Multivariate statistical analysis approach for prediction of blast-induced ground vibration

Excavation of coal, overburden, and mineral deposits by blasting is dominant over the globe to date, although there are certain undesirable effects of blasting which need to be controlled. Blast-induced vibration is one of the major concerns for blast designers as it may lead to structural damage. The empirical method for prediction of blast-induced vibration has been adopted by many researchers in the form of predictor equations. Predictor equations are site specific and indirectly related to physicomechanical and geological properties of rock mass as blast-induced ground vibration is a function of various controllable and uncontrollable parameters. Rock parameters for blasting face and propagation media for blast vibration waves are uncontrollable parameters, whereas blast design parameters like hole diameter, hole depth, column length of explosive charge, total number of blast holes, burden, spacing, explosive charge per delay, total explosive charge in a blasting round, and initiation system are controllable parameters. Optimization of blast design parameters is based on site condition and availability of equipment. Most of the smaller mines have predesigned blasting parameters except explosive charge per delay, total explosive charge, and distance of blast face from surface structures. However, larger opencast mines have variations in blast design parameters for different benches based on strata condition: Multivariate predictor equation is necessary in such case. This paper deals with a case study to establish multivariate predictor equation for Moher and Moher Amlohri Extension opencast mine of India. The multivariate statistical regression approach to establish linear and logarithmic scale relation between variables to predict peak particle velocity (PPV) has been used for this purpose. Blast design has been proposed based on established multivariate regression equation to optimize blast design parameters keeping PPV within legislative limits.     

Application of soft computing in predicting rock fragmentation to reduce environmental blasting side effects

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.     

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Blasting is a widely used technique for rock fragmentation in opencast mines and tunneling projects. Ground vibration is one of the most environmental effects produced by blasting operation. Therefore, the proper prediction of blast-induced ground vibrations is essential to identify safety area of blasting. This paper presents a predictive model based on gene expression programming (GEP) for estimating ground vibration produced by blasting operations conducted in a granite quarry, Malaysia. To achieve this aim, a total number of 102 blasting operations were investigated and relevant blasting parameters were measured. Furthermore, the most influential parameters on ground vibration, i.e., burden-to-spacing ratio, hole depth, stemming, powder factor, maximum charge per delay, and the distance from the blast face were considered and utilized to construct the GEP model. In order to show the capability of GEP model in estimating ground vibration, nonlinear multiple regression (NLMR) technique was also performed using the same datasets. The results demonstrated that the proposed model is able to predict blast-induced ground vibration more accurately than other developed technique. Coefficient of determination values of 0.914 and 0.874 for training and testing datasets of GEP model, respectively show superiority of this model in predicting ground vibration, while these values were obtained as 0.829 and 0.790 for NLMR model.     

Coupling of two methods,waveform superposition and numerical,to model blast vibration effect on slope stability in jointed rock masses

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.     

花岗岩循环爆破振动衰减规律与损伤演化机理试验

为了研究岩石在循环爆破作用下的动力学响应,本文对黑云母花岗岩试块进行了小型爆破试验,利用加速度传感器和声波测试仪,分别对循环爆破荷载下质点振动衰减规律与累积损伤演化机理进行了探析,并对不同装药量下花岗岩试块的裂纹扩展与断裂形态进行了比较。结果表明:萨道夫斯基公式对室内花岗岩试块的爆破振动衰减规律具有较好的适用性,拟合相关参数都处于0.90以上;花岗岩的爆破损伤随着爆破次数的增加而增加,且损伤值随着距爆心距离（爆心距）的增加而降低,近区损伤值迅速降低,降幅约为1.46/m,而中区和远区损伤值降低相对缓慢,约为0.57/m和0.13/m;花岗岩的破坏程度和装药量有较高的关联度,当药量较低时,岩块致裂所需要的爆破次数就越大;随着药量增加到一定程度,岩块在低爆破次数下就会发生破坏;此外,还发现随着装药量的增加,试块爆后破裂的块数呈现增加趋势,如较低药量时试样破裂成2块,较高药量下破裂成3~4块。     

Evaluation of initiating system by measurement of seismic energy dissipation in surface blasting

Enhanced demand for coal and minerals in the country has forced mine operators for mass production through large opencast mines. Heavy blasting and a large amount of explosive use have led to increased environmental problems, which may have potential harm and causes a disturbance. Ground vibrations generated due to blasting operations in mines and quarries are a very important environmental aspect. It is clear that a small amount of total explosive energy is being utilized in blasting for breakage of rock mass, while the rest is being wasted. The amount of energy which is wasted causes various environmental issues such as ground vibrations, air overpressure, and fly rock. Ground vibrations caused by blasting cannot be eliminated entirely, yet they can be minimized as far as possible through a suitable blasting methodology. A considerable amount of work has been done to identify ground vibrations and assess the blast performance regarding the intensity of ground vibrations, i.e., peak particle velocity and frequency spectrum. However, not much research has done into reducing the seismic energy wasted during blasting leading to ground vibrations. In this paper, the blast-induced ground vibrations in three orthogonal directions, i.e., transverse, vertical, and longitudinal, were recorded at different distances using seismographs. An attempt has been made for the estimation of the percentage of explosive energy dissipated in the form of seismic energy with electronic and non-electric (NONEL) initiation system. signal processing techniques with the help of DADiSP software is used to study the same.     

Application of Air Decks in Production Blasting to Improve Fragmentation and Economics of an Open Pit Mine

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.     

Ground Vibration due to Blasting in Limestone Quarries

A database of ground vibration due to blasting at 27 limestone quarries, located in various parts of India, has been created. The database contains peak particle velocity (PPV), frequency, other vibration related and blast design parameters. Regression analysis of the data is carried out to derive site constants of the USBM predictor equation for individual quarries. It is found that these site constants are correlated with each other. By combining all the data, a generalised predictor equation is developed to assess and control ground vibration. In addition, mean zone of attenuation has been delineated using the predictor equations of the individual quarries. The dominant frequency of ground vibration with respect to distance and the possibility of modifying it by changing delay intervals in production blasts are also examined.     

Incremental explosive energy distribution in blasting design

Summary The increasing range of explosive types and methods of initiation available to the blasting design engineer, and the possibilities of obtaining more detailed rock property data, require improvements in the precision of blasting design methods. Average design values, such as powder factor and specific charge, have little significance where rock properties vary in any lithological section of the blast. Application of the concept of incremental explosive energy distribution will increase the design sensitivity and control over blastability variations. In this paper the use of this concept is described for different levels of complexity. These range from the simple allocation of explosive energy for large rock sections, to the use of more complex energy attentuation functions to allocate incremental specific energy levels. Procedures to develop rock fragmentation predictions from such data are also outlined.     

Application of an Expert System for the Assessment of Blast Vibration

The purpose of this article is to evaluate and predict the blast induced ground vibration using different conventional vibration predictors and artificial neural network (ANN) at a surface coal mine of India. Ground Vibration is a seismic wave that spread out from the blast hole when detonated in a confined manner. 128 blast vibrations were recorded and monitored in and around the surface coal mine at different strategic and vulnerable locations. Among these, 103 blast vibrations data sets were used for the training of the ANN network as well as to determine site constants of various conventional vibration predictors, whereas rest 25 blast vibration data sets were used for the validation and comparison by ANN and empirical formulas. Two types of ANN model based on two parameters (maximum charge per delay and distance between blast face to monitoring point) and multiple parameters (burden, spacing, charge length, maximum charge per delay and distance between blast face to monitoring point) were used in the present study to predict the peak particle velocity. Finally, it is found that the ANN model based on multiple input parameters have better prediction capability over two input parameters ANN model and conventional vibration predictors.     

爆破工程地质灾害及其防治

因爆破作用而产生的诸如岩体失稳、爆破怍用方向改变、爆破飞石、爆破地震波等爆破工程地质灾害，对工程建设和环境产生了不同程度的影响，并日益受到人们的关注。基于爆破工程地质学理论研究及生产实践，作者提出爆破工程地质灾害的基本概念，系统分析爆破工程地质灾害的形成原因、机制、条件以及爆破工程地质灾害类型。在此基础上，提出了避免或减轻产生爆破工程地质灾害的具体措施。即必须重视和加强爆破工程地质勘测研究工作，正确运用爆破岩体工程地质力学原理，分析、评价爆破工程地质条件，预测爆破效果、质量及可能发生的爆破工程地质灾害，有效控制炸药能量与爆破岩体介质之间的相互作用和效果，最大限度地避免爆破工程地质灾害的产生。     

New Prediction Models for Mean Particle Size in Rock Blast Fragmentation

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.     

Prediction of surface blast patterns in limestone quarries using artificial neural networks

This paper is an application of artificial neural networks (ANNs) in the prediction of the geometry of surface blast patterns in limestone quarries. The built model uses 11 input parameters which affect the design of the pattern. These parameters are: formation dip, blasthole diameter, blasthole inclination, bench height, initiation system, specific gravity of the rock, compressive and tensile strength, Young's modulus, specific energy of the explosive and the average resulting fragmentation size. Detailed data from a previous investigation were used to train and verify the network and predict burden and spacing of a blast. The built model was used to conduct parametric studies to show the effect of blasthole diameter and bench height on pattern geometry.     

Measurement and analysis of near-field blast vibration and damage

Summary Blast vibration and its attenuation within the rock mass immediately adjacent to a blast hole (2–15 m) were monitored for a blast hole diameter of 100 mm and a 2.4 m column of an emulsion explosive charge. Peak particle velocities calculated from the measured accelerations were compared with predictions from the charge-weight scaling law using typical site parameters which would be adopted for many far-field vibration predictions. It was found that the vibration amplitudes predicted by the conventional charge-weight scaling law are significantly lower than measured values. Strain and strain rates at different monitoring holes were calculated from experimental data. Using attenuation analysis of different frequency bands of measured acceleration signals, it was found that blast vibration attenuation between 2 m and 4 m depended not only on frequency but also on amplitude. A failure wave was postulated based on observations at the monitoring hole 2 m from the blast. A blast damage zone was evaluated using borehole camera and cross hole seismic studies. The damage zone in the rock was also analysed according to acceleration waveforms measured at different monitoring locations. The use of different techniques to measure blast damage provided an accurate assessment of the blast damage volume.     

Improvements in Blast Fragmentation Models Using Digital Image Processing

One of the fundamental requirements for being able to optimise blasting is the ability to predict fragmentation. An accurate blast fragmentation model allows a mine to adjust the fragmentation size for different downstream processes (mill processing versus leach, for instance), and to make real time adjustments in blasting parameters to account for changes in rock mass characteristics (hardness, fracture density, fracture orientation, etc). A number of blast fragmentation models have been developed in the past 40 years such as the Kuz-Ram model [1]. Fragmentation models have a limited usefulness at the present time because: 1. The input parameters are not the most useful for the engineer to determine and data for these parameters are not available throughout the rock mass. 2. Even if the input parameters are known, the models still do not consistently predict the correct fragmentation. This is because the models capture some but not all of the important rock and blast phenomena. 3. The models do not allow for 'tuning' at a specific mine site. This paper describes studies that are being conducted to improve blast fragmentation models. The Split image processing software is used for these studies [2, 3].     

Theory and Practice of Air-Deck Blasting in Mines and Surface Excavations: A Review

The mechanism by which the explosive energy is transferred to the surrounding rock mass is changed in air-deck blasting. It allows the explosive energy to act repeatedly in pulses on the surrounding rock mass rather than instantly as in the case of concentrated charge blasting. The air-deck acts as a regulator, which first stores energy and then releases it in separate pulses. The release of explosion products in the air gap causes a decrease in the initial bore hole pressure and allows oscillations of shock waves in the air gap. The performance of an air-deck blast is basically derived from the expansion of gaseous products and subsequent multiple interactions between shock waves within an air column, shock waves and stemming base and shock waves and hole bottom. This phenomenon causes repeated loading on the surrounding rock mass by secondary shock fronts for a prolonged period. The length of air column and the rock mass structure are critical to the ultimate results. Several attempts have been made in the past to study the mechanism of air-deck blasting and to investigate its effects on blast performance but a clear understanding of the underlying mechanism and the physical processes to explain its actual effects is yet to emerge. In the absence of any theoretical basis, the air-deck blast designs are invariably carried out by the rules of thumb. The field trials of this technique in different blast environments have demonstrated its effectiveness in routine production blasting, pre-splitting and controlling over break and ground vibrations etc. The air-deck length appropriate to the different rock masses and applications need to be defined more explicitly. It generally ranges between 0.10 and 0.30 times the original charge length. Mid column air-deck is preferred over the top and bottom air-decks. Top air-deck is used especially in situations, which require adequate breakage in the stemming region. The influence of air-deck location within the hole on blast performance also requires further studies. This paper reviews the status of knowledge on the theory and practice of air-deck blasting in mines and surface excavations and brings out the areas for further investigation in this technique of blasting.     

舟山灌门水道海底隧道钻爆法施工稳定性分析

以舟山灌门水道海底隧道为背景,依据地质资料,选取隧道典型横断面来研究钻爆法施工时围岩的稳定性。由典型横断面的几何参数和地质资料构建数值计算模型,采用国际上常用的计算模式模拟爆破荷载,根据FLAC3D动态计算的特点,将爆破荷载以等效应力的方式加载于模拟炮孔之上。数值计算结果表明,各关键点的位移、振动速度、加速度-时程曲线均满足隧道爆破变形规律,且振动速度峰值均小于规范要求临界值,爆破作用影响范围小于岩石覆盖层建议厚度,验证了岩层覆盖厚度建议值和爆破方案的合理性。最后,为了弄清岩石覆盖厚度和炸药量对围岩稳定性的影响,给出了不同岩石覆盖厚度和炸药量情况下的计算结果。所得结论对后续施工和类似工程具有一定的指导意义。     

渗透压力作用下加锚裂隙岩体围岩稳定性研究

岩体中裂隙水的存在加剧了岩体结构围岩损伤;锚杆作为岩体工程的重要支护手段,被广泛应用于岩体加固工程中。结合无损伤材料的柔度张量的概念,用裂隙附加柔度张量来表示裂隙对岩体的损伤影响;引入渗透压力附加柔度张量的概念来定义渗透压力对裂隙岩体强度的损伤影响;利用附加刚度来反映锚杆对裂隙岩体的加固作用,附加刚度求逆即得柔度张量。对渗透压力作用下锚固裂隙岩体渗流场与损伤场相互作用及耦合机制进行了深入研究;基于能量互易定理,自洽理论等,分别在压剪和拉剪应力状态下推导了渗透压力作用下加锚裂隙岩体等效损伤模型,建立了相应的计算方法,应用半解耦方法对理论模型进行了有限元程序化。在有限元程序中,将渗透体积力化为等效节点力,参与各单元间应力调整且表现为岩体变形过程中刚度的降低;锚杆锚固力等效为单元节点力,并体现为岩体整体变形刚度的提高。结合工程实际,着重讨论渗透压力作用对隧道围岩稳定性的影响。分析表明,渗透压力对岩体围岩变形破坏及稳定性的影响是不可忽略的。     

Newspapers as a validation proxy for GIS modeling in Fujairah,United Arab Emirates: identifying flood-prone areas

Prediction and control of blast-induced ground vibration is a matter of concern in mining industry since long. Several approaches ranging from scaled distance regression, different numerical methods to wave superimposition theories have been tried by many researchers for better prediction and control of blast-induced ground vibration. Signature hole analysis is one of the popular simulation methods to predict the ground vibration generated due to production blast. It superimposes the recorded signature hole waveform using a computer program to predict the production blast-induced vibration. The technique inputs the designated time of detonation of each hole and superimposes the waves generated by each hole to predict the nearest value of peak particle velocity and frequency of blast-induced ground vibration. Although a very useful approach, it requires a computer program to simulate the linear superimposition of waveforms. The simulation is not possible for every blast as it takes time and also is difficult for field engineers to simulate every time, whereas it is always easy for blasting engineers to adapt and use an empirical equation/approach for prediction and control of blast-induced ground vibration than simulation. In this paper, an attempt has been made to develop an innovative and simplified analytical approach of signature hole analysis. The simplified sinusoidal wave equation is obtained from recorded signature hole ground vibration waveform properties and is superimposed mathematically according to the multi-hole blast design to predict the production blast-induced ground vibrations. The validation of the developed approach was done in three different sites, and up to 15% more accuracy in prediction of the blast, vibrations are achieved in comparison with signature hole analysis prediction.

     

Investigation of the site-specific character of blast vibration prediction

A new site-specific vibration prediction equation was developed based on site measurement performed in a sandstone quarry. Also, several vibration prediction equations were compiled from the blasting literature and used to predict ground vibration for the studied quarry. By this way, site-specific equation created by regression analysis and the equations obtained from the blasting literature were compared in terms of prediction accuracy. Some of the equations obtained from the literature made better predictions than the site-specific equation created for the studied quarry. The prediction equations were grouped, and the effects of the rock formation and mine type on the prediction accuracy were investigated. Suitable error measures for evaluation of ground vibration prediction were examined in detail. A new general prediction equation was created using site factors (K, β) of the examined studies. The general equation was created using 17 prediction equations reported by blast researchers. Prediction capability of the general equation was found to be strong. Diversity of the blast data is one of the strongest features of the general equation.