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1.
In the blasting operation, risk of facing with undesirable environmental phenomena such as ground vibration, air blast, and flyrock is very high. Blasting pattern should properly be designed to achieve better fragmentation to guarantee the successfulness of the process. A good fragmentation means that the explosive energy has been applied in a right direction. However, many studies indicate that only 20–30 % of the available energy is actually utilized for rock fragmentation. Involvement of various effective parameters has made the problem complicated, advocating application of new approaches such as artificial intelligence-based techniques. In this paper, artificial neural network (ANN) method is used to predict rock fragmentation in the blasting operation of the Sungun copper mine, Iran. The predictive model is developed using eight and three input and output parameters, respectively. Trying various types of the networks, it was found that a trained model with back-propagation algorithm having architecture 8-15-8-3 is the optimum network. Also, performance comparison of the ANN modeling with that of the statistical method was confirmed robustness of the neural networks to predict rock fragmentation in the blasting operation. Finally, sensitivity analysis showed that the most influential parameters on fragmentation are powder factor, burden, and bench height.  相似文献   

2.
Flyrock is one of the most hazardous events in blasting operation of surface mines. There are several empirical methods to predict flyrock. Low performance of such models is due to complexity of flyrock analysis. Existence of various effective parameters and their unknown relationships are the main reasons for inaccuracy of the empirical models. Presently, application of new approaches such as artificial intelligence is highly recommended. In this paper, an attempt has been made to predict and control flyrock in blasting operation of Sangan iron mine, Iran incorporating rock properties and blast design parameters using artificial neural network (ANN) method. A three-layer feedforward back-propagation neural network having 13 hidden neurons with nine input parameters and one output parameter were trained using 192 experimental blast datasets. It was also observed that in ascending order, blastability index, charge per delay, hole diameter, stemming length, powder factor are the most effective parameters on the flyrock. Reducing charge per delay caused significant reduction in the flyrock from 165 to 25 m in the Sangan iron mine.  相似文献   

3.
Most blast fragmentation models assume the rock mass properties. explosive properties and blast design variables to be constants and uniformly distributed within a blast. However, in reality all these input variables vary within a blast resulting in variation in the resulting fragmentation size distribution. A stochastic modelling approach is introduced in this paper to quantify this variation. This technique takes the input variables as statistical distributions rather than constants and through several thousand iterations, generates a statistical representation of the expected fragmentation resulting from a poduction blast. A case study of three production blasts from a large open pit mine are presented and the modelled fragmentation 'envelope' shows good agreement with the fragmentation 'envelope' estimated from Split image analysis. The various blast-related parameters influence different parts of the fragmentation distribution, e.g., rock strength and explosive velocity of detonation have most impact on the fines. The technique is used to identify the parameters that have the greatest influence on various size fractions. Such an analysis will be useful to direct resources to efficiently minimise the variation.  相似文献   

4.
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.  相似文献   

5.
Over the past 18 months the De Beers Consolidated Mines Ltd operations have made a concerted effort to move away from using the traditional shock tube initiating systems. These systems are being systematically replaced by the use of electronic delay detonators (EDD). Various trials were conducted in both host rock and kimberlite rock masses to improve tunnel advance as well as to optimise delay timing during trough openings [1-3]. The high cost of EDD's, when compared with traditional initiation systems, led to a number of detailed studies being conducted on the mines where EDD's were being used. These studies aimed to quantify the additional benefits when blasting with electronic detonators. The studies showed that the change was justified on the basis of increased quality control and reliability gained through the use of EDD's. However, these benefits attract other related benefits, like fragmentation control, and backbreak reductions. When compared to the shock tube initiating systems the increased development face advance and the reduction of oversize during production blasting using EDDs, compared favourably to the less costly systems. As blasting engineers gained experience and confidence in the use of the system bigger blasts were initiated in mass under-cut blasts and slot raise development, by using multiple hole firing and second delay periods between holes. In the open pit and sublevel open stope mining methods the control of the fragmentation distribution and the effect of the mass of explosive detonated during a blast is detrimental to the loading and hauling production rates and the stability of the rock mass behind the blast. With a stable rock mass the bench cutting can be executed to establish steeper overall slope angles leading to large cost savings due to a reduction in waste stripping. It is the purpose of this paper to indicate through quantification that the use of the EDDs as an initiating system improves all-round blasting performances and assists in meeting customer requirements. The customer being the ore treatment plant.  相似文献   

6.
Blasting is the primary comminution process in most mining operations. This process involves the highly complex and dynamic interaction between two main components. The first is the detonating explosive and the second is the rock mass into which the explosive is loaded. The mechanical properties of the rock material (such as dynamic strength, tensile strength, dynamic modulus and fracture toughness) are important considerations in understanding the blasting process. However, it is the characteristics of the geological defects (joints, foliation planes, bedding planes) within the rock mass that ultimately determine how effectively a blast performs in terms of fragmentation, all else being equal. The defect characteristics include, but are not limited to, their orientation, spacing, and mechanical properties. During the blasting process, some of the geotechnical characteristics of the rock mass are substantially changed. From the blasting outcome point of view, the most notable and important is the change in fragment size distribution that the rock mass undergoes. The pre-blast in situ defect-bounded block size distribution is transformed into the post-blast muckpile fragment size distribution. Consequently, it is fundamental to our understanding of and ability to predict the blasting process that both the blastability of a rock mass and its transformation into the fragment size distribution can be appropriately quantified.  相似文献   

7.
One of the most important aims of blasting in open pit mines is to reach desirable size of fragmentation. Prediction of fragmentation has great importance in an attempt to prevent economic drawbacks. In this study, blasting data from Meydook mine were used to study the effect of different parameters on fragmentation; 30 blast cycles performed in Meydook mine were selected to predict fragmentation where six more blast cycles are used to validate the results of developed models. In this research, mutual information (MI) method was employed to predict fragmentation. Ten parameters were considered as primary ones in the model. For the sake of comparison, Kuz-Ram empirical model and statistical modeling were also used. Coefficient of determination (R 2), root mean square error (RMSE), and mean absolute error (MAE) were then used to compare the models. Results show that MI model with values of R 2, RMSE, and MAE equals 0.81, 10.71, and 9.02, respectively, is found to have more accuracy with better performance comparing to Kuz-Ram and statistical models.  相似文献   

8.
Backbreak is an undesirable phenomenon in blasting operations. It can cause instability of mine walls, falling down of machinery, improper fragmentation, reduced efficiency of drilling, etc. The existence of various effective parameters and their unknown relationships are the main reasons for inaccuracy of the empirical models. Presently, the application of new approaches such as artificial intelligence is highly recommended. In this paper, an attempt has been made to predict backbreak in blasting operations of Soungun iron mine, Iran, incorporating rock properties and blast design parameters using the support vector machine (SVM) method. To investigate the suitability of this approach, the predictions by SVM have been compared with multivariate regression analysis (MVRA). The coefficient of determination (CoD) and the mean absolute error (MAE) were taken as performance measures. It was found that the CoD between measured and predicted backbreak was 0.987 and 0.89 by SVM and MVRA, respectively, whereas the MAE was 0.29 and 1.07 by SVM and MVRA, respectively.  相似文献   

9.
Blast design is a critical factor dominating fragmentation and cost of actual bench blasts. However, due to the varying nature of rock properties and geology as well as free surface conditions, reliable theoretic formulae are still unavailable at present and in most cases blast design is carried out by personal experience. As an effort to find a more scientific and reliable tool for blast design, a computer-aided bench blast design and simulation system, the BLAST-CODE model, is developed for Shuichang surface mine, Mining Industry Company of the Capital Iron and Steel Corporation Beijing. The BLAST-CODE model consists of a database representing geological and topographical conditions of the mine and the modules Frag + and Disp + for blast design and prediction of resultant fragmentation and displacement of rock mass. The two modules are established in accordance with cratering theory qualitatively and modified quantitatively by regression of the data collected from 85 bench blasting practices conducted in 3 mines of the Shuichang surface mine. Blasting parameters are selected based upon quantitative and comprehensive evaluation on the effect of the factors such as rock properties, geology, free surface conditions and detonation characteristics of the explosive products in use. In order to ensure practicality and reliability of the system, the BLAST-CODE model allows automatic adjustment to the selected parameters such as burden B and spacing S as well as explosive charge amount Q of any blasthole under irregular topographic and/or varying blastability conditions of the rock mass to be blasted. Simulation of the BLAST-CODE model includes prediction of fragmentation and displacement that are demonstrated in terms of swell factor, characteristic rock size x c and size distribution coefficient n by Rossin-Ramler's equation, and 3-dimentional muck pile profile. The BLAST-CODE model also permits interactive parameter selection based on comparison of the predicted fragmentation and displacement as well as the cost for drilling, explosives, and accessories until the most effective option can be selected.  相似文献   

10.
New Prediction Models for Mean Particle Size in Rock Blast Fragmentation   总被引：2，自引：1，他引：1  
The paper refers the reader to a blast data base developed in a previous study. The data base consists of blast design parameters, explosive parameters, modulus of elasticity and in situ block size. A hierarchical cluster analysis was used to separate the blast data into two different groups of similarity based on the intact rock stiffness. The group memberships were confirmed by the discriminant analysis. A part of this blast data was used to train a single-hidden layer back propagation neural network model to predict mean particle size resulting from blast fragmentation for each of the obtained similarity groups. The mean particle size was considered to be a function of seven independent parameters. An extensive analysis was performed to estimate the optimum value for the number of units for the hidden layer for each of the obtained similarity groups. The blast data that were not used for training were used to validate the trained neural network models. For the same two similarity groups, multivariate regression models were also developed to predict mean particle size. Capability of the developed neural network models as well as multivariate regression models was determined by comparing predictions with measured mean particle size values and predictions based on one of the most applied fragmentation prediction models appearing in the blasting literature. Prediction capability of the trained neural network models as well as multivariate regression models was found to be strong and better than the existing most applied fragmentation prediction model. Diversity of the blasts data used is one of the most important aspects of the developed models.  相似文献   

11.
In blasting with air decks, repeated oscillation of shock waves within the air gap increases the time over which it acts on the surrounding rock mass by a factor at between 2 and 5. The ultimate effect lies in increasing the crack network in the surrounding rock and reducing the burden movement. Trials of air deck blasting in the structurally unfavourable footwall side of an open pit manganese mine has resulted in substantial improvements in fragmentation and blast economics. Better fragmentation resulted in improved shovel loading efficiency by 50–60%. Secondary blasting was almost eliminated. Use of ANFO explosive with this technique reduced explosive cost by 31.6%. Other benefits included reductions in overbreak, throw and ground vibration of the order of 60–70, 65–85 and 44% respectively. This paper reviews the theory of air deck blasting and describes in detail the air deck blast trials conducted in a manganese open pit mine in India. The blast performance data have been analysed to evaluate the benefits of air decking over conventional blasting.  相似文献   

12.
Explosion gas plays an important role in rock mass fragmentation and cast in rock blasting. In this technical note, the discontinuous deformation analysis method is extended for bench rock blasting by coupling the rock mass failure process and the penetration effect of the explosion gas based on a generalized artificial joint concept to model rock mass fracturing. By tracking the blast chamber evolution dynamically, instant explosion gas pressure is derived from the blast chamber volume using a simple polytropic gas pressure equation of state and loaded on the blast chamber wall. A bench blasting example is carried out. The blast chamber volume and pressure time histories are obtained. The rock failure and movement process in bench rock blasting is reproduced and analysed.  相似文献   

13.
Most blasting operations are associated with various forms of energy loss, emerging as environmental side effects of rock blasting, such as flyrock, vibration, airblast, and backbreak. Backbreak is an adverse phenomenon in rock blasting operations, which imposes risk and increases operation expenses because of safety reduction due to the instability of walls, poor fragmentation, and uneven burden in subsequent blasts. In this paper, based on the basic concepts of a rock engineering systems (RES) approach, a new model for the prediction of backbreak and the risk associated with a blast is presented. The newly suggested model involves 16 effective parameters on backbreak due to blasting, while retaining simplicity as well. The data for 30 blasts, carried out at Sungun copper mine, western Iran, were used to predict backbreak and the level of risk corresponding to each blast by the RES-based model. The results obtained were compared with the backbreak measured for each blast, which showed that the level of risk achieved is in consistence with the backbreak measured. The maximum level of risk [vulnerability index (VI) = 60] was associated with blast No. 2, for which the corresponding average backbreak was the highest achieved (9.25 m). Also, for blasts with levels of risk under 40, the minimum average backbreaks (<4 m) were observed. Furthermore, to evaluate the model performance for backbreak prediction, the coefficient of correlation (R 2) and root mean square error (RMSE) of the model were calculated (R 2 = 0.8; RMSE = 1.07), indicating the good performance of the model.  相似文献   

14.
Blasting has been the most frequently used method for rock breakage since black powder was first used to fragment rocks, more than two hundred years ago. This paper is an attempt to reassess standard design techniques used in blasting by providing an alternative approach to blast design. The new approach has been termed asymmetric blasting. Based on providing real time rock recognition through the capacity of measurement while drilling (MWD) techniques, asymmetric blasting is an approach to deal with rock properties as they occur in nature, i.e., randomly and asymmetrically spatially distributed. It is well accepted that performance of basic mining operations, such as excavation and crushing rely on a broken rock mass which has been pre conditioned by the blast. By pre-conditioned we mean well fragmented, sufficiently loose and with adequate muckpile profile. These muckpile characteristics affect loading and hauling [1]. The influence of blasting does not end there. Under the Mine to Mill paradigm, blasting has a significant leverage on downstream operations such as crushing and milling. There is a body of evidence that blasting affects mineral liberation [2]. Thus, the importance of blasting has increased from simply fragmenting and loosing the rock mass, to a broader role that encompasses many aspects of mining, which affects the cost of the end product. A new approach is proposed in this paper which facilitates this trend 'to treat non-homogeneous media (rock mass) in a non-homogeneous manner (an asymmetrical pattern) in order to achieve an optimal result (in terms of muckpile size distribution).' It is postulated there are no logical reasons (besides the current lack of means to infer rock mass properties in the blind zones of the bench and onsite precedents) for drilling a regular blast pattern over a rock mass that is inherently heterogeneous. Real and theoretical examples of such a method are presented.  相似文献   

15.
Summary The purpose of this study is to statistically correlate the fragmentation gradient () and average fragment size () with the blasting test parameters for rock masses having different characteristics. Blasting tests were conducted in limestone exposed during the highway construction between Tarsus and Pozanti (Turkey). Three test sites were classified as poor rock, good rock, and very good rock according to their RMR ratings. The selected blasting test parameters that affect the degree of fragmentation were burden, bench height and ANFO charge. After each blast, the muckpiles were screened and fragment size distribution graphs were plotted. Yates' method was applied for experimental design and analysis of variance. The single and combined effects of blasting test parameters were analyzed through the Yates' tables and significant and non-significant treatment combinations were determined for different rock masses. Some conclusions drawn from this research are: 1. The increase of RMR ratings promotes fragmentation, hence, increases blasting efficiency. 2. In rock masses of low RMR ratings, the volume of broken material is large, but fragmentation into small sizes is low. The opposite is true for rock masses of high RMR ratings. 3. The length of charge column is the significant factor affecting the average fragment size regardless the type of rock mass and is more significant in very good quality rock mass.  相似文献   

16.
Drilling and blasting is a major technology in mining since it is necessary for the initial breakage of rock masses in mining. Only a fraction of the explosive energy is efficiently consumed in the actual breakage and displacement of the rock mass, and the rest of the energy is spent in undesirable effects, such as ground vibrations. The prediction of induced ground vibrations across a fractured rock mass is of great concern to rock engineers in assessing the stability of rock slopes in open pit mines. The waveform superposition method was used in the Gol-E-Gohar iron mine to simulate the production blast seismograms based upon the single-hole shot vibration measurements carried out at a distance of 39 m from the blast. The simulated production blast seismograms were then used as input to predict particle velocity time histories of blast vibrations in the mine wall using the universal distinct element code (UDEC). Simulated time histories of particle velocity showed a good agreement with the measured production blast time histories. Displacements and peak particle velocities were determined at various points of the engineered slope. The maximum displacement at the crest of the nearest bench in the X and Y directions was 26 mm, which is acceptable in regard to open pit slope stability.  相似文献   

17.
基于TCK损伤本构的岩石爆破效应数值模拟   总被引：3，自引：0，他引：3  
王志亮  郑明新 《岩土力学》2008,29(1):230-234
脆性岩石在爆破载荷下的动态破碎行为是工程技术人员所关心的,采用数值法预估岩体破裂范围和损伤大小对施工安全具有重大意义,其中合理的岩石损伤模型是关键。假设岩体破坏近似服从Mises屈服准则,且考虑到岩体的应变硬化特性,把Taylor-Chen-Kuszmaul（TCK）模型中的拉裂损伤演化方程和材料双线性、弹塑性本构耦合到一起,并简洁地嵌入到有限元分析软件LS-DYNA中,通过半无限岩体中柱形药包爆破实例验证了其合理性与准确性。对球形药包爆破问题也进行了数值分析。该损伤模型及其数值模拟在工程中具有一定的参考价值。  相似文献   

18.
Tunnel blasting techniques in difficult ground conditions   总被引：1，自引：0，他引：1  
Summary The quality of tunnelling can be improved by proper blast design which takes into account the rock mass conditions. The effects of different rock mass properties on tunnel blast performance need to be assessed. The strength of the formation and joint orientation critically affected fragmentation and overbreak in a model study of blasting. Similar effects were noted in situ when the performance of a blast pattern in different rock mass conditions in the Tandsi inclines (Bihar, India) were analysed. Accordingly, the on-going blast pattern was modified for the poor ground conditions prevailing in the rest of the inclines. Improved fragmentation and smooth profile were obtained as a result; the rate of drivage improved considerably and the cost of excavation was reduced. Based on the observations in the model studies and the investigations at Tandsi, some guidelines for optimum blast design in difficult ground conditions are suggested.  相似文献   

19.
The environmental effects of blasting must be controlled in order to comply with regulatory limits. Because of safety concerns and risk of damage to infrastructures, equipment, and property, and also having a good fragmentation, flyrock control is crucial in blasting operations. If measures to decrease flyrock are taken, then the flyrock distance would be limited, and, in return, the risk of damage can be reduced or eliminated. This paper deals with modeling the level of risk associated with flyrock and, also, flyrock distance prediction based on the rock engineering systems (RES) methodology. In the proposed models, 13 effective parameters on flyrock due to blasting are considered as inputs, and the flyrock distance and associated level of risks as outputs. In selecting input data, the simplicity of measuring input data was taken into account as well. The data for 47 blasts, carried out at the Sungun copper mine, western Iran, were used to predict the level of risk and flyrock distance corresponding to each blast. The obtained results showed that, for the 47 blasts carried out at the Sungun copper mine, the level of estimated risks are mostly in accordance with the measured flyrock distances. Furthermore, a comparison was made between the results of the flyrock distance predictive RES-based model, the multivariate regression analysis model (MVRM), and, also, the dimensional analysis model. For the RES-based model, R 2 and root mean square error (RMSE) are equal to 0.86 and 10.01, respectively, whereas for the MVRM and dimensional analysis, R 2 and RMSE are equal to (0.84 and 12.20) and (0.76 and 13.75), respectively. These achievements confirm the better performance of the RES-based model over the other proposed models.  相似文献   

20.
The influence of air deck blasting on blast performance and blast economics and its feasibility has been studied in the production blasting of soft and medium strength sandstone overburden rocks in an open pit coal mine in India. The air deck blasting technique was very effective in soft and medium strength rocks. Its main effects resulted in reducing fines, in producing more uniform fragmentation and in improving blast economics. The fines were reduced by 60–70% in homogeneous sandstones. Oversize boulders were reduced by 80% and shovel loading efficiency was improved by 20–40% in blocky sandstones. The explosive cost was reduced by 10–35% dependent on the type of rock mass. Throw, backbreak and ground vibration were reduced by 10–35%, 50–80% and 30–94% respectively. For a particular rock mass and blast design environment, air deck length (ADL) significantly influenced the fragmentation. ADL as represented by air deck factor (ADF) in the range of 0.10–0.35 times the original charge length (OCL) produced optimum results. ADF beyond 0.35 resulted in poor fragmentation and in inadequate burden movement.  相似文献   

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