Abstract
Flyrock is considered as one of the main causes of human injury, fatalities, and structural damage among all undesirable environmental impacts of blasting. Therefore, it seems that the proper prediction/simulation of flyrock is essential, especially in order to determine blast safety area. If proper control measures are taken, then the flyrock distance can be controlled, and, in return, the risk of damage can be reduced or eliminated. The first objective of this study was to develop a predictive model for flyrock estimation based on multiple regression (MR) analyses, and after that, using the developed MR model, flyrock phenomenon was simulated by the Monte Carlo (MC) approach. In order to achieve objectives of this study, 62 blasting operations were investigated in Ulu Tiram quarry, Malaysia, and some controllable and uncontrollable factors were carefully recorded/calculated. The obtained results of MC modeling indicated that this approach is capable of simulating flyrock ranges with a good level of accuracy. The mean of simulated flyrock by MC was obtained as 236.3 m, while this value was achieved as 238.6 m for the measured one. Furthermore, a sensitivity analysis was also conducted to investigate the effects of model inputs on the output of the system. The analysis demonstrated that powder factor is the most influential parameter on fly rock among all model inputs. It is noticeable that the proposed MR and MC models should be utilized only in the studied area and the direct use of them in the other conditions is not recommended.
Similar content being viewed by others
References
Adhikari GR (1999) Studies on flyrock at limestone quarries. Rock Mech Rock Eng 32:291–301
Aghajani-Bazzazi A, Osanloo M, Azimi Y (2009) Flyrock prediction by multiple regression analysis in Esfordi phosphate mine of Iran. In: Proceedings of the 9th international symposium on rock fragmentation by blasting. Granada, Spain, pp 649–657
Amini H, Gholami R, Monjezi M, Torabi SR, Zadhesh J (2011) Evaluation of flyrock phenomenon due to blasting operation by support vector machine. Neural Comput Appl. doi:10.1007/s00521-011-0631-5
Bajpayee TS, Rehak TR, Mowrey GL, Ingram DK (2002) A summary of fatal accidents due to flyrock and lack of blast area security in surface mining, 1989–1999. In: Proceedings of the 28th annual conference on explosives and blasting technique. Las Vegas, pp 105–118
Bajpayee TS, Rehak TR, Mowrey GL, Ingram DK (2004) Blasting injuries in surface mining with emphasis on flyrock and blast area security. J Safety Res 35:47–57
Berta G (1990) Explosives: an engineering tool. Italesplosivi, Millano
Bhandari S (1997) Engineering rock blasting operations. Taylor & Francis, Boca Raton
Bianchini F, Hewage K (2012) Probabilistic social cost-benefit analysis for green roofs: a lifecycle approach. Build Environ 58:152–162. doi:10.1016/j.buildenv.2012.07.005
Dunn WL, Shultis JK (2009) Monte Carlo methods for design and analysis of radiation detectors. Radiat Phys Chem 78:852–858. doi:10.1016/j.radphyschem.2009.04.030
Ebrahimi E, Monjezi M, Khalesi MR, Jahed Armaghani D (2015) Prediction and optimization of back-break and rock fragmentation using an artificial neural network and a bee colony algorithm. Bull Eng Geol Environ. doi:10.1007/s10064-015-0720-2
Esmaeili M, Osanloo M, Rashidinejad F, Aghajani Bazzazi A, Taji M (2014) Multiple regression, ANN and ANFIS models for prediction of backbreak in the open pit blasting. Eng Comput 30:549–558
Faradonbeh RS, Monjezi M, Jahed Armaghani D (2015) Genetic programing and non-linear multiple regression techniques to predict backbreak in blasting operation. Eng Comput. doi:10.1007/s00366-015-0404-3
Fletcher LR, D’Andrea DV (1987) Reducing accident through improved blasting safety. USBM IC, 9135. In: Proceedings of bureau of mines technology transfer SEM, Chicago, pp 6–18
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
Hajihassani M, Jahed Armaghani D, Sohaei H, Tonnizam Mohamad E, Marto A (2014) Prediction of airblast-overpressure induced by blasting using a hybrid artificial neural network and particle swarm optimization. Appl Acoust 80:57–67
Hasanipanah M, Monjezi M, Shahnazar A, Jahed Armaghanid D, Farazmand A (2015a) Feasibility of indirect determination of blast induced ground vibration based on support vector machine. Measurement 75:289–297
Hasanipanah M, Jahed Armaghani D, Khamesi H, Bakhshandeh Amnieh H, Ghoraba S (2015b) Several non-linear models in estimating air-overpressure resulting from mine blasting. Eng Comput. doi:10.1007/s00366-015-0425-y
Hemphill GB (1981) Blasting operations. McGraw-Hill, New York
Institute of Makers of Explosives (IME) (1997) Glossary of commercial explosive industry terms. Safety Publication, Washington DC: Institute of Makers of Explosives. No 12
ISRM (2007) In: Ulusay and Hudson (eds) The complete ISRM suggested methods for rock characterization, testing and monitoring: 1974–2006. Suggested methods prepared by the commission on testing methods, International Society for Rock Mechanics
Jahed Armaghani D, Hajihassani M, Mohamad ET, Marto A, Noorani SA (2014) Blasting-induced flyrock and ground vibration prediction through an expert artificial neural network based on particle swarm optimization. Arabian J Geosci 7:5383–5396
Jahed Armaghani D, Hasanipanah M, Tonnizam Mohamad E (2015a) A combination of the ICA-ANN model to predict air-overpressure resulting from blasting. Eng Comput. doi:10.1007/s00366-015-0408-z
Jahed Armaghani D, Hajihassani M, Monjezi M, Mohamad ET, Marto A, Moghaddam MR (2015b) Application of two intelligent systems in predicting environmental impacts of quarry blasting. Arabian J Geosci. doi:10.1007/s12517-015-1908-2
Jahed Armaghani D, Mohamad ET, Hajihassani M, Abad SANK, Marto A, Moghaddam MR (2015c) Evaluation and prediction of flyrock resulting from blasting operations using empirical and computational methods. Eng Comput. doi:10.1007/s00366-015-0402-5
Jimeno CL, Jimeno EL, Carcedo FJA (1995) Drilling and blasting of rocks. Balkema, Rotterdam
Kecojevic V, Radomsky M (2005) Flyrock phenomena and area security in blasting-related accidents. Safety Sci 43:739–750
Khandelwal M, Monjezi M (2013a) Prediction of backbreak in open-pit blasting operations using the machine learning method. Rock Mech Rock Eng 46(2):389–396
Khandelwal M, Monjezi M (2013b) Prediction of flyrock in open pit blasting operation using machine learning method. Int J Rock Mech Min Sci Technol 23:313–316
Khandelwal M, Singh TN (2007) Evaluation of blast-induced ground vibration predictors. Soil Dyn Earthq Eng 27:116–125
Ladegaard-Pedersen A, Holmberg R (1973) The dependence of charge geometry on flyrock caused by crater effects in bench blasting. Report DS1973, Swedish Detonic Res Found (SweDeFo), pp 1–38
Little TN, Blair DP (2010) Mechanistic Monte Carlo models for analysis of flyrock risk. Rock fragmentation by blasting. Taylor and Francis, London, pp 641–647
Liu MM (2014) Probabilistic prediction of green roof energy performance under parameter uncertainty. Energy 77:667–674
Lundborg N (1981) The probability of flyrock. Report DS1981, Swedish Detonic Res Found (SweDeFo)
Lundborg N, Persson N, Ladegaard-Pedersen A, Holmberg R (1975) Keeping the lid on flyrock in open pit blasting. Eng Min J 176:95–100
Mandal SK (1997) Causes of flyrock damages and its remedial measures. Course on: recent advances in blasting techniques in mining and construction projects, HRD-CMRI Dhanbad, pp 130–136
Marto A, Hajihassani M, Jahed Armaghani D, Tonnizam Mohamad E, Makhtar AM (2014) A novel approach for blast-induced flyrock prediction based on imperialist competitive algorithm and artificial neural network. Sci World J (Article ID 643715). http://dx.doi.org/10.1155/2014/643715
Monjezi M, Khoshalan HA, Varjani AY (2012) Prediction of flyrock and backbreak in open pit blasting operation: a neurogenetic approach. Arabian J Geosci 5:441–448
Monjezi M, Hasanipanah M, Khandelwal M (2013) Evaluation and prediction of blast-induced ground vibration at Shur River Dam, Iran, by artificial neural network. Neural Comput Appl 22:1637–1643
Morin AM, Ficarazzo F (2006) Monte Carlo simulation as a tool to predict blasting fragmentation based on the Kuz-Ram model. Comput Geosci 32:352–359
Raina AK, Murthy VMSR, Soni AK (2014) Flyrock in bench blasting: a comprehensive review. Bull Eng Geol Environ. doi:10.1007/s10064-014-0588-6
Rezaei M, Monjezi M, Yazdian Varjani A (2011) Development of a fuzzy model to predict flyrock in surface mining. Safety Sci 49:298–305
Richards AB, Moore AJ (2004) Flyrock control-by chance or design. In: Proceedings of 30th ISEE conference on explosives and blasting technique, New Orleans
Roth JA (1979) A model for the determination of flyrock range as a function of shot condition. US Department Commerce, NTIS Report no. PB81222358
Roy PP (2005) Rock blasting effects and operations. Taylor & Francis, Boca Raton
Sari M, Ghasemi E, Ataei M (2013) Stochastic modeling approach for the evaluation of backbreak due to blasting operations in open pit mines. Rock Mech Rock Eng. doi:10.1007/s00603-013-0438-z
Solver F (2010) Premium solver platform. User Guide, Frontline Systems, Inc
SPSS Inc (2007) SPSS for Windows (Version 16.0). Chicago: SPSS Inc
Trivedi R, Singh TN, Gupta N (2015) Prediction of blast-induced flyrock in opencast mines using ANN and ANFIS. Geotech Geolog Eng. doi:10.1007/s10706-015-9869-5
US EPA Technical Panel (1997) Guiding principles for Monte Carlo analysis. Us Epa 1–35
Verakis HC, Lobb TE (2003) An analysis of blasting accidents in mining operations. In: Proceedings of 29th annual conference explosives and blasting technique. Cleveland: International Society of Explosives Engineers, vol 2, pp 119–129
Acknowledgments
The authors would like to express their sincere appreciation to the anonymous reviewers for their valuable and constructive suggestions.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Armaghani, D.J., Mahdiyar, A., Hasanipanah, M. et al. Risk Assessment and Prediction of Flyrock Distance by Combined Multiple Regression Analysis and Monte Carlo Simulation of Quarry Blasting. Rock Mech Rock Eng 49, 3631–3641 (2016). https://doi.org/10.1007/s00603-016-1015-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00603-016-1015-z