenge in mechanized mining.This study designed an adjustable-spacing mold and conducted double cutting pick indentation tests on granite.Mechanical responses and fragmentation characteristics under varying horizontal stresses,pick spacings,and groove depths were systematically analyzed.Unidirectional stress concentration altered the rock fragmentation modes,exhibiting a dual effect on the fragmentation process.The maximum indentation force(F_(max)),indentation hardness index(IHI),indentation modulus(IM),and indentation energy(W)initially increased and then decreased with rising horizontal stress.Appropriate spacing promoted radial crack coalescence,whereas too small a spacing(20 mm)caused repetitive re-fragmentation of rock chips,and too large a spacing(50 mm)resulted in unbroken ridges.Pre-cut grooves weakened the rock,reducing F_(max) and specific energy(SE),thus improving fragmentation efficiency,although the improvement slowed beyond a 10-mm groove depth.Based on the results and rock-mass conditioning assisted fragmentation mechanism,a“stress-structure dual control”assisted fragmentation mechanism was proposed,and a“pre-drilling unloading−alternate stopping”mining scheme was exploratorily designed.This approach creates favorable conditions for rock fragmentation by reducing stress levels and rock mass integrity in target zones,providing theoretical support and an engineering paradigm for mecheanized mining of deep resources.展开更多
Mountain hazards with large masses of rock blocks in motion – such as rock falls, avalanches and landslides – threaten human lives and structures. Dynamic fragmentation is a common phenomenon during the movement pro...Mountain hazards with large masses of rock blocks in motion – such as rock falls, avalanches and landslides – threaten human lives and structures. Dynamic fragmentation is a common phenomenon during the movement process of rock blocks in rock avalanche, due to the high velocity and impacts against obstructions. In view of the energy consumption theory for brittle rock fragmentation proposed by Bond, which relates energy to size reduction, a theoretical model is proposed to estimate the average fragment size for a moving rock block when it impacts against an obstruction. Then, different forms of motion are studied, with various drop heights and slope angles for the moving rock block. The calculated results reveal that the average fragment size decreases as the drop height increases, whether for free-fall or for a sliding or rolling rock block, and the decline in size is rapid for low heights and slow for increasing heights in the corresponding curves. Moreover, the average fragment size also decreases as the slope angle increases for a slidingrock block. In addition, a rolling rock block has a higher degree of fragmentation than a sliding rock block, even for the same slope angle and block volume. Finally, to compare with others' results, the approximate number of fragments is estimated for each calculated example, and the results show that the proposed model is applicable to a relatively isotropic moving rock block.展开更多
Rock fragmentation plays a critical role in rock avalanches,yet conventional approaches such as classical granular flow models or the bonded particle model have limitations in accurately characterizing the progressive...Rock fragmentation plays a critical role in rock avalanches,yet conventional approaches such as classical granular flow models or the bonded particle model have limitations in accurately characterizing the progressive disintegration and kinematics of multi-deformable rock blocks during rockslides.The present study proposes a discrete-continuous numerical model,based on a cohesive zone model,to explicitly incorporate the progressive fragmentation and intricate interparticle interactions inherent in rockslides.Breakable rock granular assemblies are released along an inclined plane and flow onto a horizontal plane.The numerical scenarios are established to incorporate variations in slope angle,initial height,friction coefficient,and particle number.The evolutions of fragmentation,kinematic,runout and depositional characteristics are quantitatively analyzed and compared with experimental and field data.A positive linear relationship between the equivalent friction coefficient and the apparent friction coefficient is identified.In general,the granular mass predominantly exhibits characteristics of a dense granular flow,with the Savage number exhibiting a decreasing trend as the volume of mass increases.The process of particle breakage gradually occurs in a bottom-up manner,leading to a significant increase in the angular velocities of the rock blocks with increasing depth.The simulation results reproduce the field observations of inverse grading and source stratigraphy preservation in the deposit.We propose a disintegration index that incorporates factors such as drop height,rock mass volume,and rock strength.Our findings demonstrate a consistent linear relationship between this index and the fragmentation degree in all tested scenarios.展开更多
To evaluate the accuracy of rockburst tendency classification in coal-bearing sandstone strata,this study conducted uniaxial compression loading and unloading tests on sandstone samples with four distinct grain sizes....To evaluate the accuracy of rockburst tendency classification in coal-bearing sandstone strata,this study conducted uniaxial compression loading and unloading tests on sandstone samples with four distinct grain sizes.The tests involved loading the samples to 60%,70%,and 80%of their uniaxial compressive strength,followed by unloading and reloading until failure.Key parameters such as the elastic energy index and linear elasticity criteria were derived from these tests.Additionally,rock fragments were collected to calculate their initial ejection kinetic energy,serving as a measure of rockburst tendency.The classification of rockburst tendency was conducted using grading methods based on burst energy index(WET),pre-peak stored elastic energy(PES)and experimental observations.Multi-class classification and regression analyses were applied to machine learning models using experimental data to predict rockburst tendency levels.A comparative analysis of models from two libraries revealed that the Random Forest model achieved the highest accuracy in classification,while the Ada Boost Regressor model excelled in regression predictions.This study highlights that on a laboratory scale,integrating ejection kinetic energy with the unloading ratio,failure load,W_(ET)and PES through machine learning offers a highly accurate and reliable approach for determining rockburst tendency levels.展开更多
基金National Natural Science Foundation of China,Grant/Award Number:52374153。
文摘Rock fragmentation is an important indicator for assessing the quality of blasting operations.However,accurate prediction of rock fragmentation after blasting is challenging due to the complicated blasting parameters and rock properties.For this reason,optimized by the Bayesian optimization algorithm(BOA),four hybrid machine learning models,including random forest,adaptive boosting,gradient boosting,and extremely randomized trees,were developed in this study.A total of 102 data sets with seven input parameters(spacing-to-burden ratio,hole depth-to-burden ratio,burden-to-hole diameter ratio,stemming length-to-burden ratio,powder factor,in situ block size,and elastic modulus)and one output parameter(rock fragment mean size,X_(50))were adopted to train and validate the predictive models.The root mean square error(RMSE),the mean absolute error(MAE),and the coefficient of determination(R^(2))were used as the evaluation metrics.The evaluation results demonstrated that the hybrid models showed superior performance than the standalone models.The hybrid model consisting of gradient boosting and BOA(GBoost-BOA)achieved the best prediction results compared with the other hybrid models,with the highest R^(2)value of 0.96 and the smallest values of RMSE and MAE of 0.03 and 0.02,respectively.Furthermore,sensitivity analysis was carried out to study the effects of input variables on rock fragmentation.In situ block size(XB),elastic modulus(E),and stemming length-to-burden ratio(T/B)were set as the main influencing factors.The proposed hybrid model provided a reliable prediction result and thus could be considered an alternative approach for rock fragment prediction in mining engineering.
基金supported by the Major Program of National Natural Science Foundation of China(No.52192624)the Innovative Research Group Project of National Natural Science Foundation of China(No.52421002)+3 种基金Major Science and Technology Project of Yunnan Province(No.202302AF080001)NSFC Key International(Regional)Cooperative Research Projects(No.52020105001)General Program of National Natural Science Foundation of China(Nos.52204019 and 52274016)the Foundation of State Key Laboratory of Petroleum Resources and Prospecting(No.PRE/DX-2402)。
文摘Percussion drilling is a promising approach for hot dry rock(HDR)fragmentation.However,understanding of HDR fragmentation mechanism under multi-dimensional percussion remains limited and hinders the corresponding drilling performance.Herein,an innovative true triaxial multi-dimensional percussion device was developed for the study of HDR fragmentation mechanism under in-situ temperature and stress conditions.Multi-dimensional percussion,involving both axial and torsional components,was applied to drilling in granite and carbonatite rocks sampled from the typical HDR target areas.Multiscale visualization techniques and a whale optimization-variational mode decomposition algorithm were employed to investigate the rock failure patterns and drilling energy characteristics.Results indicated that multi-dimensional percussion enhances brittle-ductile mixed failure in granite,characterized by transgranular,intergranular,and combined fracture patterns that promote rock cracking.In contrast,carbonatite drillhole displays enhanced brittle fragmentation and tortuous failure surface dominated by transgranular fracture pattern.Frequency-domain characteristics of penetration force signals for multidimensional percussion,especially the significant dominant frequency,amplitude,and high-frequency dissipation,indicate an increase in net energy for drilling into HDR and intensified rock fragmentation.Further,the effect of impact frequency on rock fragmentation performance was emphasized to maximize drilling efficiency.The optimal regulation schemes between axial and torsional impact frequencies are identified as 15 Hz+15 Hz for granite and 30 Hz+15 Hz for carbonatite.The reliability of the optimization approach was validated through a field test that employed a novel impactor in the geothermal well Fushen-1.
基金Foundation item:Project (2006BAB02A02) supported by the National Key Technology R&D Program during the 11th Five-year Plan Period of ChinaProject (CX2011B119) supported by the Graduated Students' Research and Innovation Fund of Hunan Province, ChinaProject (2009ssxt230) supported by the Central South University Innovation Fund,China
文摘Aiming at the problems of the traditional method of assessing distribution of particle size in bench blasting, a support vector machines （SVMs） regression methodology was used to predict the mean particle size （X50） resulting from rock blast fragmentation in various mines based on the statistical learning theory. The data base consisted of blast design parameters, explosive parameters, modulus of elasticity and in-situ block size. The seven input independent variables used for the SVMs model for the prediction of X50 of rock blast fragmentation were the ratio of bench height to drilled burden （H/B）, ratio of spacing to burden （S/B）, ratio of burden to hole diameter （B/D）, ratio of stemming to burden （T/B）, powder factor （Pf）, modulus of elasticity （E） and in-situ block size （XB）. After using the 90 sets of the measured data in various mines and rock formations in the world for training and testing, the model was applied to 12 another blast data for validation of the trained support vector regression （SVR） model. The prediction results of SVR were compared with those of artificial neural network （ANN）, multivariate regression analysis （MVRA） models, conventional Kuznetsov method and the measured X50 values. The proposed method shows promising results and the prediction accuracy of SVMs model is acceptable.
基金The financial support from Coal S&T grant of Ministry of Coal,Government of India
文摘The blasting operation plays a pivotal role in the overall economics of opencast mines.The blasting subsystem affects all the other associated sub-systems,i.e.loading,transport,crushing and milling operations.Fragmentation control through effective blast design and its effect on productivity are the challenging tasks for practicing blasting engineer due to inadequate knowledge of actual explosive energy released in the borehole,varying initiation practice in blast design and its effect on explosive energy release characteristic.This paper describes the result of a systematic study on the impact of blast design parameters on rock fragmentation at three mines in India.The mines use draglines and shoveledumper combination for removal of overburden.Despite its pivotal role in controlling the overall economics of a mining operation,the expected blasting performance is often judged almost exclusively on the basis of poorly defined parameters such as powder factor and is often qualitative which results in very subjective assessment of blasting performance.Such an approach is very poor substitutes for accurate assessment of explosive and blasting performance.Ninety one blasts were conducted with varying blast designs and charging patterns,and their impacts on the rock fragmentation were documented.A high-speed camera was deployed to record the detonation sequences of the blasts.The efficiency of the loading machines was also correlated with the mean fragment size obtained from the fragmentation analyses.
基金The authors gratefully acknowledge the financial support from Natural Science Research Project of Universities in Anhui Province(No.KJ2021A0463)Scientific Research Startup Fund for introduced talents of Anhui University of Science and Technology,and Natural Science Foundation of Anhui Province(No.2108085QE208).
文摘This investigation aims to explore the effects of stress conditions and rock cutting rates on hard rock fragmentation through indentation tests on a newly designed triaxial testing apparatus.This apparatus was designed to realize a triaxial loading and indentation test of cylindrical specimens using inserted tooth cutter.The boreability and crushing efficiency of granite rock was investigated by analyzing the change rules of the thrusting force,penetration depth,characteristics of chippings and failure patterns.Several quantitative indexes were used to evaluate rock boreability in this investigation.The granite rock samples all had a chiselled pit and a crushed rock core.Under initial stress conditions,only flat-shape chippings were stripped from the rock surface when the thrusting force reached 20 kN.The rock cutting special energy had a close correlation with the initial stress conditions and inserted tooth shape.Moreover,a thrusting force prediction model was proposed in this paper.The contribution of this study is that for the first time the influence mechanism of the initial triaxial stress conditions on rock fragmentation is investigated using an inserted tooth and the newly designed testing apparatus.This study has a crucial importance for practical underground hard rock crushing in geoengineering.
基金support of National Natural Science Foundation of China(No.52177144)。
文摘High-voltage pulse discharge(HVPD)rock fragmentation controls a plasma channel forming inside the rock by adjusting the electrical parameters,electrode type,etc.In this work,an HVPD rock fragmentation test platform was built and the test waveforms were measured.Considering the effects of temperature,channel expansion and electromagnetic radiation,the impedance model of the plasma channel in the rock was established.The parameters and initial values of the model were determined by an iterative computational process.The model calculation results can reasonably characterize the development of the plasma channel in the rock and estimate the shock wave characteristics.Based on the plasma channel impedance model,the temporal and spatial distribution characteristics of the radial stress and tangential stress in the rock were calculated,and the rock fragmentation effect of the HVPD was analyzed.
基金Project(10472134 ,50490274 ,50534030) supported by the National Natural Science Foundation of China
文摘The fragmentation test of granite subjected to strain rate of 10~010~2s~ -1 was carried out using split Hopkinson pressure bar(SHPB) whose diameter is 75 mm, where half-sine loading waveform was performed. The sieving statistics results of the fragments show that the distribution of the fragments is a fractal, and the fractal dimension values fall into the range of 1.22.4. The correlation analysis between the fractal dimension and the logarithm of the energy density shows that they have approximately linear relation. Finally, based on damage theory and scale invariant principle, the fragmentation model with renormalization method was put forward, and the fractal dimension value predicted with the model was compared with the test results. It is found that the fractal dimension value obtained from the improved fragmentation model is more reasonable.
基金Projects(42177164,52474121)supported by the National Science Foundation of ChinaProject(PBSKL2023A12)supported by the State Key Laboratory of Precision Blasting and Hubei Key Laboratory of Blasting Engineering,China。
文摘In the mining industry,precise forecasting of rock fragmentation is critical for optimising blasting processes.In this study,we address the challenge of enhancing rock fragmentation assessment by developing a novel hybrid predictive model named GWO-RF.This model combines the grey wolf optimization(GWO)algorithm with the random forest(RF)technique to predict the D_(80)value,a critical parameter in evaluating rock fragmentation quality.The study is conducted using a dataset from Sarcheshmeh Copper Mine,employing six different swarm sizes for the GWO-RF hybrid model construction.The GWO-RF model’s hyperparameters are systematically optimized within established bounds,and its performance is rigorously evaluated using multiple evaluation metrics.The results show that the GWO-RF hybrid model has higher predictive skills,exceeding traditional models in terms of accuracy.Furthermore,the interpretability of the GWO-RF model is enhanced through the utilization of SHapley Additive exPlanations(SHAP)values.The insights gained from this research contribute to optimizing blasting operations and rock fragmentation outcomes in the mining industry.
基金Project(2013CB035401)supported by the National Basic Research Program of ChinaProject(51174228)supported by the National Natural Science Foundation of ChinaProject(71380100003)supported by Hunan Provincial Innovation Foundation for Postgraduate,China
文摘Based on the simplification of cutting process,a series of numerical simulations were conducted using a 2-D discrete element method to explore the effects of embedded cracks with different dip angles on the rock fragmentation process,cutting characteristics and breaking efficiency.The results show that the simulated results are in a good agreement with previous theoretical study.The main crack propagates to the top tip of embedded crack,except when the dip angle is 90°.Side cracks which are more fully developed in the rocks containing embedded cracks tend to propagate towards the free surface.According to the history of vertical cutting force,it is shown that the peak force is decreased by embedded cracks.The study on cutting efficiency was conducted by combining the quantity of crack and cutting energy.And the results show that breaking efficiency can be treated as a decreasing or a increasing function when the dip angle is less or larger than 30°,respectively.Breaking efficiency is higher than that in intact rock when the dip angle is larger than 45°.
文摘In blasting operation,the aim is to achieve proper fragmentation and to avoid undesirable events such as backbreak.Therefore,predicting rock fragmentation and backbreak is very important to arrive at a technically and economically successful outcome.Since many parameters affect the blasting results in a complicated mechanism,employment of robust methods such as artificial neural network may be very useful.In this regard,this paper attends to simultaneous prediction of rock fragmentation and backbreak in the blasting operation of Tehran Cement Company limestone mines in Iran.Back propagation neural network（BPNN） and radial basis function neural network（RBFNN） are adopted for the simulation.Also,regression analysis is performed between independent and dependent variables.For the BPNN modeling,a network with architecture 6-10-2 is found to be optimum whereas for the RBFNN,architecture 636-2 with spread factor of 0.79 provides maximum prediction aptitude.Performance comparison of the developed models is fulfilled using value account for（VAF）,root mean square error（RMSE）,determination coefficient（R2） and maximum relative error（MRE）.As such,it is observed that the BPNN model is the most preferable model providing maximum accuracy and minimum error.Also,sensitivity analysis shows that inputs burden and stemming are the most effective parameters on the outputs fragmentation and backbreak,respectively.On the other hand,for both of the outputs,specific charge is the least effective parameter.
基金National Science Foundation of China (No.50974059No.50934006)
文摘This paper puts forward a new rock fragmentation loading method of dual-cutter head combined dynamic and static loads. By applying the numerical simulation software - RFPA2D, we have done numerical experiment about the sihstone＇ s crushing effect by dynamic load on single cutter head without confining pressure, dynamic load on single cut- ter head with confining pressure 10 MPa and different dual-cutter heads spacing by combined dynamic and static loads with confining pressure 10 MPa. Experimental results show that the confining pressure can obviously affect the rock frag- mentation effect. Combined dynamic and static loads can greatly improve the rock fragmentation effect. There exists an optimal spacing of dual-cutter head that can make the rock fragmentation achieve the desired effect. Through analyzing the acoustic emission accumulative energy and quantity, the authors make a conclusion that the optimum spacing is 30 mm.
基金supported by the National Natural Science Foundation of China(Nos.52034006,52004229,52225401,and 52274231)the Regional Innovation Cooperation Project of Sichuan Province(No.2022YFQ0059)+3 种基金Science and Technology Cooperation Project of the CNPC-SWPU Innovation Alliance(No.2020CX040301)Natural Science Foundation of Sichuan Province(No.2023NSFSC0431)Science and Technology Strategic Cooperation Project between Nanchong City and Southwest Petroleum University(No.SXHZ004)Research and innovation Fund for Graduate Students of Southwest Petroleum University(No.2022KYCX058).
文摘Hydraulic-electric rock fragmentation(HERF)plays a significant role in improving the efficiency of high voltage pulse rock breaking.However,the underlying mechanism of HERF remains unclear.In this study,considering the heterogeneity of the rock,microscopic thermodynamic properties,and shockwave time domain waveforms,based on the shockwave model,digital imaging technology and the discrete element method,the cyclic loading numerical simulations of HERF is achieved by coupling electrical,thermal,and solid mechanics under different formation temperatures,confining pressure,initial peak voltage,electrode bit diameter,and loading times.Meanwhile,the HERF discharge system is conducive to the laboratory experiments with various electrical parameters and the resulting broken pits are numerically reconstructed to obtain the geometric parameters.The results show that,the completely broken area consists of powdery rock debris.In the pre-broken zone,the mineral cementation of the rock determines the transition of type CⅠcracks to type CⅡand type CⅢcracks.Furthermore,the peak pressure of the shockwave increased with initial peak voltage but decreased with electrode bit diameter,while the wave front time reduced.Moreover,increasing well depth,formation temperature and confining pressure augment and inhibit HERF,but once confining pressure surpassed the threshold of 60 MPa for 152.40,215.90,and 228.60 mm electrode bits,and 40 MPa for 309.88 mm electrode bits,HERF is promoted.Additionally,for the same kind of rock,the volume and width of the broken pit increase with higher initial peak voltage and rock fissures will promote HERF.Eventually,the electrode drill bit with a 215.90 mm diameter is more suitable for drilling pink granite.This research contributes to a better microscopic understanding of HERF and provides valuable insights for electrode bit selection,as well as the optimization of circuit parameters for HERF technology.
文摘A new multifunctional testing device for rock fragmentation was introduced, which can conduct many experiments such as single cutting under static load, crushing under impact load, thrusting under static load and cutting-impact test under the dynamic and static load. The results of granite and concrete抯 experiments with polycrystalline diamond compact (PDC) flat cutters and carbide alloy cutters under different loadings show that the device has good performance, and the characteristics of broken rock under the combined loads are similar to that under the single static pressure or impact crushing the rock, and the combined loads can increase the effect of rock fragmentation obviously. The experimental methods and effects have the important meaning for studying new drill-ing tool on hard rock fragmentation.
文摘Spontaneous combustion of coal increases the temperature in adjoining overburden strata of coal seams and poses a challenge when loading blastholes.This condition,known as hot-hole blasting,is dangerous due to the increased possibility of premature explosions in loaded blastholes.Thus,it is crucial to load the blastholes with an appropriate amount of explosives within a short period to avoid premature detonation caused by high temperatures of blastholes.Additionally,it will help achieve the desired fragment size.This study tried to ascertain the most influencial variables of mean fragment size and their optimum values adopted for blasting in a fiery seam.Data on blast design,rock mass,and fragmentation of 100 blasts in fiery seams of a coal mine were collected and used to develop mean fragmentation prediction models using soft computational techniques.The coefficient of determination(R^(2)),root mean square error(RMSE),mean absolute error(MAE),mean square error(MSE),variance account for(VAF)and coefficient of efficiency in percentage(CE)were calculated to validate the results.It indicates that the random forest algorithm(RFA)outperforms the artificial neural network(ANN),response surface method(RSM),and decision tree(DT).The values of R^(2),RMSE,MAE,MSE,VAF,and CE for RFA are 0.94,0.034,0.027,0.001,93.58,and 93.01,respectively.Multiple parametric sensitivity analyses(MPSAs)of the input variables showed that the Schmidt hammer rebound number and spacing-to-burden ratio are the most influencial variables for the blast fragment size.The analysis was finally used to define the best blast design variables to achieve optimum fragment size from blasting.The optimum factor values for RFA of S/B,ld/B and ls/ld are 1.03,1.85 and 0.7,respectively.
基金the National Natural ScienceFoundation of China(Grant 11772190),which is gratefully acknowledged.
文摘The rock fragmentation involves the inter-block and the intra-block fracture.A simulation method for rock fragmentation is developed by coupling Voronoi diagram(VD)and discretized virtual internal bond(DVIB).The DVIB is a lattice model that consists of bonds.The VD is used to generate the potential block structure in the DVIB mesh.Each potential block may contain any number of bond cells.To characterize the inter-block fracture,a hyperelastic bond potential is employed for the bond cells that are cut by the VD edges.While to characterize the intra-block fracture,an elastobrittle bond potential is adopted for the bonds in a block.By this method,both the inter-block and intra-block fracture can be well simulated.The simulation results suggest that this method is a simple and efficient approach to rock fragmentation simulation with block smash.
文摘To optimize the excavation of rock using underground blasting techniques,a reliable and simplified approach for modeling rock fragmentation is desired.This paper presents a multistep experimentalnumerical methodology for simplifying the three-dimensional(3D)to two-dimensional(2D)quasiplane-strain problem and reducing computational costs by more than 100-fold.First,in situ tests were conducted involving single-hole and free-face blasting of a dolomite rock mass in a 1050-m-deep mine.The results were validated by laser scanning.The craters were then compared with four analytical models to calculate the radius of the crushing zone.Next,a full 3D model for single-hole blasting was prepared and validated by simulating the crack length and the radius of the crushing zone.Based on the stable crack propagation zones observed in the 3D model and experiments,a 2D model was prepared.The properties of the high explosive(HE)were slightly reduced to match the shape and number of radial cracks and crushing zone radius between the 3D and 2D models.The final methodology was used to reproduce various cut-hole blasting scenarios and observe the effects of residual cracks in the rock mass on further fragmentation.The presence of preexisting cracks was found to be crucial for fragmentation,particularly when the borehole was situated near a free rock face.Finally,an optimization study was performed to determine the possibility of losing rock continuity at different positions within the well in relation to the free rock face.
基金National Major Science and Technology Project for Deep Earth Exploration(No.2025ZD1008301)National Natural Science Foundation of China(No.52374153)for the financial supportthe support of the China Scholarship Council.
文摘Efficient hard-rock fragmentation remains a critical challenge in mechanized mining.This study designed an adjustable-spacing mold and conducted double cutting pick indentation tests on granite.Mechanical responses and fragmentation characteristics under varying horizontal stresses,pick spacings,and groove depths were systematically analyzed.Unidirectional stress concentration altered the rock fragmentation modes,exhibiting a dual effect on the fragmentation process.The maximum indentation force(F_(max)),indentation hardness index(IHI),indentation modulus(IM),and indentation energy(W)initially increased and then decreased with rising horizontal stress.Appropriate spacing promoted radial crack coalescence,whereas too small a spacing(20 mm)caused repetitive re-fragmentation of rock chips,and too large a spacing(50 mm)resulted in unbroken ridges.Pre-cut grooves weakened the rock,reducing F_(max) and specific energy(SE),thus improving fragmentation efficiency,although the improvement slowed beyond a 10-mm groove depth.Based on the results and rock-mass conditioning assisted fragmentation mechanism,a“stress-structure dual control”assisted fragmentation mechanism was proposed,and a“pre-drilling unloading−alternate stopping”mining scheme was exploratorily designed.This approach creates favorable conditions for rock fragmentation by reducing stress levels and rock mass integrity in target zones,providing theoretical support and an engineering paradigm for mecheanized mining of deep resources.
基金supported by the National Natural Science Foundation of China (41472272, 41225011)the Youth Science and Technology Fund of Sichuan Province (2016JQ0011)the Opening Fund of the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection (Chengdu University of Technology) (SKLGP2013K015)
文摘Mountain hazards with large masses of rock blocks in motion – such as rock falls, avalanches and landslides – threaten human lives and structures. Dynamic fragmentation is a common phenomenon during the movement process of rock blocks in rock avalanche, due to the high velocity and impacts against obstructions. In view of the energy consumption theory for brittle rock fragmentation proposed by Bond, which relates energy to size reduction, a theoretical model is proposed to estimate the average fragment size for a moving rock block when it impacts against an obstruction. Then, different forms of motion are studied, with various drop heights and slope angles for the moving rock block. The calculated results reveal that the average fragment size decreases as the drop height increases, whether for free-fall or for a sliding or rolling rock block, and the decline in size is rapid for low heights and slow for increasing heights in the corresponding curves. Moreover, the average fragment size also decreases as the slope angle increases for a slidingrock block. In addition, a rolling rock block has a higher degree of fragmentation than a sliding rock block, even for the same slope angle and block volume. Finally, to compare with others' results, the approximate number of fragments is estimated for each calculated example, and the results show that the proposed model is applicable to a relatively isotropic moving rock block.
基金support from the National Key R&D plan(Grant No.2022YFC3004303)the National Natural Science Foundation of China(Grant No.42107161)+3 种基金the State Key Laboratory of Hydroscience and Hydraulic Engineering(Grant No.2021-KY-04)the Open Research Fund Program of State Key Laboratory of Hydroscience and Engineering(sklhse-2023-C-01)the Open Research Fund Program of Key Laboratory of the Hydrosphere of the Ministry of Water Resources(mklhs-2023-04)the China Three Gorges Corporation(XLD/2117).
文摘Rock fragmentation plays a critical role in rock avalanches,yet conventional approaches such as classical granular flow models or the bonded particle model have limitations in accurately characterizing the progressive disintegration and kinematics of multi-deformable rock blocks during rockslides.The present study proposes a discrete-continuous numerical model,based on a cohesive zone model,to explicitly incorporate the progressive fragmentation and intricate interparticle interactions inherent in rockslides.Breakable rock granular assemblies are released along an inclined plane and flow onto a horizontal plane.The numerical scenarios are established to incorporate variations in slope angle,initial height,friction coefficient,and particle number.The evolutions of fragmentation,kinematic,runout and depositional characteristics are quantitatively analyzed and compared with experimental and field data.A positive linear relationship between the equivalent friction coefficient and the apparent friction coefficient is identified.In general,the granular mass predominantly exhibits characteristics of a dense granular flow,with the Savage number exhibiting a decreasing trend as the volume of mass increases.The process of particle breakage gradually occurs in a bottom-up manner,leading to a significant increase in the angular velocities of the rock blocks with increasing depth.The simulation results reproduce the field observations of inverse grading and source stratigraphy preservation in the deposit.We propose a disintegration index that incorporates factors such as drop height,rock mass volume,and rock strength.Our findings demonstrate a consistent linear relationship between this index and the fragmentation degree in all tested scenarios.
基金financial support for this work provided by the National Natural Science Foundation of China (No.52227901)。
文摘To evaluate the accuracy of rockburst tendency classification in coal-bearing sandstone strata,this study conducted uniaxial compression loading and unloading tests on sandstone samples with four distinct grain sizes.The tests involved loading the samples to 60%,70%,and 80%of their uniaxial compressive strength,followed by unloading and reloading until failure.Key parameters such as the elastic energy index and linear elasticity criteria were derived from these tests.Additionally,rock fragments were collected to calculate their initial ejection kinetic energy,serving as a measure of rockburst tendency.The classification of rockburst tendency was conducted using grading methods based on burst energy index(WET),pre-peak stored elastic energy(PES)and experimental observations.Multi-class classification and regression analyses were applied to machine learning models using experimental data to predict rockburst tendency levels.A comparative analysis of models from two libraries revealed that the Random Forest model achieved the highest accuracy in classification,while the Ada Boost Regressor model excelled in regression predictions.This study highlights that on a laboratory scale,integrating ejection kinetic energy with the unloading ratio,failure load,W_(ET)and PES through machine learning offers a highly accurate and reliable approach for determining rockburst tendency levels.
