Modelling the Impact of Rockmass and Blast Design Variation on Blast Fragmentation

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.     

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.     

A Practical Procedure for the Measurement of Fragmentation by Blasting by Image Analysis

Summary. The operation of a digital image analysis system in a limestone quarry is described. The calibration of the system, required in order to obtain moderately reliable fragmentation values, is done from muckpile sieving data by tuning the image analysis software settings so that the fragmentation curve obtained matches as close as possible the sieving. The sieving data have also been used to extend the fragment size distribution curves measured to sizes below the system’s optical resolution and to process the results in terms of fragmented rock, discounting the material coming from a loose overburden (natural fines) that is cast together with the fragmented rock. Automatic and manual operation modes of the image analysis are compared. The total fragmentation of a blast is obtained from the analysis of twenty photographs; a criterion for the elimination of outlier photographs has been adopted using a robust statistic. The limitations of the measurement system due to sampling, image processing and fines corrections are discussed and the errors estimated whenever possible. An analysis of consistency of the results based on the known amount of natural fines is made. Blasts with large differences in the amount of fines require a differentiated treatment, as the fine sizes tend to be the more underestimated in the image analysis as they become more abundant; this has been accomplished by means of a variable fines adjustment factor. Despite of the unavoidable errors and the large dispersion always associated with large-scale rock blasting data, the system is sensitive to relative changes in fragmentation.     

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].     

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.     

Tunnel blasting techniques in difficult ground conditions

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.     

Random Forest Tree Based Approach for Blast Design in Surface Mine

Blasting is one of the primary mining operations for extracting minerals and ores however, if not designed properly, may have a varying degree of environmental and socio-economic impact in and around mining areas. In Indian mining industry, blast designs are fundamentally based on the experience and capability of the blasting crew and its assessment is more qualitative in nature, based on conventional trial and error basis. With the change in site geology and geotechnical parameters, the blast design parameters also require alterations, which can be standardized with the development of an intelligent system such as neural network. In this paper, the concept of artificial neural network and random forest algorithm has been used for better blast designs. Over 120 blast results from an opencast coal mine have been used for prediction of burden and energy factor with blast hole diameter, bench height to stemming ratio, nature of strata and average fragment size as input parameters. Out of 120 data sets 85 data sets recorded at a surface coal mine was used to train the model and 20 for the validation. Co-efficient of determination and root mean square error was chosen as the indicators to identify the optimum neural network and random forest model. The root mean square values obtained for energy factor is 0.153 while it is 0.1947 for burden. Similarly, the RMSE values obtained using random forest tree algorithm is 0.48 for burden while 50.76 for energy factor. The results revealed that random forest tree network system has potential to design better blast that is not generic and can be a potential tool for blasting engineers to design optimum blast for the mines.     

Optimum Blasting? Is it Minimum Cost Per Broken Rock or Maximum Value Per Broken Rock?

In most mining operations the ore undergoes several processes such as drilling, blasting, loading, hauling, crushing, grinding and liberation to become the final salable product. Drilling and blasting is an important step in this process chain and it's results such as fragmentation, muckpile shape and looseness, dilution, damage and rock softening effect the efficiency of downstream processes. The value created per ton of broken ore is the difference between the price it commands when sold as the final product and the cost to produce it. Traditionally, the total process in the mining industry is classified into two groups as mining and milling. These are managed as separate cost centres inspite of the interdependency. Each process has a budget and production target and emphasis is usually on maximising production (tons) and minimising cost rather than the overall profitability of the whole business unit. The efficiency of each process is considered to be satisfactory as long as they are within budget and meet the production targets. The mine and mill managers usually try to optimise each process independently rather than the entire process. This paper discusses the potential pitfalls of decreasing the drilling and blasting cost per ton of broken rock without considering its impact on downstream processes. It introduces a holistic approach to blast optimisation by identifying and measuring the leverage that blast results have on different downstream processes and then optimising the blast design to achieve the results that maximise the overall profitability rather than just minimising the drilling and blasting costs. This paper demonstrates the benefits of such a holistic approach to blasting based on computer model simulations and field studies from metal and open cut coal mining.     

A two-dimensional kinematic model for predicting muckpile shape in bench blasting

Summary Most existing models of blasting are stress-based and involve many fundamental parameters difficult or impossible to measure in practice. Even a single prediction with such models takes large quantities of computer time, so that calibration becomes a major impediment to their practical use.The model in this paper is based on a simple kinematic approach to modelling muckpile formation. This has the advantage of relative simplicity, while still reflecting the essence of the blasting displacement process. Because of the simple implementation, the model can be calibrated against field data in a straightforward manner and then used for predictions at the same site. The inputs to the model are simply the blast design parameters. The output of the model is a muckpile cross-section, within which contours of diggability or distribution of materials can also be calculated. Case studies have shown that, provided the model is calibrated to the site condition, it will give accurate predictions for altered blast designs.     

The BLAST-CODE model - A Computer-Aided Bench Blast Design and Simulation System

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.     

Prediction of in-situ block size distributions with reference to armourstone for breakwaters

Understanding a quarry in terms of its potential for breakwater construction materials presents a special challenge for the engineering geologist. Unlike blasting in aggregates and mining operations, optimisation of the extraction process has a focus on the potential for production of large blocks for armourstone. These blocks weighing many tonnes are used for cover layers to resist wave action. The quarry-run is used for breakwater core. If the quarry has been developed as a source of materials dedicated to a breakwater construction project, the success of the project depends greatly on the blasting and production of rock sizes that are required and the avoidance of leaving a massive quantity of unused materials behind in the quarry after project completion. Prediction of in-situ block sizes such as from joint spacing data, provides the most critical input for the prediction of the blast pile block size distribution (BBSD), which in turn is a vital early design input if the constructed breakwater is to be economical as well as effective.This paper is part of a series of papers that introduces the coastal engineering motivation for this work on engineering geology, giving reasons why the prediction of the fragmentation curve of the blast products in a dedicated quarry is of such economic importance for breakwater projects. The first step towards blasted block size distribution (BBSD) prediction is the prediction of the in-situ block sized distribution (IBSD), the main subject of this paper. Drawing together research methods from the 1990s and the rock mechanics principles of discontinuity analysis, a practical step by step methodology for IBSD assessment that includes approaches that are not reliant on specialised computer software is presented. Continuing on the practical theme, a new extension of the volumetric joint count approach is suggested for IBSD prediction for the case when sparse borehole data is all that is available. A case study of IBSD assessment and the associated BBSD and blast assessment is presented from a Carboniferous limestone quarry. For clarity, details of blast design and yield curve prediction that are recommended for use in the context of armourstone production, have been presented in a companion paper. The Rosin-Rammler equation is used as an example form for the BBSD prediction of a dedicated quarry and the potential for breakwater project optimisation is illustrated. The final section sets out a method for directly comparing yield curves together with the demand for materials set by the breakwater design. On the same plot, sizes where there is a relative shortfall in production can be identified. The dependence of effective breakwater design on accurate quarry yield prediction and quarry blasting performance is discussed.     

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.     

Further Field Applications of Electronic Detonator Technology

The increasing use of the Daveytronic digital programmable detonators is continuing to yield data reinforcing earlier studies concluding that accurate timing will provide substantial performance and economic benefits. This study quantifies performance increases as they relate to fragmentation, excavation, vibration control and productivity in a limestone aggregate mining operation. High levels of field controls were adhered to during the drilling and blasting process as they related to blast design, bench preparation, pattern layout, drilling and blasthole loading. Following each blast, the fragmentation composite of the post-blast muckpile was quantified. The excavation and crushing procedures were then studied to quantify any down stream advantages due to improvements in fragmentation. This study will help provide the industry with more information as to the advantages of high accuracy electronic blasting systems over conventional pyrotechnic systems.     

Variable Energy Explosives for Soft Ground Blasting

A range of bulk explosives, the NOVALITE range hay been specifically developed for soft ground blasting. These explosives can be used in both wet and dry blasting conditions, range in density from 0.3-1.2 g/cc and range in VoD from 2-4.5 km/s. This range of explosives hay the potential to be tailored to ground type and is predicted to be suitable for a variety of applications which include: blasting in soft to medium overburden, coal blasting, wall control, and low vibration blasting. Trials have been conducted in several applications with encouraging results. Several cast/throw blasts have been conducted with these products partially replacing either ANFO or Heavy ANFO. The results from the blast have been equivalent in cast (per cent) and at reduced cost per unit volume. These products have also been used in presplit blasting and have again achieved equivalent or better results when compared to conventional presplit blasting at a lower cost per unit volume. This product has also been used in a vibration sensitive area replacing traditional explosive products, and generating excellent fragmentation and digging whilst maintaining vibration limits. This new range of products, NOVALITE, has shown great potential in many applications either reducing cost per unit volume, improving wall quality or improving productivity in environmentally sensitive areas.     

A Blind Comparison Between Results of Four Image Analysis Systems Using a Photo-Library of Piles of Sieved Fragments

Four image analysis systems for measuring rock fragmentation: FragScan, PowerSieve®, Split and WipFrag, have been compared under conditions necessary to provide an objective though limited assessment of their capabilities. The analysis of results is based on a sample of ten photographs taken from a series of photographs of controlled artificial muckpiles. These were created from dumping a blended mixture of sieved samples of limestone aggregate, in order to create a range of near perfect Rosin-Rammler sieve size distributions. Results from the various systems are compared with sieved results using both histogram and cumulative forms, with and without fines corrections in the case of Split and Wipfrag. Statistical indicators are evaluated to examine the match between system prediction values and sieving values. Commentaries on the results by the inventors of each system have been incorporated. All four systems were found to perform both well in some cases and poorly in others. From a detailed examination of the results, some insight into the strengths and weaknesses of the various systems is presented.     

Prediction of blasting-induced fragmentation in Meydook copper mine using empirical,statistical, and mutual information models

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.     

Using Electronic Detonators to Improve All-Round Blasting Performances

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.     

Geoindicators for tropical urbanization

The urban population of the developing countries, which are almost entirely within the tropics and subtropics, increased from 286 to 1,515 million between 1950 and 1990. This figure is expected to reach 4 billion by 2025. Certain major cities (Mexico City, Bombay, São Paulo, etc.) are expected to grow to extremely large sizes. The major physical changes that occur with urbanization can be summarized as changes in hydrology, geomorphology, climate, vegetation, and air and water quality. The intensity and rapidity of such changes require a careful, but urgent assessment of the environmental modification. The tropical environment tends to magnify the environmental impact of urbanization. Geoindicators can be used for the measurement of a number of changes of this nature. This paper presents a selection of geoindicators that could be used to measure such impacts. The geoindicators have been selected according to (1) their effectiveness in measuring environmental impacts and (2) the type of data that is required for their use. Shortage of quantitative information is a common problem for tropical cities. In addition, certain types of geoindicators need to be highlighted for cities in specific types of location such as deltas or coastal plains, steep slopes, or in proximity to convergent or transverse plate margins. The projection, that in another 50 years about half of the population of tropical countries will be urban, adds urgency to this venture.     

A Statistical Analysis of Fragmentation After Single Hole Bench Blasting

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.     

Controlled blasting in a limestone mine using electronic detonators: A case study

Except for very deep-seated deposits, open cast mining method has been recognized as the safest and most productive mode for mining minerals. Ever growing demand in minerals and coal has compelled the mine operators to increase the size of mine, which has resulted in an increasing trend towards large capacity open cast projects. Explosives and blasting techniques play a significant role in efficient opencast mining operations. There have been constant technological developments towards safer, faster, economical and more efficient blasting systems. Further, globally increased competitiveness has necessitated to carryout blasts in such a way that the desired degree of fragmentation is achieved in the primary blast, with minimum undesired side effects such as ground vibration, air blast/noise, flyrock, generation of oversize boulders, formation of toe, and over break or back break. Hence, the ultimate objective of the blasting engineer is to ensure that the blasts are carried out in an eco-friendly manner. This paper presents a case study of limestone mine where a controlled blasting was conducted near a green structure of wagon tippler (at 2 m) being constructed for foundation work of belt conveyor as the mine management wants to double the existing production. This paper deals with controlled blast design and its implementation using electronic detonators with signature hole technique.