Influencia de Las Propiedades Del Macizo Rocoso en La Eficiencia de Voladura

Scientific Research and Essay Vol.4 (11), pp. 1213-1224, November, 2009 Available online at ISSN 1992-2248 © 2009 Academic Journals Full Length Research paper Influence of rock mass properties on blasting efficiency A. M. Kiliç 1 , E. Yaar 2* , Y. Erdoan 2 and P. G. Ranjith 3 1 Department of Mining Engineering, Cukurova University, 01330 Adana, Turkey. 2 Department of Petroleum and Natural Gas Engineering, Mustafa Kemal University, 3
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  Scientific Research and Essay Vol.4 (11), pp. 1213-1224, November, 2009 Available online at ISSN 1992-2248 © 2009 Academic Journals Full Length Research paper    Influence of rock mass properties on blasting efficiency A. M. Kiliç 1 , E. Ya  ar 2* , Y. Erdo  an 2 and P. G.   Ranjith 3   1 Department of Mining Engineering, Cukurova University, 01330 Adana, Turkey. 2 Department of Petroleum and Natural Gas Engineering, Mustafa Kemal University, 31200 Iskenderun-Hatay, Turkey. 3 Department of Civil Engineering, Monash University, Australia. Accepted 28 August, 2009 The purpose of this paper is to determine the influence of rock mass properties on the blasting efficiency which is ratio of the block size distribution of the rock mass to the block size distribution of the muck-pile. The proposed methodology of blasting efficiency in this study is to compare physical and mechanical properties of the rock mass and block fragmentation under the same blasting conditions in Kırka borax mine. Intact rock properties, block size of rock mass before blasting and muck pile after blasting were found to measure blasting efficiency. Firstly, intact rock properties, which are unit volume weight, water absorption, uniaxial compressive strength, tensile (Brazilian) strength, cohesion and internal friction angle, were tested for each mining bench. Secondly, block sizes of rock masses in respect to discontinuity boundaries were measured and muck pile photos were taken in order to determine Block Fragmentation (BF) which is to separate the rock mass block size by blasting and that of the corresponding muck pile. Thirdly, statistical analysis between rock mass properties and block fragmentation were developed and these analysis test results have shown that a good relation between block fragmentation and Brazilian tensile strength and internal friction angle were found. As a result, block fragmentation in the same blasting conditions and other rock properties can be estimated from the best empirical correlations with the rock properties. Key words:  Intact rock properties, blasting, block fragmentation, statistical analysis, image analysis.  INTRODUCTION A particular rock fragmentation size by blasting methods is very important to excavate in mining and civil engineering applications. The fragment size is mainly governed by the physico-mechanical properties and structure of the rock masses. Block Fragmentation (BF) is to separate the rock mass block size by blasting and that of the corresponding muck pile. Therefore, the blasting efficiency is important for the excavation of rock mass and is evaluated through comprising of the blocky size distributions of the rock mass and the corresponding muck pile. Rock blasting is controlled by using of explosive and rock characterization to excavate or rem-ove rock. A number of researchers have long been stud-ied about the influence of rock mass properties on blasting blasting operations. Bond (1952) proposed (equation 1) *Corresponding author. E -mail: Fax:+90 326 6135613.  for combination which was based on feed size, product size and a rock property factor. ))1()1((10 8080  F PW W  i  −=  (1) where W = energy required for fragmentation (kWh/ton);   Wi = Bond’s work index which depends upon the physico- mechanical properties of rock; P 80 = 80% passing size of product (µm) and F80   = 80% passing size of feed (µm). Bond's theory is a compromise between Rittinger's and Kick's theories and is generally recognised to be the best model to describe blasting operations (Da Gama, 1983).  McKenzie (1966) found, in the studies at Quebec Cartier Mines, that the efficiency of all the subsystems is depen- dent on the fragmentation. Kuznetsov (1973) developed a relation between the mean fragment size (K 50 , m) and the  explosive quantity used per unit volume as a function of rock type categorised as medium hard rocks, hard and fissured rocks and weak rocks (equation 2).  1214 Sci. Res. Essays 618.050  )( T T  QQV  AK   =  (2) where A = rock factor = 7, for medium hard rocks = 10, for hard and highly fissured rock = 13, for hard and weakly fissured rocks; V = rock volume broken per blast hole (m 3 ); Q T  = mass of TNT containing the energy equivalent of the explosive charge in each blast hole (kg). Cunningham   (1983) developed a model (Kuz-Ram) for prediction of the uniformity in the fragmentation based on Kuznetsov model and Rosin-Rammler formula on distribution pattern of fragmentation (equation 3). It was experienced by many that the rock mass categories defined by Kuznetsov (1973) are very wide and need more precision. Cunningham (1983) used Blastability Index proposed by Lilly   (1986) to fulfil this gap. ) / (1.0)1.0) / )((()( / 1()2 / ) / 1)(( / 14.2.2(  5.0  Hb Lch Lchlclbabs Bd W md d  Bd n  +−−−=  (3) where n = index of uniformity; B d = burden in drilling (m), d = blast hole diameter (mm), m d = spacing to burden ratio while drilling; W = standard deviation of accuracy in burden while drilling (m); abs = the absolute value; l b = base charge length (m); l c = column charge length (m); L ch = total charge length (m); H b = bench height (m). Da Gamma (1983) encouraged for blast prediction to engineers understanding the role of in-situ rock mass geometry in terms of block sizes in mine production. Estimating equations of the undersize fragment percentage were developed by Da Gamma and Jimeno (1993). These equations (equations 4 and 5) are in below. cb  Bd Sd W Pf   ) / ( =  (4) d cb F  X  Bd Sd aW Pf   ) / 1() / ( 50 = (modified equation) (5)  where P f = percent cumulative undersize of a particular fraction size (%); W = 10Wi/P 80 ; S d = drilled spacing (m); B d = drilled burden (m); a, b, c and d = site specific empirical constants and F 50 = average joint spacing or inherent block size (m). Jurgensen and Chung (1987) and Singh (1991) also opined that the blast results were influenced directly by the overall formational strength of rock. Chakraborty et al. (2002) found the joint orientations can considerably influence the average fragment size and shape. Hagan (1995) concluded that the results of rock blasting were affected more by rock properties than by any other variables. He also opined that as the mean spacing between the joints, fissures or the cracks decreases, the importance of rock material strength decreases while that of the rock mass strength increases. He added that in a rock mass with widely spaced joints, the blasts were required to create many new cracks. In a closely fissured rock mass, on the other hand, generation of new cracks is not needed and the fragmentation is achieved by the explosion gas pressure which opens the joints to trans-form a large rock mass into several loose blocks. He also commented that the blasting efficiency was affected to a lesser degree by the internal friction, grain size and porosity compared to rock strength. Pal Roy and Dhar (1996) proposed a fragmentation prediction scale based on the joint orientation with respect to bench face. Scott (1996) reported that the blast-controlling rock mass properties include the strength parameters, the mechani-cal properties like modulus of elasticity, Poison’s ratio, shock wave transmission capability, the size and the shape of the natural block and the required fragment size reduction by blasting. Thornton et al. (2002) categorised the parameters influencing fragmentation in three groups like; (i) rock mass properties, (ii) blast geometry and (iii) explosive properties. Hall and Brunton (2002) claimed that the JKMRC models provided better prediction than Kuz-Ram model due to improved estimation of the fines to intermediate size (< 100 mm) of the fragmentation distribution. The models calculate the coarse and fines distribution independently based on experimental obser-vations made the developers and a semi-mechanistic approach. Hudson (1992) developed a rock engineering systems methodology for providing both a useful checklist for the influential factors of rock engineering projects. Rock mass properties are among the most important contributory factors in fragmentation. Aler et al. (1996)   studied evaluation of blast fragmen-tation efficiency and its prediction by multivariate analysis procedures. Their proposed methodology of evaluating the blasting efficiency was essentially based on the comparison of the block size distribution in the rock mass and that of the corresponding muck pile after blasting.The evaluation of blasting efficiencies is ultimately done by calculating two ratios: Fragmentation Index and Frag-mentation Quality Factor. Latham and Lu (1999) outlined an energy-block-transition model for characterising the blast process. A blastability designation model was designed which reflected the intrinsic resistance of the rock mass are relatively constant to blasting. Hamdi and Mouza (2005) studied a methodology for rock mass characterisation and classification to improve blast results. They aimed the characterisation of the two rock mass components which are discontinuity network and rock matrix. The discontinuity network was described using the 3D stochastic simulations of discontinuity networks using the SIMBLOC program methodology. The rock matrix microstructure was characterised by the means of the experimental determination of severa l mechanical and physical parameters. Wang et al. (2008) studied the numerical analysis of blast-induced stress wave propa-gation and related spalling damage in a rock plate or wall. Gheibie et al. (2009) developed a new Modified Kuz-Ram fragmentation model which a prefactor of 0.073 is included in the formula for prediction of X50 and its use at the Sungun Copper Mine. In the model, a Blastability Index  Kilic et al. 1215 Ankara Kırka Kırka 05101520 km N   Figure 1.  The location map of Kırka borax open-pit mine. (BI) was used to correct the calculation of the Uniformity Index of Cunningham. The new model has a two parameter fragmentation size distribution that can be easily determined in the field. Zhu (2009) simulated the process of rock fracture and fragmentation in crater blasting and bench blasting and found a better understanding of the dominant parameters that control the results of crater blasting and bench blasting. It was noted findings reported by different researchers such as Belland (1966), Just (1973), Singh and Sarma (1983), Karpuz et al. (1990), Wang et al. (1992), Lizotte and Scoble (1994), Jimeno et al. (1995), Hustrulid (1999), Esen et al.   (2003) and Bond and Whittney (1959). It is evident from the above literature that greater the explosive energy utilised in blasting finer will be the product. But the product size depends not only on the explosive energy input but also the initial size of the rock to be fragmented. In widely jointed rocks, the average block size is more and hence, more explosive energy must be utilised to obtain the desired product size. In this study, the mine of Kırka Borax which is the North-West of Turkey and is 246 km far away from Ankara was investigated (Figure 1). The tincal (Na 2 B 4 O 7 , 10H 2 O) mineral of borax ore deposits is produced in the altitude 1150 m. The current depth, width and length of the open pit mine are 110, 800 m and 2 km respectively. The thickness of ore deposits varies from 2 m in North to 150 m in South of the area (Etibank, 1970). Ore production has been made as benches. The height of an each bench of 6 m was divided into 4 sections. 3 blasting in an each section and totally 48 blasting in 4 benches were applied. Blast holes length of 6.5 m and diameter of 0.16 m are charged with gelatine dynamite and ANFO. The main purpose of the investigation is to determine the influence of rock mass properties on blasting in Kırka Borax mine. Firstly, geology of the study area, physical and mechanical properties of rocks were determined. Secondly, same blasting conditions were chosen to determine the affecting of rock properties. Many factors affect the blastability of rock masses and it is therefore considered to be a composite intrinsic property of the rock mass. Blasting conditions in a variety of rock mass properties were assessed because rock masses have inherently different resistance to fragmentation by blasting. Thirdly, statistical analyses between rock mass properties and blasting fragmentation were developed and  1216 Sci. Res. Essays Figure 2. The geological map of the Kırka borax open-pit mine around, Yalçın (988).   a number of equations were obtained from the analysis. Geology of the study area The geologic formations, Neogene sedimentary units, volcanic rocks and alluviums around the Sakarya River were outcropped in Kırka borax open pit mine (Figure 2). Five different stratigraphic units which are breccia rhyolite, rhyolotic tuff, massive layered limestone, dolomitic marl, clay and borax sequence, olivined basalt, non-consolidate tuff and alluviums were determined as can be seen in Figure 3 (Yalçın, 1988). The borax ore deposits were observed in the Sarıkaya formation that contains different lithological units. Borax layer, mainly tincal mineral (Na 2 B 4 O 7 , 10H 2 O), is framed downwards and upwards by a series of marl and clay followed of limestone dating from Upper Miocene. The from lower to upper of Sarıkaya formation have the series of lower limestone, marl and clay, tincal minerals, marl and clay and series of upper limestone respectively. The borax ore deposits are represented in three different forms: breccia, layered and massive ores. Breccia ore deposits have 2 - 3 mm thickness of angulated mineral granules that were surrounded by clay matrix. Layered ore shows thin layer ore alternate with clay beds. A massive ore deposit presents as a vitreous aspect and has not shown sedimentary structure. The content of the layer of borax ore deposits is on average 25.3%. The average density of the ore is 1.92 t/m 3  and its hardness is 1.9. The proven and probable reserves of ore deposits are 62.341 and 437.747 million tonnes respectively. Structural geology of study area consists of Neogene sediments, which is over the schist and limestone, which is lower level of ore deposits approaches to exploitation as a fold. The ore deposit is cut by normal type faults whose principal directions are N-S ad NE-SW (Baysal, 1972). Physical and mechanical properties of rocks In mining area, discontinuity direction and dips of forma-tions before the blasting were measured in each mining bench. The proposed methodology of fragmentations efficiency is to compare block size in terms of rock properties in the same blasting method (Figure 4). The methodology occur three different stages. First stage is that rock mass characterization such as dip and direction, space, filling material of discontinuities were measured and classified according to visual inspection and measuring results of geologic compass. The number of  joint sets, orientation, dimension and intensity, distribu-tion of discontinuities and intact rock properties such as unit volume weight, porosity, water absorption, uniaxial compressive (UCS), tensile ( σ t ) and cohesion (c) strengths and internal friction angle ( φ ) were determined in the four sections of an each bench (Table 1).
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