Optimisation of Drill and Blast Parameters Using Emperical Fragmentation Modelling

Transcription

1 Optimisation of Drill and Blast Parameters Using Emperical Fragmentation Modelling J. B. Ninepence, E. J. A. Appianing, B. A. Kansake and R. Amoako Ninepence, J. B, Appianing, E. J. A., Kansake, B. A., and Amoako, R., Optimisation of Drill and Blast Parameters Using Emperical Fragmentation Modelling, 4 th UMaT Biennial International Mining and Mineral Conference, pp.mp Abstract The products from blasting affect all downstream operations like loading, hauling and processing. Therefore, blasts should be designed to produce fragments that will optimise these downstream processes. This paper analysed the blast output of Boss Mining Company Limited (BMCL), an open pit mine in Tarkwa in the Western Region of Ghana, using Split-Desktop Software for fragmentation analysis. The results showed that the mean fragmentation of the mine using current drill and blast parameters were below the expected mean fragment size of 415 mm. Blast optimisation was therefore carried out using the Kuz-Ram Model prosposing two options by varying the spacing and burden. Option 1 proposed a spacing of 5 cm and burden of 4.7 cm which resulted in an expected mean fragment size of cm while Option 2 proposed a spacing and burden of 5.5 cm and 5.0 cm respectively resulting in an expected mean fragment size of cm. Cost savings of 35.37% for Option 1 and 30.6% for Option 2 are expected to be made. Trial blasts should be conducted with the proposed paramters to ascertain the expected results. The parameters should be also evaluated to predict the environmental impacts (like airblast, ground vibration and flyrocks) that will result from their implementation. Keywords: Kuz-Ram model, Optimisation, Emperical modelling 1 Introduction In hard rock mining, blasting is the most productive excavation technique applied to fragment in situ rock to the required size for effective loading and processing (Vasileois, 2008; Siddiqui et al., 2009 and Engin, 2010). In order to blast the in situ rock to the desired fragment size, blasts are designed considering controllable (bench height, hole diameter, spacing, burden, hole length, bottom charge, specific charge) and uncontrollable (rock strength, discontinuity spacing and orientation, rock density) factors to ensure that the desired blast output is achieved to optimise downstream processes as blast output is known to affect the efficiency and cost of downstream processes like loading, hauling and processing (Siddiqui et al., 2009). At Boss Mining Company Limited (BMCL), drill and blast operations are conducted by African Mining Services (AMS) with an expected mean fragment size of 415 mm. The current drill and blast parameters employed by the mine result in mean fragment sizes that are below the expected. There is therefore the need for an evaluation of the parameters to obtain optimal paramters that will result in the expected fragmentation. This paper therefore assessed the current drill and blast parameters of the mine and conducted blast optimisation studies using the Kuz-Ram model which is the most widely used empirical fragmentation model for surface blast modelling (Cunningham, 2005). 2 Resources and Methods 2.1 Resources BMCL is an open pit mine located in Tarkwa in the Western Region of Ghana, about 70 km North of the port city of Takoradi and 320 km West of Accra, Ghana s capital city (Kwaha, 2010). It is located approximately on longitude 2 02 West and latitude 5 14 North. It is within the tropical rain forest of Ghana with temperatures ranging from 24 C to 36 C, humidity ranging from 60% to above 90% and an average annual rainfall of mm (Al-Hassan, 2007). Geologically, BMCL is located within the Tarkwaian group of rocks with gold mineralisation confined to about a 50 m thick section of the Banket conglomerate unit (Griffins et al., 2002). Data was collected from the blast reports of BMCL on the current drill and blast parameters of the mine (Table 1). Multiple muckpile images (Fig. 1) were also taken for two shots at the mine for fragmentation analysis. These were taken after a visual inspection of the muckpile to ensure representativeness. They were acquired using a MP 25

2 digital camera. Two metallic poles of length 1.5 m were used as scaling objects. Data on the rock properties of the mine (Table 2) were also obtained through rock sampling and laboratory analysis (for uniaxial compressive strength and bulk density) and geotechnical cell mapping for the discontinuity information and general rock description. Table 1 Design Parameters for Shots 1 and 2 Shot Shot Parameter Units 1 2 Burden m Spacing m Hole Depth m Charge Length m Bench Height m Hole Diameter mm Sub-drill m Drilling Deviation m Stemming Height m Amount of kg Explosives Per Hole Rock Density kg/m Powder Factor kg/m Fragmentation optimisation was conducted using the Kuz-Ram model consists of three key equations (Cunningham, 2005): Kuznetsov s equation This equation (Eqn. 1) is for estimating the mean fragmentation expected from the use of selected blast parameters. X = AK 0.8 Q 1/6 ( 115/RWS) 19/20 (1) m Where: X m is the mean fragment size, cm; A is the rock factor; K is the powder factor, kg/m 3 ; Q is the quantity of explosives per hole, kg; RWS is the relative weight strength of the explosive. Rosin-Rammler s equation This equation (Eqn. 2) is for obtaining the expected fragmentation distribution from the selected blast parameters. [ 0.693( ) n ] R X = exp X/X m (2) Where: R x is mass fraction retained on screen opening X; n is the Cunningham uniformity index. Uniformity Index equation Sample Image of Muckpile Fig. 1 Table 2 Rock Properties of BMCL Parameter Value Uniaxial Compressive Strength (MPa) Bulk density (tonnes/m 3 ) 2.39 Geological Strength Index, GSI (%) Joint spacing (m) 1.56 Moderately strong General rock description and blocky with slight weathering 2.2 Methods Fragmentation analysis was conducted using the image analysis technique (Split Desktop Version 3.0). Out of the numerous images taken for each shot, four images were analysed and combined in to represent the fragmentation from each shot. This equation (Eqn. 3) otherwise known as the Rosin-Rammler exponent characterises the geometric blast design parameters. 1 S / B BCL CCL n / 2 L B / D 1 W / Babs 0.1 L H 0.1 (3) where; B is the burden, m; S is the spacing, m; D is the hole diameter, mm; W is the standard deviation of drilling precision, m; L is the charge length, m; BCL is the bottom charge length, m; CCL is the column charge length, m; H is the bench height, m. When staggered pattern is used, this equation is multipled by a factor of 1.1 as this pattern is known to improve the uniformity with about 10%. The rock mass factor, A (in Eqn. 1), can be estimated using Eqn. 4. = 0.06( RMD + RDI + HF) A (4) Where MP 26

3 RMD is the Rock Mass Description [10 (powdery/ friable rock), JF (if vertical joints) or 50 (massive rock)]; JF is the Joint Factor (JPS + JPA); JPS is the Joint/discontinuity Plane Spacing [10 (average joint spacing < 0.1 m), 20 (0.1< average joint spacing < 1 m) or 50 (average joint spacing > 1 m)]; JPA represents the Joint/discontinuity Plane Angle/Orientation [20 (dip out of face), 30 (strike perpendicular to face) or 40 (dip into face)]; RDI is the Rock Density Influence = (0.25 ρ - 50) where ρ is in kg/m 3 ; HF is the hardness factor [(E/3) if the E < 50 GPa or (σ c /5) if E > 50 GPa)]; E is the Young s modulus of the rock while σ c is the uniaxial compressive strength. 3 Results and Discussion 3.1. Fragmentation Analysis The results of the fragmentation analysis for the two shots considered are summarised in Table 3. Table 3 Combined Distribution for Shots 1 and 2 Size (mm) Shot 1 Shot 2 % Passing F F F F F F F F F Top Size (99.95) At BMCL, the desired mean fragment size (F50) is 415 mm and the crusher gape is mm. From Table 3, the F50 for both shots 1 and 2 are below the desired size by 37.5% and 24.1% respectively. Also, the top size (99.95% passing) of the two shots were significantly (>36%) below the crusher gape of mm. Though these results are finer than the expected, extra cost may be incurred in achieving this finer fragmentation without a corresponding improvement in plant performance to warrant this extra cost. Therefore, blast optimisation was conducted to evaluate the possibility of modifying blast design to obtain results that compared well with the desired outcomes Blast Optimisation The spacing and burden were varied as shown in Table 4. The results expected from this variation were predicted and are presented in Fig. 2. The expected drilling and blasting cost and mean fragmentation (X 50 ) are also presented in Table 4. Table 4 Blast Optimisation Results Parameter Current Data Proposed Options Shot 1 Shot Burden (m) Spacing (m) X 50 (cm) Cost/BCM ($/m 3 ) Percent Passing 100% 80% 60% 40% 20% % Size (cm) Option 1 Option 2 Fig. 2 Kuz-Ram Predictions for Proposed Options With the proposed spacing and burden, the mean fragmentation expected is very close to the desired fragmentation of the mine as option 1 deviates by only 1% while option 2 has a deviation of 7%. These compare better with the desired mean fragment size than the current paramters that deviated with 37.5% and 24.1% respectively for shots 1 and 2. Proposed options 1 and 2 if adopted, will result in powder factors of 0.35 kg/m3 and 0.38 kg/m3 respectively which are consistent with the recommendations of Choudhary and Sonu (2013) for rocks of medium strength as occurs at BMCL. The powder factor of the mine will thus reduce significantly by 43.5% and 38.7% if options 1 and 2 respectively were adopted to replace the MP 27

4 parameters used in shot 1 while a reduction of about 20% and 14% could be attained if options 1 and 2 respectively are adopted to replace the parameters used in shot 2. Additionally, the cost of drilling and blasting are expected to decrease significantly by 35.37% ($1.47/bcm to $0.95/bcm) for Option 1 and 30.6% ($1.47/bcm to $1.02/bcm) for Option 2 when compared against shot 1 while a cost reduction of 19.49% ($1.18/bcm to $0.95/bcm) for Option 1 and 13.55% ($1.18/bcm to $1.02/bcm) for Option 2 can be achieved as to shot 2. When 80% of the blasted materials are able to pass through the crusher gape, industry players consider it satisfactory as boulder formation is difficult to eliminate from blasting. From Fig. 2, this requirement is met by the proposed options as over 80% of the material have sizes less than the crusher gape of mm. 4 Conclusions and Recommendations It is concluded from the study that the current drill and blast paramters of the mine result in finer fragmentation than the desired. Blast optimisation has successfully been carried out utilising the Kuz- Ram fragmentation model that has proposed two options by varying the spacing and burden. The proposed options will produce results closer to the desired with the mean fragmentation expected to deviate by a negligible amount (1% and 7%) if the proposed options are adopted. Also there will be a reduction in the powder factor with corresponding cost savings of over 30% if these options are adopted. It is thus recommended that pilot blasts be conducted using the proposed parameters to ascertain the expected results. Blast prediction (ground vibration, airblast and flyrock) modelling should be conducted using these proposed options to know the expected impact on the environment. References Al-Hassan, S. (2007), A Comparative Study of Rainfall in Tarkwa Mining District of Ghana, Ghana Mining Journal, Vol. 9, pp Choudhary, B. S. and Sonu, K. (2013), Assessment of Powder Factor in Surface Bench Blasting Using Schmidt Rebound Number of Rock Mass, International Journal of Research in Engineering and Technology, Vol. 2, No. 12, pp Cunningham, C.V.B. (2005), The Kuz-Ram Fragmentation Model 20 Years On, 3 rd International Conference of Explosives and Blasting, R. Holmberg Et Al., Brighton, England, pp Engin, I. C. (2010), A Practical Method of Bench Blasting for Desired Fragmentation based on Digital Image Processing Technique and the Kuz-Ram Model, Afyon Kocatape University, Iscehisar Vocational School, Iscehisar, Afyonkarahisar. Griffins, R. F., Barning, K., Agezo, F. L. and Akosa, F. K. (2002), Gold Deposit of Ghana, Minerals Commission, Accra, Ghana, pp Kwaha, J. Z. (2010), Geostatistical Mineral Resource Estimation Using Conidtional Simulation at AngloGold Ashanti, Iduapriem Mine, Tarkwa, Unpublished MSc. Thesis Report, University of Mines and Technology, Tarkwa, 60 pp. Siddiqui, F. I., Shah, S. M. A. and Behan, M. Y. (2009), Measurement of Size Distribution of Blasted Rock Using Digital Image Processing, JKAU: Eng. Sci., Vol. 20, No. 2, pp Vasileios, D. (2008), Fragmentation Analysis of Optimised Blasting Rounds in the Aitik Mine Effect of Specific Charge, Unpublished Masters Thesis Report, Luleå University of Technology, Sweden, 108 pp. Authors J. B. Ninepence holds a BSc in Mining Engineering from the University of Mines and Technology, Tarkwa. His research interests include explosives and blasting, blast optimsation and Mineral Project Evaluation. E. J. A. Appianing holds HND in Building Technology from Kumasi Polytechnic. He also holds BSc and MPhil degrees in Mining Engineering from the University of Mines and Technology, Tarkwa, Ghana. He is currently an Assistant Lecturer in the Mining Engineering Department of the University of Mines and Technology, Tarkwa, Ghana. Areas of his research interest are Mine Planning and Design, Operations Research and Mineral Economics. B. A. Kasanke holds an MPhil and a BSc in Mining Engineering. He is currently a Demonstrator at the University of Mines And Technology (UMaT), Tarkwa, Ghana.. His research interests are in Simulation of Mining Systems, Operations Reseacrh in Mining, Explosives and Rock Fragmentation, Blats Optimisation, Environmental Impacts of Blasting and Small Scale Mining. Richard Amoako is a holder of MPhil. and BSc. (Hons.) degrees in Mining Engineering from the University of Mines and Technology (UMaT), Tarkwa. He is currently an Assistant Lecturer at the Mining Engineering Department of UMaT. His research interests are in the areas of Geostatistics and the Environmental and Economic Sustainabilbity of Small Scale Mining. He is a graduate member MP 28

5 of the Australasian Institute of Mining and Metallurgy (AusIMM), Australia. MP 29