Document Type : Research Note

Authors

1 Department of Mining Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Department of Mining and Metallurgy Engineering, Amir Kabir University, Tehran, Iran.

3 Department of Mining Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran

4 Department of Petroleum, Mining and Material Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran

Abstract

Calculation of the specific charge and specific drilling before a blasting operation plays a significant role in the design of a blasting pattern and the reduction of the final extraction cost of minerals. In this work, the information from the Sungun, Miduk and Chah-Firouzeh copper mines in Iran was assessed, and it was found that there was a significant relationship between the specific charge and specific drilling and the hole diameter, bench height, uniaxial compressive strength and joint set orientation. After finding a technical and economic model to calculate the specific charge and specific drilling, this model was tested on the Sungun copper mine. Due to the insufficient consideration during the design of a blast pattern and because of the high hardness of the rocks in some parts of the mine, lots of destructive events such as boulders, back break, bench toe, high specific charge and high specific drilling, fly rock, and ground vibration in the blast operations were observed. The specific charge and specific drilling were found to be the most important technical and economic parameters involved in designing a blasting pattern, and they were found to play an important role in reducing the blasting cost. The blasting cost could be largely controlled by the accurate examination and computation of these parameters. An increase in the rock strength and the angle between the bench face and the main joint set would increase the specific charge and specific drilling. On the other hand, a specific charge and a specific drilling would decrease when the hole diameter increased in every range of the uniaxial compressive strength.

Keywords

[1]. Parsaei, M. (2010). Analysis of geomechanical and stability of Rock mass conditions in Sungun copper mine with numerical modeling, Journal of Earth & Resources, pp. 31-42.
[2]. Ghanizadeh Zarghami, A., Shahriar, K., Goshtasbi, K. and Akbari A. (2018). A model to calculate blasting costs using hole diameter, uniaxial compressive strength, and joint set orientation, In: The Southern African Institute of Mining and Metallurgy, Vol. 118, pp. 869-877.
[3]. Hudaverdi, T. (2012). Application of multivariate analysis for prediction of blast-induced ground vibrations, Soil Dynamics and Earthquake Engineering, Vol. 43, pp. 300-308.
[4]. Kecojevic, V. and Radomsky, M. (2005). Flyrock phenomena and area security in blasting-related accidents, Safety Science, Vol. 43, pp. 739-750.
[5]. Monjezi, M. and Rezaei, M. (2011). Developing a new fuzzy model to predict burden from rock geo-mechanical properties, Expert Systems with Applications, Vol. 38, pp. 9266-9273.
[6]. Elevli, B. and Arpaz, E. (2010). Evaluation of Parameters Affected on the Blast Induced Ground Vibration (BIGV) using Relation Diagram Method (RDM), Acta Montanistica Slovaca, Vol. 15, pp. 261-268.
[7]. Stojadinović, S., Pantović, R. and Žikić, M. (2011). Prediction of flyrock trajectories for forensic applications using ballistic flight equations, International Journal of Rock Mechanics and Mining Sciences, Vol. 48, pp. 1086-1094.
[8]. Inanloo Arabi Shad, H. and Ahangari, K. (2012). An empirical relation to calculate the proper burden in blast design of open pit mines based on modification of the Konya relation, International Journal of Rock Mechanics and Mining Sciences, Vol. 56, pp. 121-26.
[9]. Sanchidrián, J., Segarra, P. and López, L. (2006). A practical procedure for the measurement of fragmentation by blasting by image analysis, Rock Mechanics and Rock Engineering, Vol. 39, pp. 359-382.
[10]. Ghasemi, E., Amini, H., Ataei, M. and Khalokakaei, R. (2012). Application of artificial intelligence techniques for predicting the flyrock distance caused by blasting operation, Arabian Journal of Geosciences, pp. 1-10.
[11]. Kulatilake, P., Qiong, W., Hudaverdi, T. and Kuzu, C. (2010). Mean particle size prediction in rock blast fragmentation using neural networks, Engineering Geology, Vol. 114, pp. 298-311.
[12]. Michaux, S. and Djordjevic, N. (2005). Influence of explosive energy on the strength of the rock fragments and SAG mill throughput, Minerals Engineering, Vol. 18, pp. 439-448.
[13]. Morin, M.A. and Ficarazzo, F. (2006). Monte Carlo simulation as a tool to predict blasting fragmentation based on the Kuz-Ram model, Computers & Geosciences, Vol. 32, pp. 352-359.
[14]. Yari, M., Bagherpour, R., Jamali, S. and Asadi, F. (2015). Selection of Most Proper Blasting Pattern in Mines using Linear Assignment Method: Sungun Copper Mine, Arch. Min. Sci., Vol. 60, No 1, pp. 375–386.
[15]. Gate, W., Ortiz, B. and Florez, R. (2005). Analysis of rock fall and blasting backbreak problems, Paper ARMA/USRMS, Proceedings of the American rock mechanics conference, pp. 671-680.
[16]. Khandelwal, M. and Monjezi, M. (2012). Prediction of Backbreak in Open-Pit Blasting Operations using the Machine Learning Method, Rock Mechanics and Rock Engineering, pp. 1-8.
[17]. Monjezi, M., Amini Khoshalan, H. and Yazdian Varjani, A. (2012). Prediction of flyrock and backbreak in open pit blasting operation: a neuro-genetic approach, Arabian Journal of Geosciences, Vol. 5, pp. 441.
[18]. Monjezi, M. and Dehghani, H. (2008). Evaluation of effect of blasting pattern parameters on back break using neural networks, International Journal of Rock Mechanics and Mining Sciences, Vol. 45, pp. 1446-1453.
[19]. Monjezi, M., Rezaei, M. and Yazdian, A. (2010). Prediction of backbreak in open-pit blasting using fuzzy set theory, Expert Systems with Applications, Vol. 37, pp. 2637-2643.
[20]. Amini, H., Gholami, R., Monjezi, M., Torabi, S.R. and Zadhesh, J. (2011). Evaluation of flyrock phenomenon due to blasting operation by support vector machine, Neural Computing & Applications, pp. 1-9.
[21]. Bajpayee, T., Rehak, T., Mowrey, G. and Ingram, D. (1999, 2002). A Summary of Fatal Accidents due to flyrock and Lack of Blast Area Security in Surface Mining, 1989 to 1999, Proceedings of The Annual Conference on Explosives and Blasting Technique, ISEE, pp. 105-118.
[22]. Bajpayee, T., Bhatt, S.K., Rehak, T.R., Engineer, G., Mowrey, G.L. and Ingram, D.K. (2003). Fatal accidents due to flyrock and lack of blast area security and working practices in mining. Journal of mines, metals and fuels, Vol. 51, pp. 344-349.
[23]. Bajpayee, T., Rehak, T., Mowrey, G. and Ingram, D. (2004). Blasting injuries in surface mining with emphasis on flyrock and blast area security, Journal of Safety Research, Vol. 35, pp. 47-57.
[24]. Bajpayee, T., Verakis, H. and Lobb, T. (2004). An Analysis and Prevention of Flyrock Accidents in Surface Blasting Operations, Proceedings of The Annual Conference on Explosives and Blasting Technique, ISEE; 1999, pp. 401-410.
[25]. Ghasemi, E., Sari, M. and Ataei, M. (2012). Development of an empirical model for predicting the effects of controllable blasting parameters on fly rock distance in surface mines, International Journal of Rock Mechanics and Mining Sciences, Vol. 52, pp. 163-70.
[26]. Little, T., Blair, D. (2010). Mechanistic Monte Carlo models for analysis of flyrock risk, Rock Fragmentation by Blasting, pp. 641-647.
[27]. Ning, K. (1999). Prevention Measures for Controlling Flyrock in Engineering Blasting [J], Blasting.
[28]. Rehak, T., Bajpayee, T., Mowrey, G. and Ingram, D. (2001). Flyrock issues in blasting. Proceedings of the Annual Conference on Explosives and Blasting Technique, ISEE; 1999, pp. 165-176.
[29]. Rezaei, M., Monjezi, M. and Yazdian Varjani, A. (2011). Development of a fuzzy model to predict flyrock in surface mining, Safety Science, Vol. 49, pp. 298-305.
[30]. Tota E.W., Mudge K., Branson J.W., Georgiou P.N., Gavrilovic M. and Watson J.D. (2001). Method and apparatus for flyrock control in small charge blasting, Google Patents.
[31]. Ak, H., Iphar, M., Yavuz, M. and Konuk, A. (2009). Evaluation of ground vibration effect of blasting operations in a magnetite mine, Soil Dynamics and Earthquake Engineering, Vol. 29, pp. 669-676.
[32]. Bakhshandeh Amnieh, H., Siamaki, A. and Soltani, S. (2012). Design of blasting pattern in proportion to the peak particle velocity (PPV): Artificial neural networks approach, Safety Science, Vol. 50, pp.1913-1916.
[33]. Dehghani, H. and Ataee-Pour, M. (2011). Development of a model to predict peak particle velocity in a blasting operation, International Journal of Rock Mechanics and Mining Sciences, Vol. 48, pp. 51-58.
[34]. Guosheng Z., Jiang L. and Kui Z. (2011). Structural safety criteria for blasting vibration based on wavelet packet energy spectra, Mining Science and Technology, China, Vol. 21, pp. 35-40.
[35]. Iphar M., Yavuz M. and Ak H. (2008). Prediction of ground vibrations resulting from the blasting operations in an open-pit mine by adaptive neuro-fuzzy inference system, Environmental Geolog, Vol. 56, pp. 97-107.
[36]. Monjezi M., Ahmadi M., Sheikhan M., Bahrami A. and Salimi A. (2010). Predicting blast-induced ground vibration using various types of neural networks, Soil Dynamics and Earthquake Engineering, Vol. 30, pp. 1233-1236.
[37]. Shuran L. and Shujin L. (2011). Applying BP Neural Network Model to Forecast Peak Velocity of Blasting Ground Vibration, Procedia Engineering, Vol. 26, pp. 257-263.
[38]. Gheibie, S., Aghababaei, H., Hoseinie, S.H. and Pourrahimian, Y. (2009). Modified Kuz-Ram Fragmentation Model and its use at the Sungun Copper Mine, International Journal of Rock Mechanics and Mining Sciences, Vol. 46, pp. 967-73.
[39]. Faramarzi, F., Mansouri, H. and Farsangi, M.A. (2013). A rock engineering systems based model to predict rock fragmentation by blasting, International Journal of Rock Mechanics and Mining Sciences, Vol. 60, pp. 82-94.
[40]. Ghanizadeh Zarghami, A., Shahriar, K., Goshtasbi, K. and Akbari, A. (2017). Assessing the most important economic parameters of surface mine blasting using ANP method, In: Technical Exhibition of the 4th National Open Pit Mining Conference. Kerman University, Iran, pp. 9-19.
[41]. Ghanizadeh Zarghami A., Shahriar K., Goshtasbi K. and Akbari A. (2018). An investigation into the extremum points of the specific charge for presentation of models to calculate of burden in three copper mines in Iran, In: The 1st National Conference of Modeling in Mining Engineering, https://www.civilica.com/Paper-NCMME01-NCMME01_032.html.
[42]. Afum B.O. and Temeng V.A. (2014). Reducing Drill and Blast Cost through Blast Optimization: A Case Study, In: GMJ. 3rd UMaT Biennial International Mining and Mineral Conference, Ghana, pp. 137-45.
[43]. Adebayo, B. and Akande, J.M. (2015). Effects of Blast-Hole Deviation on Drilling and Muck-Pile Loading Cost, International Journal of Scientific Research and Innovative Technology, Vol. 2, No. 6. pp. 64-73.
[44]. Adebayo, B. and Mutandwa, B. (2015). Correlation of Blast-hole Deviation and Area of Block with Fragment Size and Fragmentation Cost, International Research Journal of Engineering and Technology, Vol. 2, pp. 402-06.
[45]. Nenuwa, O.B., Jimoh, B.O. (2014). Cost Implication of Explosive Consumption in Selected Quarries in Ondo and Ekiti State, International Journal of Engineering and Technology, Vol. 4, pp. 402-09.
[46]. Cunningham, C. (2013). Blasting for construction some critical aspects, Civil Engineering, Vol. 21, pp. 11-21.
[47]. Strelec S., Gazdek M. and Mesec J. (2011). Blasting Design for Obtaining Desired Fragmentation, Technical Gazette, Vol. 18, pp. 79-86.
[48]. Alipour A. and Ashtiani M. (2011). Fuzzy modeling approaches for the prediction of maximum charge per delay in surface mining, International Journal of Rock Mechanics and Mining Sciences, Vol. 48, pp. 305-10.
[49]. Dey, K. and Sen, P. (2003). Concept of Blastability – An Update. The Indian Mining and Engineering Journal, vol. 42, No. 8-9, September, pp. 24-31.
[50]. Kim, K. (2006). Blasting Design Using Fracture Toughness and Image Analysis of the Bench face and Muckpile , Virginia, Polytechnic Institute and state University, p. 137.
[51]. Ghazanfari nia, J. and Hoshangi, A. (2006). Predictive methods of the specific charge in open-pit mines blasting, in Fifth Student Conference on Mining Engineering, Isfahan.
[52]. Bhanwar, S.C. and Kumar, S. (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, pp. 132-8.
[53]. Cunningham, C.V.B. (1987). Fragmentation estimations and the Kuz–Ram model – four years on. Proceedings of Second International Symposium on Rock Fragmentation by Blasting, Keystone, Colorado. pp 475–487.
[54]. Tomi, G., Seccatore, J., Dempieri, M. and Rezende, A. (2011). Blasting Fragmentation Management using Complexity Analysis, in 6th Brazilian Congress on Open-Pit Mining, Brazil, Vol. 64, Pagine525-530.
[55]. Lilly, P.A. (1986). An empirical method of assessing rock mass blastability. Proceedings of the Large Open-Pit Conference, IMM, Australia, 89–92.
[56]. Kuzentsov, V. (1973). The mean diameter of fragments formed by blasting rock, Sovier Mining Science, pp. 144-8.
[57]. Rusten, P. and Kou S. (1993). Computerized design and result prediction of bench blasting, in fragblast-4A, Rotterdam.
[58]. Osanloo, M. (2013). Surface mining methods, Amirkabir University of Technology, Tehran, Vol. 1, 2, 3rd edition, p. 1070.
[59]. Pokrovsky, M. (1980). "Underground Structure and Mines Construction Practices," in Chapter 1, Blasting Parameters, p. 13.