Refine your search
Collections
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Mokhtarian, M.
- Geological Modeling and Short-Term Production Planning of Dimension Stone Quarries Based on Market Demand
Abstract Views :697 |
PDF Views:0
Authors
Affiliations
1 University of Urmia, Urmia, IR
2 Department of Mining and Metallurgical Engineering, Urmia University of Technology, Urmia, IR
1 University of Urmia, Urmia, IR
2 Department of Mining and Metallurgical Engineering, Urmia University of Technology, Urmia, IR
Source
Journal of Geological Society of India (Online archive from Vol 1 to Vol 78), Vol 80, No 3 (2012), Pagination: 420-428Abstract
In order to obtain minimum amount of ore wastage and maximum profitability in dimension stone quarries an optimal short-term production planning procedure has been established here according to the market demand. As the base of this procedure geological modelling has been first created and smoothing of ore-body boundaries was done. Then, an economical block model has been provided. In the next step, all probable shapes of minable-blocks were specified and their priorities in assignment were done according to desired size of the blocks by market demand. Finally, searching from a base sub-block was started in order to find the optimal plan. The procedure has been used for a dimension marble quarry located in northwest of Iran. It demonstrates a decrease about 26% of ore wastage and 21.3% of diamond wire assumption with comparing to the existent traditional procedure.Keywords
Dimension Stone Quarry, Geological Modelling, Short-Term, Production Planning, Market Demand, Iran.References
- ABDOLLAHISHARIF, J. and BAKHTAVAR, E. (2009) An intelligent algorithm of minimum cutting plane to find optimal size of extractable-blocks in dimension stone quarries. Archives of Mining Sciences, v.54(4), pp.641-656.
- BASTANTE, F.G., TABOADA, J. and ORDONEZ, C. (2004) Design and planning for slate mining using optimisation algorithms. Engg. Geol., v.73, pp.93-103.
- CARANASSIOS, A., TOMI, G.D. and SENHORINHO, N. (2000) Geological modeling and mine planning for dimension stone quarries. In: Panagiotou and Michalakopoulos (Eds.), Proc. Mine Planning and Equipment Selection, Balkema, Rotterdam, pp.39-45.
- CACCETTA, L. (2007) Application of Optimisation Techniques in Open Pit Mining. Handbook of Operations Research in Natural Resources. Springer-US, v.99, pp.547-559.
- KOPPE, J.C., ZINGANO, A.C. and COSTA, J.F.C.L. (1995) Three dimensional modeling in planning ornamental stone quarries. In: Singhal et al. (Eds.), Proc. Mine Planning and Equipment Selection, Balkema, Rotterdam, pp.117-120.
- LATHAM, J.P., MEULEN, J.V. and DUPRAY, S. (2006) Prediction of in-situ block size distributions with reference to armourstone for breakwaters. Engg. Geol., v.86, pp.18-36.
- LUODES, H., SELONEN, O. and PAAKKONEN, K. (2000) Evaluation of dimension stone in gneissic rocks a case history from southern Finland. Engg. Geol., v.52, pp.209-223.
- MUTLUTÜRK, M. (2007) Determining the amount of marketable blocks of dimensional stone before actual extraction. Jour. Mining Sci., v.43(1), pp.67-72.
- RATHORE, S.S. and BHANDARI, S. (2006) Study of controlled blasting techniques in dimensional stone quarrying. Jour. Instt. Engineers, Mining Engineering Division, v.86, pp.46-49.
- SIRAKOV, N.M. and MUGE, F.H. (2001) A system for reconstructing and visualising three-dimensional objects. Computers and Geosciences, v.27, pp.59-69.
- TABOADA, J., VAAMONDE, A. and SAAVEDRA, A. (1999) Evaluation of the quality of a granite quarry. Engg. Geol., v.53, pp.1-11.
- XU, H. and WU, Q. (2001) A framework modeling of geological related spatial data in 3D scene. Proc. 6th Internat. Symp. on Future Software Technology, Zhengzhou, China, pp. 252-257.
- Artificial Neural Network or Empirical Criteria? A Comparative Approach in Evaluating Maximum Charge per Delay in Surface Mining - Sungun Copper Mine
Abstract Views :191 |
PDF Views:0
Authors
Affiliations
1 Department of Mining Engineering, Urmia University of Technology, West Azerbaijan, IR
2 Department of Mining Engineering, University of Urmia, West Azerbaijan, IR
1 Department of Mining Engineering, Urmia University of Technology, West Azerbaijan, IR
2 Department of Mining Engineering, University of Urmia, West Azerbaijan, IR
Source
Journal of Geological Society of India (Online archive from Vol 1 to Vol 78), Vol 79, No 6 (2012), Pagination: 652-658Abstract
Ground vibration due to blasting causes damages in the existence of the surface structures nearby the mine. The study of vibration control plays an important role in minimizing environmental effects of blasting in mines. Ground vibration regulations primarily rely on the peak particle velocity (PPV, mm/s). Prediction of maximum charge weight per delay (Q, kg) by distance from blasting face up to vibration monitoring point as well as allowable PPV was proposed in order to perform under control blasting and therefore avoiding damages on structures nearby the mine. Various empirical predictor equations have proposed to determine the PPV and maximum charge per delay. Maximum charge per delay is calculated by using PPV predictors indirectly or Q predictor directly. This paper presents the results of ground vibration measurement induced by bench blasting in Sungun copper mine in Iran. The scope of this study is to evaluate the capability of two different methods in order to predict maximum charge per delay. A comparison between two ways of investigations including empirical equations and artificial neural network (ANN) are presented. It has been shown that the applicability of ANN method is more promising than any under study empirical equations.Keywords
Blasting, Maximum Charge Per Delay, PPV, Empirical Criteria and ANN.References
- ALIPOUR, A. (2007) Study of geomechanical parameters on tunnel blasting results using ANNs. MSc thesis. University of Tehran. Iran.
- AMBRASEYS, N.R. and HENDRON, A.J. (1968) Dynamic behavior of rock masses in rock mechanics in engineering Practice. John Wiley and Sons, London, pp.203-207.
- AZIMI, Y. (2006) Investigation of seismic wave due to blasting, in Sungun copper mine. MSc thesis, Amir Kabir University of Technology. Tehran.Iran.
- DEHGHANI, H. and ATAEE-POUR, M. (2011) Development of a model to predict peak particle velocity in a blasting operation, Internat. Jour. Rock Mechanics and Mining Sci., v.48(1), pp.51-58.
- DOWDING, C.H. (1996) Construction vibration. Prentice Hall Inc. Englewood Cliffs. NJ. USA, 604 p.
- DUVALL, W.I. and FOGELSON, D.E. (1962) Review criteria for estimating damage to residences from blasting vibration. USBM-I, 5968p.
- HEBB, D.O. (1949) The organization of behavior: A neuropsychological theory. Wiley. New York.
- HOSSAINI, S.M.F. and Sen, G.C. (2004) Effect of explosive type on particle velocity criteria in ground vibration. Jour Explosive Engg., USA. v.21(4), pp.34-39.
- HOSSAINI, S.M.F. and Sen, G.C. (2006) A study of the influence of different blasting modes and explosive types on ground vibrations. Iranian Jour. Sci. Tech., Shiraz, No.29 B3, pp.313-325.
- HOSSAINI, S. M. F. ALIPOUR, A. and Jafari, A. (2008) Neural network or empirical criteria? A comparative approach in evaluating ground vibration in Karoune - 3 underground cavernSW Iran. 8th Australasian Coal Operator’s Conference, Wollongong, NSW. Australia
- IPHAR, M., YAVUZ, M. and A K, H. (2007) Prediction of ground vibrations resulting from the blasting operations in an openpit mine by adaptive neuro-fuzzy inference system. Environ. Geol., v.l 56,(1), DOI: 10.1007/s00254-007-1143-6.
- JIMENO, C. L. and JIMENO, E. L. (1995) Drilling and blasting of rocks. A A Balkema, Roterdam, 391p.
- KAHRIMAN, A. OZER, U. AKSOY, M. KARADOGAN, A. and TUNCER, G. (2006) Environmental impacts of bench blasting at Hisarcik Boron open pit mine in Turkey. Environ. Geol., v.50(7), pp.1015-1023.
- KAHRIMAN, A. (2002) Analysis of ground vibrations caused by bench blasting at open-pit lignite mine in Turkey. Environ. Geol., v.41(6), pp.653-6__.
- KAVOSHGARAN CONSULTING ENGINEERS (2003) Slope stability in Sungun mine (Phase I Report). Second Edition.
- KHANDELWAL, M. and SINGH, T.N. (2007) Evaluation of blast induced ground vibration predictors. Soil Dynamics Earthquake Engg., pp.116-125.
- KHANDELWAL, M. and SINGH, T.N. (2009) Prediction of blastinduced ground vibration using artificial neural network, Internat. Jour. Rock Mech. Min. Sci., v.46, pp.1214-1222.
- KUZU, C. and ERGIN, H. (2005) An assessment of environmental impacts of quarry-blasting operation: a case study in Istanbul, Turkey. Environ. Geol., v.48(2), pp.211-217.
- LU, Y. (2005) Underground blast induced ground shock and its modeling using artificial neural network. Computers and Geotechnics, v.32(4), pp.164–170.
- MATLAB, (1999) The language of technical computing. The Matworks, New York.
- MCCULLOCH, W. S. and PITTS, W. (1943) A Logical calculus in the ideas immanent in nervous activity. Bull. Mathematical Biophysics, v.5, pp.115-133.
- MOHAMED, M.T. (2009) Artificial neural network for prediction and control of blasting vibrations in Assiut (Egypt) limestone quarry. Internat. Jour. Rock Mech. Min. Sci., pp.426-431
- OZER, U. KAHRIMAN, A. AKSOY, M. ADIGUZEL, D. and Karadogan, A. (2008) The analysis of ground vibrations induced by bench blasting at Akyol quarry and practical blasting charts. Environ. Geol., v.54(4), pp.737-743, DOI: 10.1007/s00254-007-0859-7
- RAI, R. SHRIVASTVA, B.K. and SINGH, T. N. (2005) Prediction of maximum safe charge per delay in surface mining. Mining Technology (Trans. Inst. Min. Metall. - A), v.114, A, pp.227-231.
- ROSENBLATT, F. (1958) The perceptron: A probabilistic model for information storage and organization in the brain, Psychological Rev., v.68(6), pp.386-408.
- SINGH, P.K. ROY, M.P. and SINGH, R.K. (2005) Responses of roof and pillars of underground coal mines to vibration induced by adjacent open-pit blasting. Environ. Geol., v.47(2), pp.205-214, DOI: 10.1007/s00254-004-1144-7.
- SINGH, T. N. (2004) Artificial neural network approach for prediction and control of ground vibrations in mines. Mining Technology ((Trans. Inst. Min. Metall. - A), v.113(4), pp.251-256.
- STEFEN, M. (1997) Well log correlation using a back propagation neural network. Mathematical Geol., v.29(3), pp.413-425.
- TARASSENKO, L. (1998) A guide to neural computing application, Arnold, London.