Energy Factor-Based Blast Design in Large Opencast Coal Mines
Large surface coal mines in produce millions of tons of coal per annum, moving millions of cubic meters of overburden to mine the coal. Much of this volume is blasted in the form of benches, a common mining technique (Gustafsson, 1973). Blasting is a part of Large Opencast Coal Mine (LOCCM) operations, and is scheduled based on production requirements. With dragline pits, equipment size and operating parameters allow engineers to use tall benches and methods like cast blasting or production dozing to assist with moving blasted material. Changes in scale of equipment and speed of production scheduling have brought about a multi-dimensional shift in the planning process for drilling and blasting team at large surface coal mine operations. So, the problem is that while equipment scale and pace of planning have drastically changed over the last decade blast design and the explosive selection criteria has not changed significantly. Work done by eminent researchers such as Richard Ash and Calvin Konya set the standard for today’s scientific bench blast design practices. Recently, the explosive’s engineering community has largely occupied themselves with applying technology to subsets of the design problem – how to improve or measure fragmentation (M. Monjezi, 2009), how to use technologically advanced methods to design blasts (Y. Azimi, 2010) (P.D. Katsabani, 2005), the public’s perception of mining (Hoffman, 2013). Explosives research for surface coal mining has essentially ignored bench blasting; the industry has not notably recognized the fundamental differences in scale and operational tempo that separate large surface mine blast from regular quarry-scale bench blasting. There is a vast scope of research in the field for explosive energy-based design for better fragmentation with less risk.
Bond, F.C. 1952. The third theory of comminution. Trans. AIMM 193: 484.
Bond, F.C. & Whittney, B.B. 1959. The work index in blasting. Quarterly of the Colorado School of Mines 54(3): 77–82.
Central Electricity Authority, 2015. Growth of Electricity Sector in India from 1947-2015. Ministry of Power, India.
Cunningham CV. Keynote address—optical fragmentation assessment, a technical challenge. InMeasurement of Blast Fragmentation, Proceedings of the FRAGBLAST 1996 (Vol. 5, pp. 13-19). DOI: https://doi.org/10.1201/9780203747919-4
Esen S, Bilgin HA, BoBo T. Effect of explosive on fragmentation. InThe 4th Drilling and Blasting Symposium, Ankara, Turkey 2000 (Vol. 6372).
Franklin, J.A., Kemeny, J.M. &Girdner, K.K. 1995. Evolution of measuring systems: A review. In J.A. Franklin & T. Katsabanis (eds.), Measurement of blast fragmentation: 47–52. Rotterdam: Balkema. DOI: https://doi.org/10.1201/9780203747919-8
Kanchibotla SS, Morrell S, Valery W, O’Loughlin P. Exploring the effect of blast design on SAG mill throughput at KCGM. InMine to Mill. Conference. Brisbane 1998.
Kojovic T, Michaux S, McKenzie C. Impact of blast fragmentation on crushing and screening operations in quarrying. InProceedings of the EXPLO 1995 Conference, Brisbane, QLD 1995 (pp. 427-435).
Lizotte, Y., Scoble, M.J., Singh, A. &Mohanty, B. 1993. Prediction and assessment of fragmentation in under-ground mine. In H.P. Rossmanith (ed.), Proc. 4th Int. Symp. on Rock Fragmentation by Blasting, Vienna, 5–8 July, pp. 361–368. Rotterdam: Balkema.
Leung CS, Meisen P. How electricity Consumption affects social and economic development by comparing low, medium and high human development countries. Retrieved November. 2005;10:2013.
Michaux S, Djordjevic N. Influence of explosive energy on the strength of the rock fragments and SAG mill throughput. Minerals engineering. 2005 Apr 30;18(4):439-48. DOI: https://doi.org/10.1016/j.mineng.2004.07.003
Monjezi M, Rezaei M, Yazdian A. Prediction of backbreak in open-pit blasting using fuzzy set theory. Expert Systems with Applications. 2010 Mar 15;37(3):2637-43. DOI: https://doi.org/10.1016/j.eswa.2009.08.014
Monjezi M, Ghafurikalajahi M, Bahrami A. Prediction of blast-induced ground vibration using artificial neural networks. Tunnelling and underground space technology. 2011 Jan 31;26(1):46-50. DOI: https://doi.org/10.1016/j.tust.2010.05.002
Nielson, K. 1983. Optimisation of open-pit blasting. Proc. 1st Int. Symp. on Rock Fragmentation by Blasting, Lulea, Sweden, 22–26 August, pp. 653–664.
Raina AK. A history of digital image analysis technique for blast fragmentation assessment and some Indian contributions. Electrical Measuring Instruments and Measurements. 2012 Nov 5:3. DOI: https://doi.org/10.1201/b13761-3
Raina AK, Ramulu M, Choudhury PB, Chakraborty AK, Sinha A, Ramesh-Kumar B, Fazal M. Productivity improvement in an opencast coal mine in India using digital image analysis technique. In Fragmentation by Blasting, Proceedings of the 9th Int. Symp. On Rock Fragmentation by Blasting—Fragblast 2010 Sep (Vol. 9, pp. 13-17).
Singh, S., 1993. Damage causing potential of different explosives. In: Proc. of the Ninth Annual Symposium on Explosives and Blasting Research, California USA, pp. 325–337.