A new classification approach for prediction of flyrock throw in surface mines

  • Turker HudaverdiEmail author
  • Ozge Akyildiz
Original Article


A novel classification approach was proposed for prediction of flyrock throw distance based on the site measurements performed in a sandstone quarry. The classification approach was created by using multiple discriminant analysis (MDA) technique. The input parameters of discriminant analysis are blast design parameters and a rock mass parameter. The grouping stage of classification was performed considering a well-known blast regulation for flyrock. Additionally, multiple regression analysis technique applied to blast data to create a flyrock prediction equation. By this way, the capability and differences of the classification approach were investigated. Model validation was performed on the test blasts. MDA model successfully estimated the flyrock throw distance. Unlike the classical prediction models, the MDA model predicts severity of flyrock throws instead of a numerical value. MDA model can be easily practiced by the created territorial map. The model does not require any specific software or training for usage and suitable for practical applications at mines.


Blasting Flyrock Classification Discriminant analysis Regression analysis 



This study was partly supported by the Research Fund of the Istanbul Technical University (project name: ‘The effects of the variations in blast design and initiation systems on blast induced ground vibrations. No: 38511). The authors are grateful to the Research Fund of the Istanbul Technical University for their financial support.


  1. Adhikari GR (1999) Studies on flyrock at limestone quarries. Rock Mech Rock Eng 32:291–301. doi: 10.1007/s006030050049 CrossRefGoogle Scholar
  2. Aler J, Du Mouza J, Arnould M (1996) Evaluation of blast fragmentation efficiency and its prediction by multivariate analysis procedures. Int J Rock Mech Min Sci Geomech Abstr 33:189–196. doi: 10.1016/0148-9062(95)00055-0 CrossRefGoogle Scholar
  3. Alipour A, Ashtiani M (2011) Fuzzy modeling approaches for the prediction of maximum charge per delay in surface mining. Int J Rock Mech Min Sci 48:305–310. doi: 10.1016/j.ijrmms.2010.11.010 CrossRefGoogle Scholar
  4. Amini H, Gholami R, Monjezi M, Torabi SR, Zadhesh J (2012) Evaluation of flyrock phenomenon due to blasting operation by support vector machine. Neural Comput Applic 21:2077–2085. doi: 10.1007/s00521-011-0631-5 CrossRefGoogle Scholar
  5. Armstrong JS, Collopy F (1992) Error measures for generalizing about forecasting methods: empirical comparisons. Int J Forecast 8:69–80. doi: 10.1016/0169-2070(92)90008-W CrossRefGoogle Scholar
  6. Ash RL (1963) The mechanics of rock breakage (part 2) – standards for blast design. Pit Quarry 56:118–122Google Scholar
  7. Bajpayee TS, Rehak TR, Mowrey GL, Ingram DK (2004) Blasting injuries in surface mining with emphasis on flyrock and blast area security. J Saf Res 35:47–57. doi: 10.1016/j.jsr.2003.07.003 CrossRefGoogle Scholar
  8. Bhandari S (1997) Engineering rock blasting operations. A. A, BalkemaGoogle Scholar
  9. Castro JT, Liste AV, Gonzales AS (1998) Blasting index for exploitation of aggregates. In: Proceedings of the 7th Mine Planning and Equipment Selection Calgary, pp. 165–168Google Scholar
  10. Cohen J, Cohen P, West SG, Aiken LS (2003) Applied multiple regression/correlation analysis for the behavioral sciences. Lawrence Erlbaum Associates Publishers, LondonGoogle Scholar
  11. Dowdy S, Wearden S, Chilko D (2004) Statistics for research − third edition. John Wiley & Sons Inc., HobokenGoogle Scholar
  12. Eltschlager KK (2004) Blasting applications for GPS. Proceedings of the Advanced Integration of Geospatial Technologies in Mining and Reclamation Atlanta, Georgia, In, pp 1–11Google Scholar
  13. Garson GD (2012) Discriminant function analysis −statistical associates blue book series. Statistical Associates Publishing, AsheboroGoogle Scholar
  14. Garson GD (2014) Multiple regression − statistical associates blue book series. Statistical Associates Publishing, AsheboroGoogle Scholar
  15. Ghasemi E, Sari M, Ataei M (2012) Development of an empirical model for predicting the effects of controllable blasting parameters on flyrock distance in surface mines. Int J Rock Mech Min Sci 52:163–170. doi: 10.1016/j.ijrmms.2012.03.011 CrossRefGoogle Scholar
  16. Ghasemi E, Ataei M, Hashemolhosseini H (2013) Development of a fuzzy model for predicting ground vibration caused by rock blasting in surface mining. J Vib Control 19:755–770. doi: 10.1177/1077546312437002 CrossRefGoogle Scholar
  17. Giraudi A, Cardu M, Kecojevic V (2009) An assessment of blasting vibrations: a case study on quarry operation. Am J Environ Sci 5:467–473. doi: 10.3844/ajessp.2009.467.473 CrossRefGoogle Scholar
  18. Hillier DE, Holywell PD, Jeffries RM, Scott IMB (1999) Limiting the instance of fly-rock from quarry operations, research report. WS Atkins Consultants Ltd., WarringtonGoogle Scholar
  19. Ho R (2014) Handbook of univariate and multivariate data analysis with IBM SPSS − second edition. CRC Press, Boca RatonGoogle Scholar
  20. Huberty CJ, Olejnik S (2006) Applied MANOVA and discriminant analysis −, second edn. John Wiley & Sons, New JerseyCrossRefGoogle Scholar
  21. Hudaverdi T (2012) Application of multivariate analysis for prediction of blast-induced ground vibrations. Soil Dyn Earthq Eng 43:300–308. doi: 10.1016/j.soildyn.2012.08.002 CrossRefGoogle Scholar
  22. Hudaverdi T, Kuzu C, Fisne A (2012) Investigation of the blast fragmentation using the mean fragment size and fragmentation index. Int J Rock Mech Min Sci 56:136–145. doi: 10.1016/j.ijrmms.2012.07.028 CrossRefGoogle Scholar
  23. Hustrulid WA (1999) Blasting principles for open pit mining−Vol 1 general design concepts. A. A, BalkemaGoogle Scholar
  24. IBM SPSS Statistics Base 20 (2011) IBM Corp., ArmonkGoogle Scholar
  25. Kahriman A (2004) Analysis of parameters of ground vibration produced from bench blasting at a limestone quarry. Soil Dyn Earthq Eng 24:887–892. doi: 10.1016/j.soildyn.2004.06.018 CrossRefGoogle Scholar
  26. Khandelwal M (2010) Evaluation and prediction of blast-induced ground vibration using support vector machine. Int J Rock Mech Min Sci 47:509–516. doi: 10.1016/j.ijrmms.2010.01.007 CrossRefGoogle Scholar
  27. Konya CJ, Walter EJ (1990) Surface blast design. Prentice Hall Int, USAGoogle Scholar
  28. Kuznetsov VM (1973) Mean diameter of fragments formed by blasting rock. Sov Min Sci 9:144–148. doi: 10.1007/bf02506177 CrossRefGoogle Scholar
  29. Landau S, Everitt BS (2004) A handbook of statistical analyses using SPSS. Chapman & Hall/CRC, Boca RatonGoogle Scholar
  30. Latham JP, Lu P (1999) Development of an assessment system for the blastability of rock masses. Int J Rock Mech Min Sci Geomech Abstr 36:41–55. doi: 10.1016/S0148-9062(98)00175-2 CrossRefGoogle Scholar
  31. Little TN (2007) Flyrock Risk. In: Proceedings of the EXPLO 2007 Conference Wollongong, Australia. pp. 35–43Google Scholar
  32. Lundborg N, Persson PA, Ladegaard-Pedersen A, Holmberg R (1975) Keeping the lid on flyrock in opencast blasting. Eng Min J 95–100Google Scholar
  33. Makridakis S, Hibon M (1995) Evaluating accuracy (or error) measures. INSEAD Working Paper Series. No. 18/TM:1–31.
  34. McLachlan GJ (2004) Discriminant analysis and statistical pattern recognition. John Wiley & Sons, New JerseyGoogle Scholar
  35. McNeill FM, Thro E (1994) Fuzzy logic: a practical approach. AP Professional, CambridgeGoogle Scholar
  36. Mishra AK, Mallick DK (2012) Analysis of blasting related accidents with emphasis on flyrock and its mitigation in surface mines. In: Proceedings of the 10th International Symposium on Rock Fragmentation by Blasting New Delhi, India. pp. 555–563Google Scholar
  37. Monjezi M, Bahrami A, Yazdian Varjani A (2010) Simultaneous prediction of fragmentation and flyrock in blasting operation using artificial neural networks. Int J Rock Mech Min Sci 47:476–480. doi: 10.1016/j.ijrmms.2009.09.008 CrossRefGoogle Scholar
  38. Monjezi M, Mehrdanesh A, Malek A, Khandelwal M (2012) Evaluation of effect of blast design parameters on flyrock using artificial neural networks. Neural Comput & Applic 23:349–356. doi: 10.1007/s00521-012-0917-2 CrossRefGoogle Scholar
  39. Olofsson SO (1990) Applied explosives technology for construction and mining. Applex, SwedenGoogle Scholar
  40. Ouchterlony F (2003) Influence of blasting on the size distribution and properties of muckpile fragments, a state-of-the-art review, MinFo project report P2000–10: energy optimisation in comminution. Lulea University of Technology, Sweden, SwebrecGoogle Scholar
  41. Persson PA, Holmberg R, Lee J (1994) Rock blasting and explosives engineering. CRC Press, Boca RatonGoogle Scholar
  42. Raina AK, Chakraborty AK, Choudhury PB, Sinha A (2011) Flyrock danger zone demarcation in opencast mines: a risk based approach. Bull Eng Geol Environ 70:163–172. doi: 10.1007/s10064-010-0298-7 CrossRefGoogle Scholar
  43. Raina AK, Murthy VMSR, Soni AK (2014) Flyrock in bench blasting: a comprehensive review. Bull Eng Geol Environ 73:1199–1209. doi: 10.1007/s10064-014-0588-6 CrossRefGoogle Scholar
  44. Raina AK, Murthy VMSR, Soni AK (2015) Flyrock in surface mine blasting: understanding the basics to develop a predictive regime. Curr Sci 108:660–665Google Scholar
  45. Rezaei M, Monjezi M, Yazdian Varjani A (2011) Development of a fuzzy model to predict flyrock in surface mining. Saf Sci 49:298–305. doi: 10.1016/j.ssci.2010.09.004 CrossRefGoogle Scholar
  46. Richards AB, More AJ (2004) Flyrock Control – By Chance or Design. In: Proceedings of the 30th Annual Conference on Explosives and Blasting Technique New Orleans, Louisiana. pp.1–13Google Scholar
  47. Roth J (1979) A model for the determination of flyrock range as a function of shot conditions, final report contract no. J03872A2. Management Science Associates, Los AltosGoogle Scholar
  48. Saadat M, Khandelwal M, Monjezi M (2014) An ANN-based approach to predict blast-induced ground vibration of Gol-E-Gohar iron ore mine, Iran. J Rock Mech Geotech Eng 6:67–76. doi: 10.1016/j.jrmge.2013.11.001 CrossRefGoogle Scholar
  49. Schneider L (1997) Back to the basics, flyrock (part 2: prevention). The Journal of explosives engineering 14:1−14 quarry blasting. Appl Acoust 71:1169–1176. doi: 10.1016/j.apacoust.2010.07.008 Google Scholar
  50. Segarra P, Domingo JF, López LM, Sanchidrián JA, Ortega MF (2010) Prediction of near field overpressure from quarry blasting. Appl Acoust 71:1169–1176. doi: 10.1016/j.apacoust.2010.07.008 CrossRefGoogle Scholar
  51. Singh TN, Dontha LK, Bhardwaj V (2008) Study into blast vibration and frequency using ANFIS and MVRA. Min Technol 117:116–121. doi: 10.1179/037178409X405741 CrossRefGoogle Scholar
  52. Tabachnick BG, Fidell LS (2013) Using multivariate statistics, Sixth edn. Pearson, New JerseyGoogle Scholar
  53. Tugrul A, Undul O (2006) Engineering geological characteristics of Istanbul greywackes. In: Proceedings of the 10th International Association for Engineering Geology and the Environment (IAEG) Congress Nottingham, United Kingdom. Paper no. 395Google Scholar
  54. US Code of Federal Regulations-Title 30 Mineral Resources (2016) Office of the Federal register national archives and records administration. U.S. Government Publishing Office, Washington, DCGoogle Scholar
  55. Yu TR, Vongpaisal S (1996) New blast damage criteria for underground blasting. CIM Bull 89:139–145Google Scholar
  56. Yugo N, Shin W (2015) Analysis of blasting damage in adjacent mining excavations. J Rock Mech Geotech Eng 7:282–290. doi: 10.1016/j.jrmge.2014.12.005 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Department of Mining EngineeringIstanbul Technical UniversityIstanbulTurkey

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