MASTER'S THESIS. Improvement of blast-induced fragmentation and crusher efficiency by means of optimized drilling and blasting in Aitik

Transcription

1 MASTER'S THESIS Improvement of blast-induced fragmentation and crusher efficiency by means of optimized drilling and blasting in Aitik Ali H. Beyglou Master of Science (120 credits) Civil Engineering Luleå University of Technology Department of Civil, Environmental and Natural Resources Engineering

2 Improvement of blast-induced fragmentation and crusher efficiency by means of optimized drilling and blasting in Aitik. Ali H. Beyglou Division of mining and geotechnical engineering Department of civil, environmental and natural resources engineering Luleå University of Technology September 2012

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4 ACKNOWLEDGMENTS The thesis project presented in this report was conducted in Boliden s Aitik mine; thereby I wish to gratefully thank Boliden Mines for their financial and technical support. I would like to express my very great appreciation to Ulf Nyberg, my supervisor at Luleå University of Technology, and Evgeny Novikov, my supervisor in Boliden for their patient guidance, technical support and valuable suggestions on this project. Useful advice given by Dr. Daniel Johansson is also greatly appreciated; I wish to acknowledge the constructive recommendations provided by Nikolaos Petropoulos as well. My special thanks are extended to the staff of Boliden Mines for all their help and technical support in Aitik. I am particularly grateful for the assistance given by Torbjörn Krigsman, Nils Johansson and Peter Palo. I would also like to acknowledge the help provided by Sofia Höglund, Torbjörn Larsson, Jansiri Malmgren and Lisette Larsson during data collection in Aitik mine. I would also like to thank Forcit company for their assistance with the collection of the data, my special thanks goes to Per-Arne Kortelainen for all his contribution. Finally my deep gratitude goes to my parents for their invaluable support, patience and encouragement throughout my academic studies. Luleå, September 2012 Ali H. Beyglou

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6 SUMMARY Rock blasting is one of the most dominating operations in open pit mining efficiency. As many downstream processes depend on the blast-induced fragmentation, an optimized blasting strategy can influence the total revenue of a mine to a large extent. Boliden Aitik mine in northern Sweden is one of the largest copper mines in Europe. The annual production of the mine is expected to reach 36 million tonnes of ore in 2014; so continuous efforts are being made to boost the production. Highly automated equipment and new processing plant, in addition to new crushers, have sufficient capacity to reach the production goals; the current obstacle in the process of production increase is a bottleneck in crushers caused by oversize boulders. Boulders require extra efforts for secondary blasting or hammer breakage and if entered the crushers, they cause downtimes. Therefore a more evenly distributed fragmentation with less oversize material can be advantageous. Furthermore, a better fragmentation can cause a reduction in energy costs by demanding less amounts of crushing energy. In order to achieve a more favorable fragmentation, two alternative blast designs in addition to a reference design were tested and the results were evaluated and compared to the current design in Aitik. A comparatively large bench was divided to three sections with three different drill plans, which led to different specific charges in each section. The sections were drilled in patterns of 6x9 m, 7x9 m and 7x10 m of burden and spacing; planned specific charges of the sections were 1.17 kg/m 3, 1.02 kg/m 3, and 0.91 kg/m 3 respectively. Similar to the current drill plan in Aitik, the section with 7x9 m ( 1.02 kg/m 3 specific charge) was used as the reference for results comparison. The drilling and charging processes were monitored carefully and the post-blast parameters were measured accordingly. Laser scanning was used to measure the swelling of the sections and two different methods of image analysis were utilized to evaluate the fragmentation of the rock for each section. Drilling log data (MWD)

7 were analyzed to evaluate the hardness of the rock; energy consumption log of the crusher was also analyzed and all the data was collected in a single database. VBA (Visual Basic for Applications) programming language was embedded within data spreadsheets to correlate the mentioned data to the coordinates of the rock by means of Minestar logs, which include both timestamps and coordinates of all machinery e.g. shovels and trucks. The results of the test show significant improvements in fragmentation and oversize material percentage in the section with 6x9 m drill plan (1.17 kg/m 3 ). The advantage of 6x9 m plan was confirmed by 52% higher swelling, 66% lower oversize material and 26% lower crushing energy compared to the reference section. The section with 7x10 m drill plan (0.91 kg/m 3 ) also showed theoretically acceptable results; however, the deviations from reference were not as large as formerly mentioned section. The swelling had a decrease of 8% compared to the reference section and the percentage of oversize material and crushing energy were increased by 16% and 2% respectively. Presented results are based only on technical aspects and do not include the costs of drilling and charging. Thus, in order to evaluate the drill plans in practice an economical evaluation of the sections should be conducted. Also a confirmation test with more accurate geology explorations is recommended. Finally, upon the request of Boliden Mines, a short report on the usage of Air-decking technique in Aitik is enclosed as an appendix. The report includes a brief introduction to airdecking and discusses practical solutions to apply this technique in Aitik.

8 TABLE OF CONTENTS 1 INTRODUCTION Aims and objectives THEORY AND BACKGROUND Rock breakage by blasting Mechanical properties of rock mass Bench blasting Particle size distribution Influence of blasting on downstream processes AITIK MINE Drilling and blasting Loading and hauling Crushing and grinding TEST BLAST Description Data quality and constraints Drilling (MWD) Charging Shovel Trucks (Minestar) Split-Desktop FragMetrics Crusher Analysis strategy TEST RESULTS Hardness of the rock (MWD) Swelling Digability Fragmentation Split-Desktop FragMetrics Crusher efficiency DISCUSSION AND CONCLUSIONS RECOMMENDATIONS AND FURTHER STUDIES REFERENCES ADDITIONAL BIBLIOGRAPHY APPENDIX I: Fragmentation analysis of FragMetrics software APPENDIX II: An introduction to Air-decking in Aitik

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10 1 1 INTRODUCTION Open pit mining is one of the most utilized methods of ore extraction worldwide. Costeffectiveness, mechanical ease and safer environment are some of the advantages of open pit mining over other mining methods, in addition to that, its potential for large production volumes and low cost of recovery allows low-grade ore bodies to be extracted feasibly. Drilling and blasting is, by far, one of the main operations in open pit mines, affecting the total revenue of the mine to a large extent. Pre-blast costs, such as drilling and explosive expenses, are directly influenced by blast design; post-blast parameters are also affected by the outcome of the blast; secondary blasting, loading and hauling, crusher throughput, and grinder efficiency are related to blast-induced fragmentation of the ore (Nielsen and Lownds 1997, McKee et al. 1995). Blasting is the most energy efficient stage in the comminution process. According to Eloranta (1997), blasting has an energetic efficiency of 20% to 35%, which is relatively high compared to respectively 15% and 2% efficiency of crushing and grinding. High efficiency offers the blasting stage a strong potential for optimization of the overall comminution process, however, the operations included in the comminution process were treated individually for a long time and the optimizations were merely limited to the outskirts of each operation. A more recent approach to optimization is called Mine-to-Mill, provided by Julius Kruttschnitt Mineral Research Centre in 1998 (JKMRC 2012). Mine-to-Mill, in short, is an approach that identifies the leverage that blast results have on different downstream processes and then optimizes the blast design to achieve the results that maximize the overall profitability rather than individual operations (Grundstrom et al. 2001). According to Mineto-Mill concept, blasting should be designed in a way that satisfies the overall requirements of the comminution process, including haulage, crushing and grinding altogether.

11 2 Research works by Eloranta (1997), Kojovic (2005), Ouchterlony (2003 and 2005) and Ouchterlony et al. (2010) show a meaningful relation between blast properties and efficiency of crushing and grinding. Therefore the optimization of blasting should not only include the size distribution of blasted rock, but also consider the crusher throughput and grinder energy consumption. The importance of blasting has also urged the necessity of reliable monitoring systems to develop. Fragmentation is a key factor in the comminution process and image analysis has been the most utilizable method of fragmentation measurement so far (Chiappetta 1998). Developments in that field have led to systems able to measure the fragmentation continuously during mining; such systems, together with well-calibrated measurements of throughput and energy consumption in crusher and grinder, provide an appropriate database to optimize the process. 1.1 Aims and objectives The main goal of the current project is to find an economically viable alternative blast design to provide an improved fragmentation as well as an increase in the energy efficiency of the crusher. Constant efforts are being made in the Aitik mine to optimize the production process; accordingly, blast-induced fragmentation is of significant importance as a major role player in such optimization. Boliden Mines implemented an expansion of operations project (Aitik 36) during the period of 2006 to Pushbacks at the southeastern, northeastern and western sides of the pit resulted in trebling of ore reserves from 200 Mt to 600 Mt, as well as an extension in mine life from 2016 to 2025 and the ability to excavate down to 600 m depth. In 2010 a new modern processing plant has been inaugurated in accordance to Aitik 36

12 3 expansion project, aiming to increase the annual production up to 36 Mt until 2014; but presently, the crusher, which is directly influenced by fragmentation of blasted rock, is a bottleneck in comminution process. Large number of oversized boulders requires high cost and effort for secondary blasting; in addition to that, accidental throw of oversized boulders in the crusher opening causes downtime in the crusher, which creates a bottleneck in the production. A solution to such problem is to modify the blasting parameters in a way that improves the size distribution of the fragmented rock. The alteration in parameters should not only result in fewer boulders but also in an increase in the energy efficiency of the crusher.

13 4 2 THEORY AND BACKGROUND 2.1 Rock breakage by blasting The entire blasting act takes only a few seconds in scale of time. However, several events take place in different segments of those seconds. Once initiated, the explosive 1 releases an enormous amount of energy through chemical reactions, resulting in high-pressure gases in the blast hole which can amount to and exceed 10 GPa. The high pressure of gases is not, in and of itself, the only cause of the breakage; the rapidity of the reaction plays the leading role (Langefors and Kihlström 1967). Upon initiation, the reaction advances at a rate (Velocity of Detonation, VOD) of approximately m/s throughout the explosive. Considering the m length of a normal blast hole, one can easily realize that the reaction takes place within thousandths of a second. The rapid reaction leads to an almost instantaneous pressure rise in the hole, which produces a shockwave in the rock, traveling at a speed of m/s. The high pressure expands the walls of the hole and the area adjacent to the drill hole shatters as a result of vast amounts of tangential strains and stresses. The shattered area around the hole, with rose shaped cracks towards outside of the hole, is the first platform for fracturing (Esen et al. 2003). See figure In this report, the word Explosive refers to non-military, civil explosive materials used in mining industry.

14 5 Figure 2.1: Fractured area around the blast hole, the so-called Rose of cracks, After Esen et al. (2003). The shockwave travels at such high speed that the initial cracks form within a few milliseconds. According to wave propagation concept (Hustrulid 1999), the positive pressure of shockwave falls rapidly to negative values, which implies a change from compression to tension. Since rock is generally more resistant to compression than to tensile strain, the initial radial cracks are the results of tensile forces acting on the area around the hole. During the first stage there is practically no breakage in the rock other than the radial cracks. The main breakage occurs after the shockwave reaches the free face of the rock and reflects as a tensile wave, such phenomenon gives a rise to the tensile strains and consequently extends the cracks throughout the rock. This stage is called Scabbing (Langefors and Kihlström 1967). The scabbing and radial cracks are both effects of the shockwave; the last stage of breakage is under the influence of pressurized gases produced by the blast; this stage is considerably slower than the first two. The high-pressure gases in the blast hole, kept inside by the stemming, pressurize the borehole and apply a radial compressive stress perpendicular to the borehole; the compressive stress is large enough to initiate new cracks and extend the

15 6 existing cracks. The crack expansion outspreads through the rock and results in breakage. The overall displacement of the rock mass prior to gas action is very little; the gases not only extend the cracks, but also exert a pushing force to move the broken rock forward (Langefors and Kihlström 1967). A successful, complete breakage takes place when the amount of explosive and the geometry of the blast e.g. burden, spacing, height, are balanced in a way that the cracks expand all the way to the free face and gases push the rock forward to form a well-swollen pile; so it is critical to find the appropriate proportions of these factors based on the rock strength, fracturing, and explosives characteristics in order to reach an adequately broken and swollen rock pile. 2.2 Mechanical properties of rock mass The strength of rock can be defined by many parameters, e.g. compressive and tensile strength. The large difference between intact rock strength and rock mass strength cause many uncertainties in large-scale mining activities. Figure 2.2 shows the difference between rock mass and intact rock; the mechanical behavior of rock mass is heavily affected by discontinuities, varying in a wide range from microscopic cracks to regional faults. In addition to that the direction of the load and confinement conditions effect the behavior of the rock mass; high confinement pressure turns brittle failure to ductile and due to closure of micro cracks Young s modulus increases (Brady and Brown 1993).

16 7 Figure 2. 2: Schematic difference of intact rock and rock mass, after Scott et al. (1996). In addition to that, the failure of rock includes an element of creep, which means the loading rate effects the strength of the material (Bergman 2005). Crushing and grinding of rock are performed through static loading of the rock. However, blasting exposes the rock to both static and dynamic loading due to rapid explosive reactions. Such dynamic loading exposes the rock to high loading rates, which results in higher compressive strength (Persson et al. 1994) and increased Young s modulus of the rock (Bergman 2005). The complexity of rock mass characterization for blasting purposes leads to the conclusion that analytical solutions are not possible. As of yet, empirical measures have been the most useful tools to classify rock masses. The rock constant, c, is one of the most utilized tools in blast designs. Rock constant is a measure of the amount of explosives needed to break one cubic meter of rock and it is determined by controlled trial blasts in a vertical bench (Langefors and Kihlström 1967).

17 8 2.3 Bench blasting Achieving a well-distributed particle size is the main goal of blasting, so that the rock can be handled efficiently in post-blast processes, e.g. loading and crushing. The outcome of blast is influenced by several parameters; mechanical properties of rock mass, geometry of blast holes, type and amount of explosives, initiation pattern and delay times are some of the key factors in blast design. A brief terminology of bench blasting geometry is presented in Figure 2.3. Figure 2.3: Bench blast geometry and terminology, Bergman (2005). Specific charge, in addition to the geometry, is a key factor in bench design (Langefors and Kihlström 1967). The specific charge, q, represents the explosives consumption per cubic meter of rock (or per tonne rock). Specific charge varies based on explosive and rock mass characteristics, see equation 2.1.

18 9 Q q = B S H (2.1) Where: q: Specific charge (kg/m 3 ) Q: Total explosive per hole (kg) B: burden (m) S: Spacing (m) H: Bench height (m) Burden, B, is the distance between the rows and spacing, S, is the distance between the holes in a row. Several empirical equations are provided in the textbooks for calculation of the burden; Langefors and Kihlström (1967) provided a well-known formula for calculation of maximum burden, equation 2.2. D p E Bmax = (2.2) 33 c f ( S ) B Where D = blast hole diameter (mm), p = explosive density (kg/dm 3 ) E = weight strength of explosive (%) B = burden (m), c = rock constant (kg/m 3 ) f = degree of confinement, 1 for vertical holes. Other parameters are basically calculated by empirical rules of thumb, such as (Persson et al. 1994): S B = 1.3 (2.3)

19 10 U = B 0.3 (2.4) max L = 1.05( H + U ) (2.5) These empirical relationships are usually modified depending on the size and characteristics of the blast. 2.4 Particle size distribution 2 The results of a production blast are mainly presented by fragmentation of the broken rock. The fragmentation is described in terms of geometrical characteristics of the particles i.e. size, angularity or roundness. The cumulative size distribution function, CDF, provides a complete description of the former. It is either obtained from physical sieving of the material, which is very costly in large-scale blasts, or by non-physical sieving methods such as image analysis. The CDF is the fraction of mass P passing a screen with a given mesh size x. (Ouchterlony 2003). Percentage of passing material from each mesh, P(x), varies between 0-100%, see Figure Mainly based on the SWEBREC report by Ouchterlony (2003).

20 11 Figure 2.4: Cumulative size distribution curve, Ouchterlony (2003). Depending on the purpose of the analysis, several distinctive quantities are extracted from the curve, here follows some: X 50 = a measure of the average fragmentation, i.e. mesh size through which half of the material passes, X 50 is a central production measure. X N = other percentage related block size numbers in use. N=20, 30, 80, 90 etc. P O = percentage of fragments larger than a typical size X O. P O is related to e.g. the handling of big blocks by trucks or the size of blocks that the primary crusher cannot swallow. P F = percentage of fine material smaller than a typical size X F. In large-scale production sites the focus is on the most important of these, which in Aitik case is P O, due to problems caused by boulders at the crusher feed.

21 Influence of blasting on downstream processes The effect of blasting on subsequent operations has drawn a great deal of attention in recent years. In the past, the only criterion for blast results was the ability of excavation and hauling equipment to handle the blasted rock, but mining economy demands high production capacities as well as efficiency of costly operations. Since crushing and grinding consume enormous amounts of energy, the effect of blasting on efficiency of these operations is undoubtedly important. The effect of blasting on fragmentation is assessed in two different aspects: Seen and Unseen. The size distribution of blasted fragments is the seen part of blasting results, which can be measured quantitatively by sieving or image analysis techniques. The unseen effect of blasting is the fracture generation within the fragments, these fracture can be classified as either macrofractures or microfractures. Macrofractures are comparatively large and can be seen on the surface of fragments; but microfractures are only seen through a microscope (Workman and Eloranta 2003). The production and downtime of the crusher are under direct influence of the seen effect of blasting; oversize fragments cause a reduction in primary crusher throughput and lead to more downtime for clearing the crusher bridging (Workman and Eloranta 2003). On the other hand, the unseen aspects of fragmentation influence the energy consumption of the crusher. Therefore, it is very important to assess the effect of blasting on the energy consumption of the primary crusher in addition to the fragments size distribution. The degree of dependency of crushing efficiency on macro and microfractures is not presently clear; but studies and field tests by Eloranta (1995), Workman and Eloranta (2003), Ouchterlony (2003) and Ouchterlony et al. (2010) confirms that fracturing of the fragments, caused by heavier blasting, leads to lower energy consumptions in crushing and grinding stages.

22 13 3 AITIK MINE Aitik open pit mine is situated outside the city of Gällivare in northern Sweden. The orebody consists of low grades of copper, gold and silver. The production started with two million tonnes of ore in 1968 and gradually increased to 31.5 Mt in 2011; the production level is expected to reach 36 Mt in The pit is 3 km long, 1.1 km wide and 425 meters deep; the orebody dips 45 towards west and mainly consists of metamorphosed plutonic, volcanic, and sedimentary rocks with various strengths. Investigations by both Sjöberg (1996) and Bergman (2005) on rock strengths in Aitik show fairly similar results. Muscovite schist is the weakest rock with an average strength of 64 MPa and Pegmatite is the strongest rock with a 141 MPa compressive strength. Biotite schist and Biotite gneiss were similarly approximated to have strengths of 88 and 121 MP respectively. The utilized method of excavation in Aitik is pallet mining, in which the ore is removed in form of horizontal slices. The comminution process is shown in figure 3.1; after drilling and blasting the ore is loaded into trucks and hauled to the in-pit crusher. Once crushed, a conveyor belt transports the ore to two ore piles that feed the grinding mills. Later the grinded ore goes through chemical processes and finally the produced concentrate is transported to smelter by railway.

23 14 Figure 3. 1: Processes involved in mining in Aitik, after Bergman (2005). 3.1 Drilling and blasting The typical drill plan presently used in Aitik consists of 311mm production holes and 127 and 152mm holes for contour blasting. As seen in figure 3.2, production holes are drilled in accordance to 7m burden and 9m spacing. Contour holes are drilled with 4 and 5 meters spacing for first and second row respectively, the rows are distant 4.5m from each other and 6m from first production row. Standard benches are 15m high and blast holes are approximately 2m sub-drilled.

24 15 Figure 3.2: Current design of bench drilling in Aitik. Four Atlas Copco pit viper PV 351 drill rigs are used for production drilling. The rigs, equipped with GPS and Terrain for Drilling 3 system, are of the most advanced blast hole drills on the mining market. The coordinates of holes are uploaded to the rig and the rig navigates to the precise coordinates of each hole using GPS. With kg of bit load and up to m/min of air at 758kPa, the vipers provide a high capacity of fast drilling. The MWD system logs all the drilling data, such as torque, penetration rate, feed pressure etc. The logged data will be analyzed and used for interpretation of the properties of the penetrated rock mass e.g. hardness, fracturing and hydraulic conditions. Emulsion explosive is used as the main charge in blast holes; it has an average VOD of 5700 m/s and is of 1350 kg/m 3 density. The emulsion matrix is made in a nearby factory. Special trucks carry the emulsion matrix, Ammonium Nitrate, diesel and water to the benches. 3 Formerly known as AQUILA

25 16 The trucks are equipped with a system to mix the matrix with diesel and AN beforehand charging. The temperature of the contents, as well as the mixture proportions and volume of the explosive filled in each hole are set through the computerized system of the mixing trucks. The current specific charge of production blasting in Aitik is 1.02 kg/m 3, which varies from time to time depending on geology and production requirements. Nonel Unidet system is used to detonate the holes. Two boosters combined with two detonators are placed at the bottom of each hole to assure the detonation of the emulsion, the boosters and detonators are of types Dyno 1.7 and Nonel U-1000 respectively. The coupling takes place after plugging the holes with about 5.5 meters of crushed stemming material; the holes are detonated with 176 ms of delay between the rows and 42 ms delay between the holes in a row. 3.2 Loading and hauling Four shovels and 30 trucks of various capacities are used to load and haul the blasted rock. All vehicles are equipped with Minestar system. Minestar is an integrated operations and mobile equipment management system; Tracking ore and waste, locating the vehicles and managing the schedule and assignments of the fleet operations are some of the capabilities of Minestar. Presently one of the shovels, of type P&H 4100C, is equipped with a camera installed on the boom. The camera is part of Fragmetrics fragmentation measurement system; it captures photos of the bucket every two minutes. The photos are analyzed with Fragmetrics image analysis software to estimate the fragmentation curve of the loaded rock.

26 Crushing and grinding The in-pit crusher, Allis-Chalmers Superior , does the main part of primary crushing of the main pit rock. It is situated at the 165 m level and consists of two primary gyratory crushing stations as well as overland conveyors and feeders. The system has a capacity of 8000 t/h and will transport the ore 7 km. At downtimes, or during maintenance periods, two crushers on the surface are used. The main crusher s opening is 152 cm in diameter and the lower part of the mantle has a diameter of 277 cm. Depending on ore properties, the coarsest boulders size after crushing varies in range of 35 to 40 cm. The crushed ore is transported to two stockpiles on a conveyor belt. The total capacity of the stockpiles provides 16 to 20 hours of full production in the mill, i.e tonnes. The grinding process is operated through five grinding lines in three grinding sections. Each grinding line consists of a primary autogenous mill and a secondary pebble mill. The process is a close chain, a screw classifier feeds the coarse material back to the primary mill and pebbles are extracted from the primary mill and fed to secondary mill, Figure 3.3. Figure 3. 3: Milling process of the ore, Bergman (2005). Finally the grinded ore is transformed into concentrate by processes of flotation, thickening, dewatering and drying. The concentrate is then transported by railway to Rönnskär smelter in the city of Skelleftehamn.

27 18 4 TEST BLAST 4.1 Description A production bench, named S1_210_13, with a volume of m 3 was assigned for the test; it was situated at the western wall of the pit at 210 m level. The bench was divided to three smaller sections, of which one was used as reference. Hereinafter the letters A, B and C are referred to these sections. Figure 4.1 shows the bench; a drilling plan of 6 m burden and 9 m spacing was assigned to section A. Section B, with the currently used drill plan (7 m burden and 9 m spacing), was the reference for further comparisons; the middle section was chosen as reference in order to minimize the effect of geological discontinuities in the blast results. Section C was ascribed a wider drill plan with respectively 7 and 10 m of burden and spacing. The test bench consisted of a total number of 668 holes; average planned depth of holes was 16.2 meters of which 1.2 m was sub-drilling. The planned specific charges were 1.17, 1.02 and 0.91 kg/m 3 for sections A, B and C respectively. A stemming length of 5.5 meters was also planned for all holes; gravel of size 5-8 cm was used as stemming material. During the drilling, some practical issues regarding neighbor benches and machinery led to a change of plans; a part of section A was omitted from the test bench and scheduled for the next round. The omitted part is shown with red rectangle in Figure 4.1.

28 19 Figure 4. 1: Test bench and drilling patterns. The bench mostly consists of Muscovite and Biotite Gneiss. Two dykes of Biotite cut through the bench diagonally, a large part of an Amphibolite Gneiss dyke also cuts the southeastern edge of the bench (Figure 4.2). Although the geology map does not show any Pegmatite dyke within the bench area, their existence cannot be discarded for sure as the precision of explorations are not so high.

29 20 Figure 4. 2: Geology of the test bench. Except the drill pattern, all the blast parameters such as emulsion density, hole depth, sub-drill etc. were kept unchanged in order to have a parametrically controlled test. Drilling and charging processes were also controlled and monitored to avoid fortuitous errors. Nonel Unidet system was used for initiation of the blast. The initiation plan is shown in Figure 4.3. The southward direction of the blast was decided based on the direction of rock structure as well as loading availability. The blast initiated at the northeast corner of the bench spreading towards southwest. A delay of 176 ms was used between the holes and each row was delayed 42 ms from previous one. As a result of smaller free face for the blast at the northwestern part of the bench, shorter delays of 67 and 109 ms were introduced for a smoothly swollen rock pile. To prevent detonation failures, two detonators and two boosters were used for each hole.

30 21 Figure 4. 3: Initiation pattern of the blast holes; the initiation starts at the upper left part in the figure. The blast itself was filmed using a high-speed camera so the initiation of all holes could be confirmed. Once blasted, the surface of the bench was laser-scanned to evaluate the swelling of the rock in three sections. The rock was photographed continuously during loading. The Fragmetrics camera, installed on the boom of one of the shovels, photographed the bucket every two minutes. A 10-megapixel camera, Nikon D3000 equipped with a 300 mm tele lens, was also used to manually photograph the bed of loaded trucks. To estimate the fragmentation of blasted rock two different softwares were used: FragMetrics and Split-Desktop. Fragmetrics was used to analyze the photos taken by its associated camera; manually taken photos were used for Split-Desktop. The Fragmetrics camera was calibrated in accordance to the width of the shovel bucket (460 cm); no further adjustments were needed since the position of the camera was fixed. However, manually

31 22 taken photos could not be shot from exact positions, so photos were taken from a suitable level depending on the location of each truck, pictures are shot from an angle which minimizes the optical distortions in the rock pile. The width of the flatbed of trucks was used as the scale for size distribution analysis. To obtain a consistent correlation between the crusher throughput and fragmentation, the measurements required to be obtained from the identical rock. In order to track the ore from the bench to the crusher, timestamps were attached to photos. The manual camera, as well as Fragmetrics camera, was synched to the clock of Minestar system, so the photos could be linked to certain times of loading and crushing. By estimating the average time delays for the ore between unloading and entering the crusher, the crusher throughput could be linked to a certain set of photos. Thus, a size distribution curve is available for each value of throughput. The location of shovel, obtained from Minestar, shows the location of the loaded ore and correlates this relationship to one of the three sections of the bench. To avoid mixtures of the ore in the crusher, all the trucks were assigned to load the ore only from the test bench during data collection, so the crusher was only fed with the ore from the test bench and no ore mixing took place. 4.2 Data quality and constraints A variety of data sets are involved in the process of correlating pre-blast measurements to post-blast parameters, each data set is obtained from a different source, including its systematic errors. In addition to that, each source has a specific chance of failure, which causes loss in the data and/or large errors. Thus, the necessity of an appropriate analysis

32 23 strategy based on the availability and quality of the data is inevitable. Following sections briefly describe some of the sources, their systematic errors and availability of their data Drilling (MWD) Drill rigs in Aitik are equipped with Aquila DM-5 drilling management system for precision drilling through GPS positioning. MWD (Measure While Drilling) is a part of this system that collects and archives the drilling parameters while drilling each hole. Although this data is not fully used in production yet, it has been studied and evaluated several times and there is no doubt in its usefulness. Several parameters are included in MWD logs; some are independent parameters, others depend on the geological and geotechnical properties of the rock mass. Depth, time, rotation speed and feed force are independent parameters while penetration rate, torque, vibration and air pressure are parameters that depend on rock mass characteristics. All these parameters implement a systematic error in the measurements, but since there are no reference measurements to evaluate the errors, one cannot quantify these errors in a numerical manner. One of the most critical parameters in drill measurements is depth, due to the fact that all other parameters are recorded along the depth of the hole. The depth of the hole also decides start and end of drilling. In this project the depths of 215 holes right before and 1 hour after charging were measured manually to control the MWD measurements of depth, the results are presented in and show an acceptably low error. However, a calibration of the depth measuring system will improve the accuracy to a large extent. Another issue with MWD data is its multi-dimensional nature. Each parameter is recorded along the depth of the hole; in order to correlate a parameter to XY coordinates for several holes, one should eliminate one of the dimensions. In other words, only one value can be assigned to the hole in order to analyze the parameters horizontally. Usually penetration rate (PR) is the governing parameter for analysis, which is also dependent on other drilling

33 24 parameters such as feed force. A solution to that is using a calculated index that includes several variables. Specific energy (SE) is a concept that represents the work done per unit excavated. The concept was introduced by Teale (1964) and has been evaluated by Schunesson (2007). Teale (1964) introduced the following equation for specific energy: SE = F A 2π NT + + A P (4.1) where: SE = Specific Energy [N.cm/cm 3 ] F = Feed Force [N] A = the cross-section area of the drill hole [cm 2 ] N = Rotation Speed [RPM] T = Torque [Nm] P = Penetration Rate [m/minute] In this report both penetration rate and specific energy are presented. By introducing specific energy alongside penetration rate, the errors in PR are eliminated or minimized; but SE is still a parameter measured along the depth. In this study an average value within a fixed depth of the hole has been considered as a median value for horizontal analyses. Figure 4.4 shows a sample MWD data for one of the holes. Custom VBA codes were written to analyze the data; the average values have been calculated for the depth of the hole in between the two red lines (the lines are unique for each hole). In this way the fractured part near the surface (Sylta) as well as the low values at the bottom of the hole are ignored and errors due to median calculation are eliminated and the median value can be considered as a suitable representative of rock quality.

34 25 Figure 4. 4: MWD analysis of a sample hole (Hole #264). The final issue with MWD data, for which no solution exists, is loss of data due to mine network failure. As it will be shown in following chapters, MWD measurements were not available for some parts of the bench. Fortunately the loss was not extreme, so there was still enough data available to evaluate the test; but obviously more data is more favorable as it helps to acquire more accurate results Charging Although highly mechanized trucks are utilized for charging process in Aitik, errors still occur due to rock fractures and human error. Manual measurements of the depth of 215 holes before and after charging show high deviations resulted by operators error (Figure 4.5). The measurements were conducted before and 1 hour after charging, the 1-hour delay was

35 26 sufficient for the expansion of emulsion explosive and it was short enough to avoid the leakage of emulsion into joints and fractures. Each point in Figure 4.5 represents the deviation of drilling and charging depths from the planned depths of one blast hole, the closer the point to the 0 circle, the smaller the error. Since the measurements were focused on a specific area on the bench, any comparison between the errors of three sections would not be judicious. Figure 4. 5: Drilling and charging errors of 215 blast holes. Despite the problems caused by groundwater during and after drilling, figure 4.5 shows acceptably low errors in drilling depths. However, charging errors are distinctively larger; a few holes were completely filled with emulsion, these overcharged holes were blasted without stemming and caused fly-rock and air-blast risks. Some holes were similarly

36 27 undercharged; the undercharged holes result in low specific charge in some areas, which lead to coarser fragmentation and more oversize boulders Shovel Shovel logs are of great importance in evaluation of fragmentation and crusher performance. The logging system records all the parameters every few seconds. The GPS positioning system installed on the shovel records three different coordinates at each recording, one for the shovel itself, one for the shovel bucket and the last for the digged area. The important coordinates are digging and bucket coordinates; further analyses regarding fragmentation and crusher throughput are correlated to the rock coordinates using digging coordinates. The bucket position log is used to evaluate the digability of the fragmented rock; the bucket coordinates are linked to the time taken to load the bucket, which is the standard measure of the digability. Depending on the GPS system and satellite visibility, there is an error of about 1 to 15 meters associated with GPS measurements, especially in higher latitudes (Aitik mine is located at approximately 70 degrees latitude). By graphing the position of the shovel and comparing it to the laser-scanned map of the bench it was revealed that the accuracy of the GPS was more than expected. No overlap was observed near the walls and on the edge of the bench, which shows a reasonably good accuracy Trucks (Minestar) Aitik mine uses Cat Minestar system for material tracking and real-time fleet management. Logging the trucks activities is one of the capabilities of this system that is used in the current study. Each truck is identified by a unique ID number, which is used to correlate the fragmentation (extracted from manually taken photos) to the crusher parameters.

37 28 Unfortunately the system was functioning faulty and the truck IDs did not match the ID signs on the trucks. Providentially the logs included correct data about times and locations of trucks to extract a representative for each section of the bench. As a solution to faulty logging of truck IDs, the truck cycle IDs from shovel are used; truck cycle ID is another unique ID which identifies each cycle of the trucks within the mine. The procedure is described in detail in Split-Desktop An effective method to assess fragmentation is to acquire digital images of rock fragments and to process these images using digital image processing techniques. In the case of postblast fragmentation, this is the only practical method to estimate fragmentation, since screening is impractical on a large scale. The Split-Desktop software was originally developed at the University of Arizona; in 1997 the technology was commercially available through a newly formed company, Split Engineering. The Split software allows post-blast fragmentation to be determined on a regular basis throughout a mine, by capturing images of fragmented rock in muckpiles, on haul trucks, or from primary crusher feed. The resulting size distribution data can then be used to accurately assess the fragmentation associated with different parts of a shot (Kemeny et al. 2002). The basic steps involved in Split-Desktop analysis are acquiring images, preprocessing the images to correct lighting, defining scales, delineating the images using Split algorithms and finally correcting the delineation manually and defining fines (Figure 4.6). The complete manual correction of delineations takes about 30 to 90 minutes per image, depending on the quality of the image, lighting conditions and presence of dust, fog or other obstacles and the level of precision in delineation. The software then applies statistical

38 29 algorithms to the 2D particle distribution to determine 3D particle volumes. To achieve an average distribution multiple images should be processed, preferably with different scales. Figure 4. 6: Delineation of a sample image with Split-Desktop. Ouchterlony (2003), Kemeny et al. (2002) and Sanchidrian et al. (2006) have extensive studies regarding the procedures and errors in measurements of fragmentation by image analysis. Based on their studies and in accordance to the conditions, the sources of errors associated with the current study can be concluded as follows: - Sampling error - Optical distortions - Manual corrections of delineation

39 30 In order to minimize the sampling errors, efforts should be made to acquire evenly distributed images among the bench area. The entire bench had been photographed during loading, but unfortunately the limited data from Minestar did not permit an evenly distributed analysis over the entire bench; as a solution to that three areas on the bench were selected as representatives for three sections and images were sampled evenly within those areas. The optical distortions were also mostly overcome by using a tele lens. The long focal distance of the lens (300mm) minimized the image distortions to a great extent. The photos were also taken from an approximately fixed angle and two separate scales were defined in each image, so the scales and perspective of all images are roughly the same. Split-Desktop results are highly user-dependent, in other words the fragmentation obtained from an identical image is not the same for two different users. In that regard, only one user has analyzed all images; the error of different delineating styles were also minimized by making an efforts forth fairly identical delineation styles through all images. Although much effort has been made in order to eliminate the errors in fragmentation analysis, the existence of systematic errors in such process in undeniable FragMetrics FragMetrics is a fragmentation measurement package provided by Motion Metrics International Corporation. The package includes a camera installed on the boom of a shovel, logging and storage devices, and a tablet PC with FragMetrics software to process the stored images. The principle of FragMetrics is the same as Split-Desktop. However, the inert position of the camera against the bucket eliminates the optical errors. In addition to that the automated essence of the system provides a very useful tool for continuous monitoring of fragmentation.

40 31 FragMetrics is a newly developed system. It started operating from January 2012 in Aitik, so very few experience regarding its results is available. Preliminary evaluations of the results reveal that in contrary to its advantages to Split-Desktop, the very low resolution of the camera leads to unreliable results. Figure 4.7 shows a sample image from FragMetrics camera, the low resolution of the image limits the particles visibility down to boulders only. Figure 4. 7: A sample image and delineation from Fragmetrics system. A normal image analyzed in Split-Desktop has a resolution of around 2500x1500 pixels, showing a wide range of particles; but FragMetrics images are limited to 380x150 pixels, which is very low comparatively. Such resolution leads to faulty size distribution analyses. Therefore the FragMetrics size distribution results were not used in evaluations and discussions of this report; but as the boulders were clearly visible in the images, they represented a very good source of data for oversize material. The images were used only to determine the percentage of oversize material in each section of the bench Crusher As mentioned before, the loading continues round the clock in Aitik and the loaded rock is from different sources. In order to avoid rock assortment one of the crushers (KR 165) had

41 32 been only fed with the rock from the test bench. The mentioned crusher consists of two primary gyratory crushing stations, so for every time point there are two energy consumption values available. The energy consumption of the crushers are logged every 12 seconds. The energy consumption of the crusher has a large scatter, so it is of great importance to apply suitable statistical methods for sampling and analyzing the data. Figure 4.8 shows a typical energy consumption diagram for one of the crusher lines. Each bar in figure 4.8 represents 12 seconds of crusher work and the values should be correlated to fragmentation of the rock on trucks. Since the rock from a single truck takes approximately 5 minutes to be crushed, a statistical analysis in necessary to come up with a median value for each truck. Figure 4. 8: A sample of crusher energy consumption variations during 6 hours. The mean values were calculated through VBA codes; the energy consumption of two crushing lines were compared to pre-defined values to check if the crushers were in process or idle mode; if either of them are in idle mode the other line s energy consumption is assumed real for that specific time point. For the time points that both crusher lines were in process, an average of the two values are considered as true energy consumption. Over the time axis box median values are calculated for periods of 5 minutes (similar to box-and-whisker diagrams). It should be mentioned that the 5-minute period used in the calculations is an approximation

42 33 of the time between dumping and end of crushing, this value is obtained from observations at the crusher and averaging the timespan. 4.3 Analysis strategy With regard to data limitations mentioned in 4.2, a coherent approach to available data is necessary for a consistent interrelation. Figure 4.9 shows the flow of the available sets of data and the logical path to correlate them and bypass the data loss. Figure 4. 9: Data-flow diagram used to correlate sets of analyzed data. The main purpose of the diagram in figure 4.9 is to integrate all data sets into one database of synchronized parameters. As seen, three sets of data come from the shovel; one is the time interval of loading each bucket of the shovel, which provides a measure of digability;

43 34 second is the date and end time of loading a specific truck, which is used to designate the affiliated photo for fragmentation analysis; and the third is the Cycle ID of the truck, this ID is a substitute for the Truck ID, which is missing in Minestar. Truck cycle ID is then used to extract the coordinates of the digged rock and end time of the truck cycle, which is equal to dump time and is used to obtain the associated crusher efficiency from the crusher log. MWD data is independent of the mentioned data sets; all available data is analyzed to extract penetration rate and specific energy over the entire bench. Dig coordinates for available truck cycles in Minestar, end time of loading from shovel, and rock properties from MWD are then filtered using a VBA loop in a way that all missing data are eliminated except the points for which all three sources have valid data. The mentioned procedure provided a parametrically comparable set of data. Based on this data, photos are selected and analyzed with Split-Desktop and Fragmetrics softwares. As mentioned, Split-Desktop is used for a detailed fragmentation analysis and Fragmetrics is only used for oversize material (boulder count). To compare three sections of the bench, three representative areas are assumed. The areas are selected based on the criteria of availability and validity of data, as well as similarities in rock mass properties, which is described in 4.1.

44 35 5 TEST RESULTS 5.1 Hardness of the rock (MWD) Since the objectives of this study do not include detailed MWD analysis, only the most important parameters are presented and discussed. As mentioned in 4.2.1, penetration rate and specific energy are the governing parameters in MWD analysis (Mozaffari 2007). Figure 5.1 shows the penetration rate over the test bench and specific energy is plotted in figure 5.2; the gray area in both plots represents the region with no available data. Although variation in penetration rate is the simplest indicator of rock mass strength, it is influenced by several factors. Since specific energy merges all factors into one single parameter, it can be used as a substitute for penetration rate. Figure 5.1 shows two main zones in the bench and few hotspots indicating harder rock; the mentioned zones are significantly less differentiated in matter of specific energy (Fig 5.2). However, a comparison between figures 5.1 and 5.2 shows very few distinctions regarding the hotspots. These figures can be paired to the geology map of the bench (Fig 4.2). Figure 4.2 shows dykes of Biotite and Amphibolite Gneiss in the bench, these dykes are approximately located at the hard rock spots in figures 5.1 and 5.2; the higher strength of Biotite and Gneiss also confirms this supposition.

45 36 Figure 5. 1: Penetration rate of drill bit. Figure 5. 2: Specific energy consumed for drilling over the test bench. These figures are mainly used as the basis for the selection of representative areas for three sections of the bench. The areas are selected in parts of the bench with acceptably similar rock mass hardness in a way that the hard rock spots are avoided as well as the areas close to the border of the sections, which cannot be a fair representative of the whole section.

46 37 It should be mentioned that the missing data in MWD database along with the constraints regarding Minestar data availability did not permit any better choice of areas (Fig 5.3). Figure 5. 3: Representative areas for three sections with respect to limited MWD and Minestar data. 5.2 Swelling The surface of the bench was laser-scanned right after the blast, the raw surface is shown in Figure 5.4. For a better comparison the 2D-projection of this surface is shown in Figure 5.5, which indicates the variation of swelling over the sections.

47 38 Figure 5. 4: 3D view of test bench's surface after the blast. q=1.17 kg/m3 q=1.02 kg/m3 q=0.91kg/m3 Figure 5. 5: Contour map of bench surface level after the blast.

48 39 The significantly larger swelling of section A in figure 5.5 is compatible with considerably higher specific charge of this section (1.17 kg/m 3 ) compared to sections B (1.02 kg/m 3 ) and C (0.91 kg/m 3 ). Although the specific charge in section B is larger than section C, no significant alteration is observed in the amount of swelling for these two sections. 5.3 Digability Timespan for filling each bucket by the shovel is plotted in figure 5.6 as a measure of digability of the blasted rock. The gray area indicates the missing data. Figure 5. 6: Digability of the blasted rock over the bench. The highly scattered digging times in figure 5.6 do not lead to any meaningful conclusion; no significant difference can be distinguished between the three sections of the bench.

49 40 The high scatter can be due to variations in machinery and operators. As mentioned before, two shovels have loaded the test bench, one of type P&H 4100C and the other of type Bucyrus 495BII. In addition to that each operator works with a unique pace; the digging time highly depends on the skills of the operator and the operation shift (day/night). 5.4 Fragmentation Since boulders are the main problem in comminution process in Aitik, extra attention has been paid to the oversized material. Oversized material is defined as particles larger than 100 cm, which is decided according to crushers opening size Split-Desktop A total number of 78 photos were processed to evaluate the fragmentation of the test bench. Respectively 23, 30 and 25 photos were analyzed for representative areas of sections A, B and C. Complete size distribution diagram of three sections are presented in figure 5.7; the curves are totally based on existing data and no curve fitting method is included. As seen in the diagram, section B is of lowest uniformity and the most uniform curve belongs to section A. However, sections B and C are approximately identical between X 80 and X 100.

50 41 Figure 5. 7: Particle size distribution of the fragmented rock. For a better comparison the values of X 50, X 80 and percentage of oversize material are presented in figures 5.8 and 5.9. Although section C has the largest X 50 and X 80 values, the variations are minor between three sections. Particle Size (cm) ,26 62,94 X50 28,64 X80 69,6 41,17 80, Section A Section B Section C q=1.17 kg/m 3 q=1.02 kg/m 3 q=0.91 kg/m 3 Figure 5. 8: Size of the material at 50% and 80% passing.

51 42 Section A has the lowest X 80 ; the deviation of X 80 from reference bench is approximately equal for sections A and C. Nevertheless, the percentages of oversize material (Fig 5.9) show a notably higher deviation for section A. Section C includes the largest percentage of oversize material, but the difference from the reference (section B) is less than 3%. However, section A includes 3.92% of oversize material, which is more than 7% lower than reference section Oversize material (Split-Desktop) 12,04 13,97 % Oversize ,92 Section A Section B Section C q=1.17 kg/m 3 q=1.02 kg/m 3 q=0.91 kg/m 3 Figure 5. 9: Percentage of oversize material from Split-Desktop analysis. Although this study mostly focuses on the coarse portion of particle size distribution (X 80 and oversize material), value of X 50 is the most common measure of fragmentation; therefore the values of X 50 for three sections are plotted against their corresponding specific charges on a log-log diagram in Figure The line fitted to three points on the diagram leads to the conclusion that section B does not follow the common trend of specific charge and X 50 correlation. The smaller X 50 in section B, which shows finer material, could be due to geological variations in three sections. As shown in the rock hardness diagram from MWD analysis (Figures 5.1 and 5.2), section B consisted of slightly weaker rock compared to sections A and C, such variation may have led to finer fragmentation and smaller X 50. In

52 43 addition to that, the errors involved in drilling, charging and measurements of fragmentation could have led to such results. Section C Section A log X50 (cm) Section B log q (kg/m 3 ) Figure 5. 10: Logarithmic diagram of X50 versus specific charge. The graphs in figures 5.8, 5.9 and 5.10 compare the mean values of X 50 and X 80 for the processed images; yet these mean values are extracted from highly scattered data sets. A statistical analysis of the data resulted in the diagram presented in Figure 5.11, which demonstrates the box and whisker diagram of X 50 and X 80 values for each section. The graph presents the probability density of the data. Each box, marked with the first and third quartiles and the median value in-between, shows the range that 50% of the points are set. As seen, the boxes include a skewness factor and show the statistical dispersion of the data rather than the normal distribution. Overlaps of the boxes, large interquartile range (IQR) of the mean values and wide range of minimum and maximum values can be explained by the fact that X 50 and X 80 values extracted from an image from a single truck cannot be a realistic representative of the fragmentation. Since segregation of the broken rock is an inevitable phenomenon during loading, each truck may carry more or less homogeneously distributed materials. In other

53 44 words, a single truck may include mostly fine materials while the next truck carries very large boulders. Figure 5. 11: Statistical dispersion of X50 (left) and X80 (right) values. In Figure 5.11, X 50 values as low as 5 cm or as large as 105 cm exist for particle size distribution of image analysis; similarly, X 80 values vary in range of 25 cm to 145 cm. The only way to draw a conclusion from such wide range, which is caused by segregation of the materials, is to sample the images in a way that includes various ranges of material sizes on trucks so the combination of several images leads to a more representative result. Therefore one can deduce that in order to achieve realistic results, sufficient number of images should be analyzed so the effect of segregation of the materials is eliminated.

54 FragMetrics The size distribution curves produced by Fragmetrics software will not be taken into account in discussions due to its nonsensical results. Four curves produced by Fragmetrics are presented in Figure 5.12 and a sample report produced by the software can be found in Appendix I. As seen in Figure 5.12, although the delineations were manually corrected, the curves provide very little information regarding the uniformity and size distribution of the rock. Figure 5. 12: Four sample size distribution curves produced by Fragmetrics software. Photos taken by Fragmetrics camera (on P&H 4100C shovel) are only analyzed as a means to determine the percentage of boulders larger than 100cm. A total number of 195 images (65 images per representative area) were analyzed using Fragmetrics software.

55 46 Results of Fragmetrics analysis are presented in figure According to the diagram, section A includes the least percentage of oversized boulders followed by section C and B respectively. Section A s deviation from the reference is noticeably larger than section C s. 5 4 Oversize Material (FragMetrics) 3,9 3,5 % Oversize ,9 0 Section A Section B Section C Figure 5. 13: Percentage of oversize material from Fragmetrics Results. A comparison of figures 5.13 and 5.9 reveals a large difference in percentage of oversize material between Fragmetrics and Split-Desktop Analyses. The reason might be the low quality of Fragmetrics images, leading to a faulty estimation of fine material. The software cannot differentiate shadows from fine material, so all the shadows and voids in between the particles are counted as fine material. Such error led to oversize percentages lower than actual values. 5.5 Crusher efficiency The correlation between coordinates of the rock and energy consumption of the crusher is shown in figure The energy value shown in the plot is a statistical median of energy consumption of both lines of crusher 165; the parts for which the data was not available are marked by gray color.

56 47 Figure 5. 14: Energy consumed to crush the rock (KWh). According to the plot, section A had consumed the least amount of crusher energy. The highest energy consumptions belong to an area at the border of sections B and C. A meaningful correlation can be observed between figure 5.14 and MWD results (figures 5.1 and 5.2); the area close to MWD hotspots, which indicate harder rock, had consumed higher crushing energies.

57 48 6 DISCUSSION AND CONCLUSIONS In order to deduce practical conclusions, an overall comparison of the results is required as well as an estimation of economic efficiencies of alternatives. Table 5.1 summarizes the most important results for each section of the bench. The drilling depth in calculation of specific drilling is assumed equal to planned depth of 17.5 meters for all holes. Mean values are calculated at 95% confidence of the data sets. The standard deviations (STDV) are also mentioned to provide a measure of the data scatter. Table 6.1: A summary of the test results. Section A B C Burden (m) Spacing (m) Height Specific Drilling (m/m3) Specific Charge (kg/m3) Swelling Mean value (m) STDV X 50 Mean value (cm) STDV X 80 Mean value (cm) STDV Percent Oversize Mean value (%) STDV Crusher Energy Consumption Mean value (KWh) STDV As section B is the currently used design in Aitik mine, it is assumed as the reference to compare two other sections; in order to make an unbiased comparison between the factors mentioned in Table 6.1, percentages of deviation from reference is plotted in Figure 6.1.

58 49 Percent deviation from reference section Figure 6. 15: Percent deviation from reference section. Specific Drilling and specific charge are the main measures of cost estimation. As seen in Figure 6.1, section A had about 15% higher cost of drilling and charging compared to section B. Same costs are -10% for section C, indicating a large thrift in total cost. High specific charge of section A resulted in 50% more swelling compared to reference section. However, section C had only 8% less swelling than section B. The deviation of X 80 in sections A and C are +14 and -10% respectively, which is fairly uniform. But the percentage of oversize material shows very different deviations; section A included 60% less boulders compared to section B; but section C included only 16% more oversize material. Crusher energy consumption is also differently deviated for sections A and C; the crushing of the rock from section A consumed 25% less energy than the rock from section B.

59 50 In contrary, energy consumption of the crusher was only 2% higher than the reference for section C. In other words, sections B and C consumed fairly equal amounts of energy in the crusher. Comparing MWD analysis results to crusher energy consumption plot (Figure 5.14) reveals a meaningful correlation between crusher efficiency and hardness of the rock; the hotspots of MWD plot, indicating harder rock, consumed significantly larger amounts of crushing energy. To summarize, the following conclusions can be drawn from the results: - Section A, with a 6x9 m drilling pattern and 1.17 kg/m 3 of specific charge, provides a smaller X 80 and lower percentage of oversize material; it also reduces the energy consumption of the crusher by around 25%. However, X 50 shows a 13% increase compared to reference section. The costs of drilling and charging also increase by 15%. - Section C, with 7x10 m drilling pattern and 0.91 kg/m 3 specific charge, produced coarser fragmentation and more boulders; in addition to that, visual observations confirmed that the size of the boulders were significantly larger than the reference.x 50 and X 80 show 14% and 41% increases respectively. The percentage of oversize materials also increased by 17%. The fragmented rock consumed only 3% more crushing energy compared to the reference section, which is almost equal to reference section energy consumption. Furthermore, the drilling and charging costs of section C were 10% lower than the reference costs.

60 51 7 RECOMMENDATIONS AND FURTHER STUDIES Two drilling patterns have been tested, evaluated and compared to the currently used pattern; the test results are in accord with the theoretical correlations of specific charge and fragmentation. In order to put the results into practice, comprehensive economic analyses as well as another comparative test seem necessary. If the post-blast benefits of 1.17 kg/m 3 of specific charge in 6x9 m drill pattern overcome the additional costs of extra drilling and charging, a confirmative test should approve the results prior to application of the new drilling pattern. Since the deviations from reference are relatively low for section C (Fig. 6.1), the 7x10 m pattern and 0.91 kg/m 3 of specific charge can still be considered as an alternative option. The increase in X 80 and oversize materials are about 15%, but the energy consumption of the crusher does not increase significantly and the pattern saves 10% of drilling and charging expenses. The study suggests advantageous practices of MWD database to predict spots of hard rock and low crusher efficiency. This data can be used to modify the drill and blast design of benches to reach uniform fragmentation throughout the whole area. The meaningful correlation between hard rock indicators on MWD maps and significantly larger crushing energies can also be used to eliminate the effect of geological uncertainties in future tests blasts. Minestar system is another potential for improvements; a well-functioning logging system opens the way for continuous surveys of mining process. Minestar logs act as a link between different sections of the mine, so in order to improve the overall efficiency of the mine it is critical for Minestar system to fully function. Fragmetrics system is also an advantageous means for continuous monitoring of fragmentation. However, low image quality and faulty analysis algorithms do not let this

61 52 system to be used in full capacity. A high resolution camera equipped with an anti-vibration system, together with more advanced image processing software, can provide more realistic results in regard of continuous fragmentation measurements. Finally, following operations are suggested for future: - A financial analysis of tested patterns; a confirmation test should be defined if either of them leads to higher benefits. - Efforts to improve the function of Minestar and mine network in order to collect as much data as possible. - Efforts to improve the function of Fragmetrics system as a key in fragmentation monitoring.

62 53 REFERENCES Bergman, P. 2005, Optimisation of Fragmentation and Comminution at Boliden Mineral,Aitik Operation, Luleå University of Technology. Brady, B.H.G. & Brown, E.T. 1993, Rock Mechanics for Underground Mining, Second edn, Chapman and Hall, London. Chiappetta, R.F. 1998, "Blast monitoring instrumentation and analysis techniques, with an emphasis on field applications", Fragblast, vol. 2, no. 1, pp Eloranta, J. 1997, "Efficiency of blasting versus crushing and grinding", 23th Explosives and Blasting Technique Conference.International Society of Explosives Engineers, Cleveland, Ohio. Eloranta, J. 1995, Selection of Powder Factor in Large-Diameter Blast Holes, Eloranta & Associates Inc. Esen, S., Onederra, I. & Bilgin, H.A. 2003, "Modelling the size of the crushed zone around a blasthole", International Journal of Rock Mechanics and Mining Sciences,, no. 40, pp Grundstrom, C., Kanchibotla, S.S., Jankovich, A. & Thornton, D. 2001, "Blast fragmentation for maximizing the sag mill throughput at Porgera gold mine", pp Kemeny, J., Mofya, E., Kaunda, R. & Lever, P. 2002, "Improvements in Blast Fragmentation Models Using Digital Image Processing", Fragblast: International Journal for Blasting and Fragmentation, vol. 6, no. 3-4, pp Kojovic, T. 2005, "Influence of aggregate stemming in blasting on the SAG mill performance", Minerals Engineering, vol. 18, no. 15, pp Langefors, U. & Kihlström, B. 1967, The Modern Technique of Rock Blasting, Almqvist & Wiksell. McKee, D.J., Chitombo, G.P. & Morrell, S. 1995, "The relationship between fragmentation in mining and comminution circuit throughput", Minerals Engineering, vol. 8, no. 11, pp Mozaffari, S. 2007, Measurement While Drilling System in Aitik Mine, Luleå University of Technology. Nielsen, K. & Lownds, C.M. 1997, "Enhancement of taconite crushing and grinding through primary blasting", International Journal of Rock Mechanics and Mining Sciences, vol. 34, no. 3--4, pp. 226.e1-226.e14. Ouchterlony, F. 2005, "The Swebrec function: linking fragmentation by blasting and crushing", Mining Technology (Trans.Inst.Min.Metall.A), vol Ouchterlony, F. 2005, "What does the fragment size distribution of blasted rock look like?", Brighton Conference Proceedings Ouchterlony, F. 2003, Influence of blasting on the size distribution and properties of muckpile fragments, a state-of-the-art review, Swebrec. Ouchterlony, F., Bergman, P. & Nyberg, U. 2010, Fragmentation in production rounds and mill throughput in the Aitik mine, a summary of development projects , Swebrec and Boliden Mineral AB. Ouchterlony, F., Nyberg, U., Bergman, P. & Esen, S. 2007, "Monitoring the blast fragmentation at Boliden Mineral's Aitik copper mine". Ouchterlony, F., Olsson, M., Nyberg, U., Andersson, P. & Gustavsson, L. 2006, "Constructing the fragment size distribution of a bench blasting round, using the new Swebrec function", Fragblast-8. Persson, P., Holmberg, R. & Lee, J. 1994, Rock blasting and explosives engineering, CRC Press.

63 54 Sanchidrian, J.A., Segarra, P. & Lopez, L.M. 2006, "A Practical Procedure for the Measurement of Fragmentation by Blasting by Image Analysis", Rock Mech.Rock Engng. Schunneson, H. & Kristoffersson, T. 2011, "Rock mass characterisation using drill and crushability monitoring - a case study", International Journal of COMADEM, vol. 14, no. 21, pp Schunneson, H. & Mozaffari, S. 2009, "Production control and optimization in open pit mining using a drill monitoring system and an image analysis system-a case study from Aitik copper mine in Sweden", Journal of mines, metals & fuels, vol. 57, no. 9. Scott, A., Cocker, A., Djordjevic, N., Higgins, M., La Rosa, D., Sarma, K. & Wedmair, R. 1996, Open Pit Blast Design-Analysis and Optimization, Julius Kruttschnitt Mineral Research Center, University of Queensland. Sjöberg, J. 1996, Large Scale Slope Stability in Open Pit Mining-A Review, Luleå University of Technology. Workman, L. & Eloranta, J. The Effects of Blasting on Crushing and Grinding Efficiency and Energy Consumption, Calder & Workman Inc. ADDITIONAL BIBLIOGRAPHY Chadwik, J. 2008, Operation in Focus: Aitik 36. Chakraborty, A.K., Raina, A.K., Ramulu, M., Choudhury, P.B., Haldar, A., Sahu, P. & Bandopadhyay, C. 2004, "Parametric study to develop guidelines for blast fragmentation improvement in jointed and massive formations", Engineering Geology, vol. 73, no. 1--2, pp Cho, S.H. 2004, "Rock Fragmentation Control in Blasting", Materials Transactions, vol. 45, no. 5, pp to Cho, S.H. 2003, "Fragment Size Distribution in Blasting", Materials Transactions, vol. 44, no. 5, pp. 951 to 956. Demenegas, V. 2008, Fragmentation analysis of optimized blasting rounds in the Aitik mine, Luleå University of Technology. Hector Ivan, P.G. 2011, "Analysis of the state of the art of blast-induced fragment conditioning", Minerals Engineering, vol. 24, no. 14, pp Hustrulid, W. 1999, Blasting principles for open pit mining, Volume 1: General design concepts, A.A. Balkema. Larsson, L. 2011, Utredning av fragmentering med hjälp av elektroniskt programmerbara sprängkapslar i Aitikgruvan, Luleå University of Technology. Latham, J., Van Meulen, J. & Dupray, S. 2006, "Prediction of fragmentation and yield curves with reference to armourstone production", Engineering Geology, vol. 87, no. 1--2, pp Malmgren, J. 2011, Utredning av pallsprängning med lutande borrhål i Aitik, Luleå University of Technology. Marklund, P., Sjöberg, J., Ouchterlony, F. & Nilsson, N. "Improved Blasting and Bench Slope Design at the Aitik Mine". Melnikov, N.V., Marchenko, L.N., Zharikov, I.F. & Seinov, N.P. 1978, "Blasting methods to improve rock fragmentation", Acta Astronautica, vol. 5, no , pp Ozkahraman, H.T. 2006, "Fragmentation assessment and design of blast pattern at Goltas Limestone Quarry, Turkey", International Journal of Rock Mechanics and Mining Sciences, vol. 43, no. 4, pp Rustan, A. 1998, Rock Blasting Terms and Symbols, A dictionary of symbols and terminology in rock blasting and related areas like drilling, mining and rock mechanics, A.A. Balkema.

64 i APPENDIX I: Fragmentation analysis of FragMetrics software. Region: S1_210_13 Shovel: 1152 Number of bucket images processed: 462 Date range: May 9, :22:16 AM GMT+2:00 ~ May 20, :31:56 AM GMT+2:00 Duration: 11 days 5 hours 9 minutes Calibration bucket width: 460 cm Report date: May 20, :31:26 PM GMT+2:00 History view of P10 to P100 History view of P50, P80, and P100

65 ii Cumulative Rock Fragmentation Graph Table 1 Passing Percentage Numbers (unit: cm) P10 P20 P30 P40 P50 P60 P70 P80 P90 P100 fine Schumann distribution modulus = Schumann size modulus = 2.8 cm Table 2 Fragmentation Target Parameters Oversize 100 cm Undersize 5 cm Table 3 Fragmentation Results Percent Oversize 3.1 % Percent in Range 27.1% Percent Undersize 69.8% Generated by: Fragmetrics - Tablet

66 iii APPENDIX II: An introduction to Air-decking in Aitik. i. Introduction The utilization of air-decks in production blasting is a fairly new method in mining industry, although the concept has been studied and practiced since Melnikov was the first to introduce air gaps inside the blast hole and most of the early research on this topic has been conducted in the former Soviet Union (Lu and Hustrulid 2010). The main concept of air-decking consists of decreasing the amount of explosive and improving the blast-induced fragmentation by means of introducing air gaps in the explosive column. Theoretical studies and field experiments by Melnikov and Marchenko(1971), Chiappetta and Mammele(1987), Bussey and Borg(1995) and Jhanwar et al. (1999) show a decrease in mean fragment size, an increase in the uniformity of fragmentation, and also a decrease in explosive consumption by 10-30%. Laboratory experiments carried out by Fourney et al. (1981) regarding air decking in thick plexiglass blocks revealed that air decking increases the effect of shockwave on the material by a factor of 2 to 5. Lu and Hustrulid (2003) reviewed the theory of airdecking and provided guidelines regarding the application of this method. In spite of these studies, the mechanism of airdecking has still not been fully understood and utilization of this method does not always improve blasting results. ii. Theory Air-decking technique comprises the use of one or several air gaps in the explosive column in order to optimize the fragmentation and reduce the explosive consumption. The theory proposed by Melnikov and Marchenko (1971) hypothesizes that the air gap is a means of shockwave reflection within the borehole. The air-deck acts similar to a cushion and produces a series of aftershocks that extend the network of microfractures in the rock. The aftershocks are produced by three main pressure fronts: shock front, pressure front due to

67 iv formation of explosion products behind the detonation front and reflected waves from the end of explosive column. Although the air-deck causes a reduction in borehole pressure, the repeated loading of the rock by a series of aftershocks prolongs the action time of the shockwave and results in improved breakage (Jhanwar et. al 1999). A series of tests by Fourney et al. (1981) in Plexiglass models supported Melnikov s theory. It was observed that the shockwave reflects back from the base of the stemming column and reinforces the stress field. This process is repeated several times; therefor the duration of the shockwave action is increased by a factor of 2-5. This mechanism leads to a larger volume of radially fractured material rather than heavy breakage in the area adjacent to the charge column, see Figure I.1. Figure I. 1: Development of crack network in Plexiglass under the influence of an air-decked explosive column (after Fourney et al. 1981). iii. Design Despite the confirmative results from field and lab tests, some important technical problems are still unsolved. The location of the air deck in the blast hole and the length of the air column are two of the main questions to which there are different answers proposed. Moxon et al. (1993) showed that as the length of the air-deck is increased the fragmentation

68 v becomes finer relative to that of a full-column charge. The reduction however is relatively small until a critical length is exceeded. The critical length depends on the strength and structure of the rock mass. From the model tests, a critical air-deck length of 30 35% of the original explosive column was determined. They concluded that a mid-column air-deck has a larger effect on fragmentation than that of the top or bottom air-deck. Liu and Katsabanis (1996) and Katsabanis (2001) found that there exists a minimum air deck length for the technique to be beneficial; they also found that variations to the top air deck, such as bottom and mid-column air decks do not make significant improvements in production blasting. Recent investigations by Hustrulid et al. (2003) also show that in case of top air decks, there is a minimum limit for the air-deck length to be effective on the fragmentation. The length of the air-deck is the most important parameter, so this limit has been determined empirically by several tests and it is presented as the Air-decking ratio, which is the ratio between the length of the air deck and the total length of the explosive column: R a L L + L a = (I.1) a e where R a is the air-decking ratio, L a is the length of the air-deck and L e is the length of the explosive in the column. The corresponding value for R, according to Hustrulid et. al (2003), is: R (I.2) For the current case in Aitik, the practical constraints do not allow a ratio as high as 0.3, so the following designs are suggested based on practical applicability of them in Aitik. As seen in Figure I.2, a total length of 18 m has been assumed for the boreholes. The length of the air-deck is suggested in accordance to rules of thumb and applicability in the site. The length of the deck is at minimum 2.5 meters that includes a safety margin for some immerging of the barrier into the emulsion.

69 vi Air-decking ratio and amounts of reduction in explosive are mentioned in table 1 to provide a comparison between the options. The price of emulsion explosive and the diameter of the borehole are assumed 5 SEK/litre and 318mm respectively 4. Figure I. 2: Suggestions for air-decking in Aitik; a)original design, b)2.5m air-deck, no charge reduction, c) 3m air-deck, reduced charge, d) 2.5m air-deck, reduced charge. Tabe I. 1: A comparison of the designs and cost reductions per hole. Type Charge column (m) Air column (m) Stemming (m) Air-decking ratio Charge reduction (litres) Cost reduction (SEK) a (original) b c d Since an extra cost will be added for the air-decking instrumentation, the c and d designs are favorable, because of their lower explosive cost. Between c and d, the latter has also the advantage of smaller reduction in amount of charge and an acceptable stemming length. 4 The price is a rough fictitious assumption.

70 vii iv. Implementation of air-deck The air gap in the blast hole is most commonly implemented through usage of balloons or gasbags. The gasbag or balloon is lowered to the desired depth in the blast hole and inflated; upon inflation, the air pressure inside the balloon fixes it inside the hole and depending on the location of the air-deck, stemming or explosive is filled on top of the balloon. Different types of gasbags and balloons are available on the market, which can be categorized into two main groups: Chemically inflated and mechanically inflated. Chemical gasbags are inflated by means of chemical reactions of the material inside the bag; the reaction is either between two substances that are mixed when a button is pressed, or by a pressurized gas capsule. These gasbags are easy to implement and fairly cheap; they also take short time to install in production holes. Mechanically inflated gasbags are more like regular balloons modified to withstand high pressure of blast hole. These balloons are inflated through an air compressor, which can be easily installed on any truck. These balloons take comparatively shorter time for installation (10-20 seconds) and usually have a smaller chance of failure. The installation method for each group varies depending on the gasbags type and manufacture, see Figure I.3.

71 viii Figure I. 3: Left: Samples of commercially available balloons (Left) and gasbags (Right). v. Air-decking and Aitik conditions Aitik mine is located in northern Sweden with long and harsh winters; the temperature in the winter can reach -40 C. The extremely low temperatures can cause malfunctions in chemical gasbags or pressurized balloons. In addition to that, high level of groundwater causes the blast holes become filled with water almost instantaneously after drilling; lowering an inflating gasbag 3-4 meters deep into a water-filled hole is not a fast and easy task for production blasting. Previous tests of capsule-inflated gasbags were not successful due to low air pressure in cold weather; the technicians also faced difficulties in implementation process of the gasbags in the water-filled blast holes. Gasbags and balloons are usually lowered into the desired depth by a rope. In case of Aitik mine, a long piece of wood is used to force the bag into the water-filled holes. In a future tryout a modified type of capsule-inflated gasbags are going to be tested; the capsules are expected to function normally in cold weather, but the mechanism of inflation will still be problematic in water-filled areas of the mine. These gasbags have a diameter less than the