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Название Uncertainty consideration in rock mass blastability assessment in open pit mines using Monte Carlo simulation
DOI 10.17580/em.2021.01.07
Автор Bameri A., Cheraghi Seifabad M., Hoseinie S. H.
Информация об авторе

Department of Mining Engineering, Isfahan University of Technology, Isfahan, Iran:

Bameri A., Researcher, Master of Science
Cheraghi Seifabad M., Associate Professor, Doctor of Philosophy
Hoseinie S. H., Assistant Professor and Head of Laboratory, Doctor of Philosophy, hadi.hoseinie@iut.ac.ir


Blastability is defined as the resistance of rock mass to fragmentation due to the dynamic stress of blasting. Comprehensive study and understanding of geomechanical conditions of the in-situ rock mass are necessary to analyze the blastability along with optimal blasting design. Blastability Index (BI) is one of the most widely applied methods for the classification of rock mass and predicting the specific charge of blasting in open pit mines. Regarding the existence of uncertainty in the geomechanical characteristics of in-situ rock masses, accurate BI assessment requires a wide range of field studies. It could lead designers to a wrong decision about rock mass classification. Simulation is one of the reliable and applicable approaches to overcome the geomechanical uncertainties in rock mass studies. Therefore, in this paper, the Monte Carlo simulation method has been applied to blastability assessment in Sungun Copper Mine, Iran. For this purpose, the geological factors, including rock mass description, joint plane spacing, joint plane orientation, specific gravity influence, and hardness, were measured and implemented in 46 points of the pit wall. Statistical analysis was carried out to find out the best fit-distribution functions of all mentioned parameters. After that, the Monte Carlo simulation program was developed and carried out in MATLAB software. The overall results of the simulation reveal that the Monte Carlo method could provide a better vision of any possible combination of geological factors. It is also found out that less than two percent of the rock masses do have challenging blastability conditions, and the average blastability of rock masses in the studied mine is 18, which is close to an average score of blastability classification as well.

Ключевые слова Classification, mixed-face bench, blasting, fragmentation
Библиографический список

1. Menzhulin M. G., Khoreva A. Y. Afanasiev P. I., Tyulkin S. A. Drilling and blasting parameters for Gavrilovo granite deposit. Gornyi Zhurnal. 2017. No. 1, pp. 42–46. DOI: 10.17580/gzh.2017.01.08
2. Taherkhani H., Doostmohammadi R. Transportation costs: a tool for evaluating the effect of rock mass mechanical parameters on blasting results in open pit mining. Journal of Mining Science. 2015. Vol. 51. pp. 730–742.
3. Kazakov N. N. The destruction and crushing of rocks in open cast mine. Explosion Technology. 2017. Vol. 118/75. pp. 5–19.
4. Singh D., Sastry. V. Influence of structural discontinuity on rock fragmentation by blasting. Proceedings of the 6th International Symposium on Intense Dynamic Loading and its Effects. Beijing, China, June 3–7 1986.
5. Ghosh A., Daemen J., Van Zyl D. Fractal-based approach to determine the effect of discontinuities on blast fragmentation. The 31st U.S Symposium on Rock Mechanics (USRMS). Golden, Colorado, USA, 18–20 June 1990.
6. Mehrdanesh A., Monjezi M., Sayadi A. R. Evaluation of the effect of rock mass properties on fragmentation using robust techniques. Engineering with Computers. 2018. Vol. 34(2). pp. 253–260.
7. Akbari M., Lashkaripour Gh., Yarahamdi Bafghi A., Ghafoori M. Blastability evaluation for rock mass fragmentation in Iran central iron ore mines. International Journal of Mining Science and Technology. 2015. Vol. 25(1). pp. 59–66.
8. Tyupin V. N., Anisimov V. N. Effect of Geological and Geophysical Characteristics of Complex-Structure Ferruginous Quartzite Ore Bodies on Blasting and Processing Performance. Journal of Mining Science. 2018. No. 54. pp. 48–52.

9. Viktorov S. D., Kazakov N. N., Shlyapin A.V. Crushing rock between two charges and at an extreme charge in the top layer of the opencast bench. Explosion Technology. 2017. Vol. 118/75. pp.18–30.
10. Khademian A., Bagherpour R. Alteration of grindability of minerals due to applying different explosives in blasting operation. Minerals Engineering. 2017. Vol. 111. pp. 174–181.
11. Ghasemi E., Sari M., Ataei M. Development of an empirical model for predicting the effects of controllable blasting parameters on flyrock distance in surface mines. International Journal of Rock Mechanics and Mining Sciences. 2012. Vol. 52. pp. 163–170.
12. Morin M. A., Ficarazzo F. Monte Carlo simulation as a tool to predict blasting fragmentation based on the Kuz–Ram model. Computers & Geosciences. 2006. Vol. 32(3). pp. 352–359.
13. Xiao S., Li K., Ding X., Liu T. Rock mass blastability classification using fuzzy pattern recognition and the combination weight method. Mathematical Problems in Engineering. 2015. Article 724619.
14. Viktorov S. D., Zakalinsky V. M., Osokin A. A. Theoretical background of large-scale and selective blasting effect on rocks in complex ground conditions. Journal of Mining Science. 2014. Vol. 50. pp.1040–1046.
15. Lilly P. An empirical method of assessing rock mass blastability. Proceeding of Large Open Pit Mining Conference. Melborn, Australia,1986. рр. 89–92.
16. Latham J. P., Lu P. Development of an assessment system for the blastability of rock masses. International Journal of Rock Mechanics and Mining Sciences. 1999. Vol. 36(1). pp. 41–55.
17. Chatziangelou M., Christaras B. Blastability Index on Poor Quality Rock Mass. International Journal of Civil Engineering (IJCE), 2013. Vol. 2(5). pp. 9–16.
18. Chatziangelou M., Christaras B. A. New Development of BQS (Blastability Quality System) for Closely Spaced Formations. Journal of Geological Resource and Engineering. 2017. Vol. 1. pp. 24–37.
19. Feng X. A neural network approach to comprehensive classification of rock stability, blastability and drillability. International Journal of Surface Mining and Reclamation. 1995. Vol. 9(2). pp. 57–62.
20. Azimi Y., Osanloo M., Aakbarpour-Shirazi M., Aghajani Bazzazi A. Prediction of the blastability designation of rock masses using fuzzy sets. International Journal of Rock Mechanics and Mining Sciences. 2010. Vol. 47(7). pp. 1126–1140.
21. Hoseinie S. H., Pourrahimian Y., Fardin N., Aghababaei H. Determination of blasting Index (BI) to predict the fragmentation amount and blasting efficiency of Sungun copper mine using Rock Mass index(RMi). 8th International Conference on Rock Fragmentation by Blasting (Fragblast-8). Santiago, Chile. May 7–11 2006. рр. 321–325.
22. Norov Y. D., Bunin Z. V., Nutfullaev G. S., Zairov Sh. Sh. Intensification of bla sting of different quality rock masses using explosive charges with cumulative effect. Gornyi Zhurnal. 2016. No. 2. pp. 16–20. DOI: 10.17580/gzh.2016.02.03
23. Chatziangelou M., Christaras B. A Geological Classification of Rock Mass Quality and Blast Ability for Widely Spaced Formations. Journal of Geological Resource and Engineering. 2016. Vol. 4. pp. 160–174.
24. Metropolis N., Ulam S. The Monte Carlo method. Journal of the American statistical association. 1949. Vol. 44(247). pp. 335–341.
25. Johansen A., Evers L. Monte Carlo methods. Lecture notes. University of Bristol, 2007. 128 р.
26. Halton J. H. A retrospective and prospective survey of the Monte Carlo method. Siam Review. 1970. Vol. 12(1). pp. 1–63.

Полный текст статьи Uncertainty consideration in rock mass blastability assessment in open pit mines using Monte Carlo simulation