Effects of rock fragments on yak dung greenhouse gas emissions on the Qinghai-Tibetan Plateau

Dung deposition is an important pathway of nutrient return and redistribution in alpine grasslands of the Qinghai-Tibetan Plateau.To date,information on the greenhouse gas emissions of yak dung on alpine grasslands,especially where there are large amounts of rock fragments,is limited.Our aim,therefore,was to evaluate variations in N_2O,CH_4,and CO_2 emissions from yak dung(CCD),and compare it to dung placed on rock fragments(RCD),alpine steppe soil(CSD),and a soil and rock fragment mixture(RSD) over a 30-day incubation period.The results showed that the total N_2O emissions from treatments without soil were significantly(P < 0.05) lower than those from treatments with soil.The highest total CH_4 emissions were detected in the CSD treatment,while CH_4 losses from treatments without rock fragments were significantly(P < 0.05) greater than those with rock fragments.The total CO_2 emissions from the RSD treatment was 6.30%–12.0% lower than those in the other three treatments.The soil beneath yak dung pats elevated the globalwarming potential(GWP),while the addition of rock fragments to the soil significantly(P < 0.05) decreased the GWP by reducing emissions of the three greenhouse gases.We therefore suggest that interactions between rock fragments and alpine steppe soil are effective in decreasing yak dung greenhouse gas emissions.This finding indicates that rock fragments are an effective medium for reducing greenhouse gas emissions from dung pats,and more attention should therefore be paid to evaluate its ecological impact in future studies.These results should help guide scientific assessments of regional GHG budgets in agricultural ecosystems where the addition of livestock manure to soils with large amounts of rock fragments is common.

Effect of Rock Fragments on Tracer Transport in Broadleaved and Coniferous Forest Soils: Column Study

This study investigated the effect of rock fragments on tracer transport in broadleaved and coniferous forest soils from the 0 - 100 cm depth of Gongga Mountain in eastern margin of Qinghai Tibetan Plateau. Using repacked soil columns (20 cm in height and 10 cm in diameter) with different rock fragments contents (0%, 5%, and 15% in v/v), breakthrough curves of bromide (as non-reactive tracer) were obtained under saturated condition. A two-region model was applied and the parameters were estimated by inverse modeling. Results show that with increasing rock fragment content the dispersivity (λ) generally increased while the mobile-immobile partition coefficient (β) and the mass transfer coefficient (ω) decreased. The presence of rock fragments led to an increase in the fraction of immobile domain as well as soil tortuosity. A plausible explanation is that the soil beneath the rock fragments behaved as immobile domain and soil-rock interfaces could serve as preferential flow paths.

Characteristics of rock fragments in different forest stony soil and its relationship with macropore characteristics in mountain area, northern China

Rock fragments have major effect on soil macropores and water movement. However, the characteristics of rock fragments and their relationship with macropore characteristics remain elusive in forest stony soils in northern mountainous area of China. The objectives of this study are to(1) use Industrial Computed Tomography(CT) scanning to quantitatively analyze rock fragment characteristics in intact soil columns in different forest lands and(2) identify the relationship between characteristics of rock fragments and that of the macropores. Intact soil columns that were 100 mm in diameter and 300 mm long were randomly taken from six local forest stony soils in Wuzuolou Forest Station in Miyun, Beijing. Industrial CT was used to scan all soil column samples, and then the scanned images were utilized to obtain the three-dimensional(3 D) images of rock fragments and macropore structures. Next, theparameters of the rock fragments and macropore structure were measured, including the volume, diameter, surface area, and number of rock fragments, as well as the volume, diameter, surface area, length, angle, tortuosity and number of macropores. The results showed that no significant difference was found in soil rock fragments content in the 10-30 cm layer between mixed forest and pure forest, but in the 0-10 cm soil layer, the rock fragments in mixed forest were significantly less than in pure forest. The number density of macropores has significant negative correlation with the number of rock fragments in the 0-10 cm soil layer, whereas this correlation is not significant in 10-20 cm and 20-30 cm soil layers. The volume density of macropore was not correlated with the volume density of rock fragments, and there is no correlation between the density of macropore surface area and the density of rock fragment surface area. Industrial CT scanning combined with image processing technology canprovide a better way to explore 3 D distribution of rock fragments in soil. The content of rock fragments in soil is mainly determined by parent rocks. The surface soil(0-10 cm) of forest contains fewer rock fragments and more macropores, which may be caused by bioturbation, root systems, gravitational settling and faunal undermining.

Numerical and experimental investigation on hydraulic-electric rock fragmentation of heterogeneous granite

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.

Enhancing rock fragmentation prediction in mining operations:A hybrid GWO-RF model with SHAP interpretability

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.

Progressive fragmentation of granular assemblies within rockslides: Insights from discrete-continuous numerical modeling

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.

Prediction of rock fragmentation in a fiery seam of an open-pit coal mine in India

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.

Numerical modeling of blast-induced rock fragmentation in deep mining with 3D and 2D FEM method approaches

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.

Stress wave analysis of high-voltage pulse discharge rock fragmentation based on plasma channel impedance model

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.

Support vector machines approach to mean particle size of rock fragmentation due to bench blasting prediction

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.

Rock fragmentation control in opencast blasting

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.

Experimental study on acoustic emission characteristics of jointed rock mass by double disc cutter

The characteristics of joints are crucial factors which influence the penetration efficiency of tunnel boring machine(TBM).Based on the theoretical study,numerical simulation and experimental research,many researchers have studied the interaction between TBM disc cutters and jointed rock mass.However,in most of these works,the effect of joint on rock fragmentation by double disc cutter has been scarcely investigated.Thus,the effects of joint orientation and joint space on rock fragmentation by double disc cutter are highlighted in this study.During the test,jointed concrete specimens are adopted to simulate jointed rock mass.Improved RYL-600rock shear rheological instrument was employed during the indentation process under disc cutters,and acoustic emission location system was used to analyze the rock damage and physical deterioration.The results show that there are four failure modes and three modes of crack initiation and propagation in jointed rock mass.It is concluded that the existing joint planes have obviously restrained the crack initiation and propagation during the rock fragmentation process.The results also indicate that samples are damaged most seriously when joint orientation equals60°,which is proved to be the optimum joint orientation in TBM penetration.

Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms

Blasting is well-known as an effective method for fragmenting or moving rock in open-pit mines.To evaluate the quality of blasting,the size of rock distribution is used as a critical criterion in blasting operations.A high percentage of oversized rocks generated by blasting operations can lead to economic and environmental damage.Therefore,this study proposed four novel intelligent models to predict the size of rock distribution in mine blasting in order to optimize blasting parameters,as well as the efficiency of blasting operation in open mines.Accordingly,a nature-inspired algorithm(i.e.,firefly algorithm-FFA)and different machine learning algorithms(i.e.,gradient boosting machine(GBM),support vector machine(SVM),Gaussian process(GP),and artificial neural network(ANN))were combined for this aim,abbreviated as FFA-GBM,FFA-SVM,FFA-GP,and FFA-ANN,respectively.Subsequently,predicted results from the abovementioned models were compared with each other using three statistical indicators(e.g.,mean absolute error,root-mean-squared error,and correlation coefficient)and color intensity method.For developing and simulating the size of rock in blasting operations,136 blasting events with their images were collected and analyzed by the Split-Desktop software.In which,111 events were randomly selected for the development and optimization of the models.Subsequently,the remaining 25 blasting events were applied to confirm the accuracy of the proposed models.Herein,blast design parameters were regarded as input variables to predict the size of rock in blasting operations.Finally,the obtained results revealed that the FFA is a robust optimization algorithm for estimating rock fragmentation in bench blasting.Among the models developed in this study,FFA-GBM provided the highest accuracy in predicting the size of fragmented rocks.The other techniques(i.e.,FFA-SVM,FFA-GP,and FFA-ANN)yielded lower computational stability and efficiency.Hence,the FFA-GBM model can be used as a powerful and precise soft computing tool that can be applied to practical engineering cases aiming to improve the quality of blasting and rock fragmentation.

Experimental investigation on hard rock fragmentation of inserted tooth cutter using a newly designed indentation testing apparatus

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.

Numerical simulation on effects of embedded crack on rock fragmentation by a tunnel boring machine cutter

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°.

Fractal characteristics of rock fragmentation at strain rate of 10~0-10~2 s^(-1)

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.

Numerical experiment rock fragmentation by combined dynamic and static loads under dual-cutter head

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.

A comparative study on the application of various artificial neural networks to simultaneous prediction of rock fragmentation and backbreak

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.

A new diamond bit for extra-hard, compact and nonabrasive rock formation

A new impregnated diamond bit was designed to solve the slipping problem when impregnated diamond bit was used for extra-hard, compact, and nonabrasive rock formation. Adding Si C grits into matrix, Si C grits can easily be exfoliated from the surface of the matrix due to weak holding-force with matrix, which made the surface non-smooth. Three Ф36/24 mm laboratorial bits were manufactured to conduct a laboratory drilling test on zirconiacorundum refractory brick. The laboratory drilling test indicates that the abrasive resistance of the bit work layer is proportional to the Si C concentation. The higher the concentration, the weaker the abrasive resistance of matrix. The new impregnated diamond bit was applied to a mining area drilling construction in Jiangxi province, China. Field drilling application indicates that the ROP(rate of penetration) of the new bit is approximately two to three times that of the common bits. Compared with the common bits, the surface of the new bit has typical abrasive wear characteristics,and the metabolic rate of the diamond can be well matched to the wear rate of the matrix.

A New System to Evaluate Comprehensive Performance of Hard-Rock Tunnel Boring Machine Cutterheads

The accurate performance evaluation of a cutterhead is essential to improving cutterhead structure design and predicting project cost. Through extensive research, this paper evaluates the performance of a tunnel boring machine(TBM) cutterhead for cutting ability and slagging ability. This paper propose cutting efficiency, stability, and continuity of slagging as the evaluation indexes of comprehensive cutterhead performance. On the basis of research of true TBM engineering applications, this paper proposes a calculation method for each index. A slagging efficiency index with a ratio of the maximum di erence between the slagging amount and average slagging is established. And a slagging stability index with a ratio of the maximum slagging fluctuation and average slagging is presented. Meanwhile, a cutting efficiency index by the weighed average value of multistage rock fragmentation of a cutter’s specific energy is established. The Robbins and China Railway Construction Corporation(CRCC) cutterheads are evaluated. The results show that under the same thrust and torque, the slagging stability of the CRCC scheme is worse, but the slagging continuity of the CRCC scheme is better. The cutting ability index shows that the CRCC cutterhead is more efficient.