influencia de las propiedades del macizo rocoso en la eficiencia de voladura

8/11/2019 Influencia de Las Propiedades Del Macizo Rocoso en La Eficiencia de Voladura

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Scientific Research and Essay Vol.4 (11), pp. 1213-1224, November, 2009Available online at http://www.academicjournals.org/SREISSN 1992-2248 2009 Academic Journals

Full Length Research paper

Influence of rock mass properties on blasting efficiencyA. M. Kili1 , E. Yaar2*, Y. Erdoan2 and P. G.Ranjith3

1Department of Mining Engineering, Cukurova University, 01330 Adana, Turkey.

2Department of Petroleum and Natural Gas Engineering, Mustafa Kemal University, 31200 Iskenderun-Hatay, Turkey.

3Department 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 blastingefficiency which is ratio of the block size distribution of the rock mass to the block size distribution ofthe 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 blastingconditions in Krka borax mine. Intact rock properties, block size of rock mass before blasting andmuck pile after blasting were found to measure blasting efficiency. Firstly, intact rock properties, whichare 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 rockmasses in respect to discontinuity boundaries were measured and muck pile photos were taken inorder to determine Block Fragmentation (BF) which is to separate the rock mass block size by blastingand that of the corresponding muck pile. Thirdly, statistical analysis between rock mass properties andblock fragmentation were developed and these analysis test results have shown that a good relationbetween block fragmentation and Brazilian tensile strength and internal friction angle were found. As aresult, block fragmentation in the same blasting conditions and other rock properties can be estimatedfrom 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 methodsis very important to excavate in mining and civilengineering applications. The fragment size is mainlygoverned by the physico-mechanical properties andstructure of the rock masses. Block Fragmentation (BF) isto separate the rock mass block size by blasting and thatof the corresponding muck pile. Therefore, the blastingefficiency is important for the excavation of rock massand is evaluated through comprising of the blocky size

distributions of the rock mass and the correspondingmuck pile. Rock blasting is controlled by using ofexplosive 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 blastingblasting operations. Bond (1952) proposed (equation 1)

*Corresponding author. E -mail: [email protected]. Fax:+90326 6135613.

for combination which was based on feed size, producsize and a rock property factor.

))1()1((108080

FPWW i = (1)

where W = energy required for fragmentation (kWh/ton);Wi= Bonds work index which depends upon the physico-

mechanical properties of rock; P80 = 80% passing size of

product (m) and F80= 80% passing size of feed (m).Bond's theory is a compromise between Rittinger's and

Kick's theories and is generally recognised to be the bestmodel to describe blasting operations (Da Gama, 1983)McKenzie (1966) found, in the studies at Quebec CartieMines, that the efficiency of all the subsystems is depen-dent on the fragmentation. Kuznetsov (1973) developed arelation between the mean fragment size (K50, m) and theexplosive quantity used per unit volume as a function ofrock type categorised as medium hard rocks, hard andfissured rocks and weak rocks (equation 2).


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1214 Sci. Res. Essays

618.0

50 )( T

T

QQ

VAK = (2)

where A = rock factor = 7, for medium hard rocks = 10,for hard and highly fissured rock = 13, for hard andweakly fissured rocks; V = rock volume broken per blast

hole (m3); QT = mass of TNT containing the energyequivalent 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 onKuznetsov model and Rosin-Rammler formula ondistribution pattern of fragmentation (equation 3). It wasexperienced by many that the rock mass categoriesdefined by Kuznetsov (1973) are very wide and needmore precision. Cunningham (1983) used BlastabilityIndex proposed by Lilly

(1986) to fulfil this gap.

)/(1.0)1.0)/)((()(/1()2/)/1)((/14.2.2( 5.0 HbLchLchlclbabsBdWmddBdn +=

(3)

where n = index of uniformity; Bd = burden in drilling (m),d = blast hole diameter (mm), md = spacing to burdenratio while drilling; W = standard deviation of accuracy inburden while drilling (m); abs = the absolute value; lb =base charge length (m); lc = column charge length (m);Lch = total charge length (m); Hb = bench height (m).

Da Gamma (1983) encouraged for blast prediction toengineers understanding the role of in-situ rock massgeometry in terms of block sizes in mine production.Estimating equations of the undersize fragmentpercentage were developed by Da Gamma and Jimeno(1993). These equations (equations 4 and 5) are in

below.

cbBdSdWPf )/(= (4)

dcbFXBdSdaWPf )/1()/( 50= (modified equation) (5)

where Pf = percent cumulative undersize of a particularfraction size (%); W = 10Wi/P80; Sd = drilled spacing (m);Bd = drilled burden (m); a, b, c and d = site specificempirical constants and F50 = average joint spacing orinherent block size (m).

Jurgensen and Chung (1987) and Singh (1991) also

opined that the blast results were influenced directly bythe overall formational strength of rock. Chakraborty et al.(2002) found the joint orientations can considerablyinfluence the average fragment size and shape. Hagan(1995) concluded that the results of rock blasting wereaffected more by rock properties than by any othervariables. He also opined that as the mean spacingbetween the joints, fissures or the cracks decreases, theimportance of rock material strength decreases while thatof the rock mass strength increases. He added that in arock mass with widely spaced joints, the blasts wererequired to create many new cracks. In a closely fissured

rock mass, on the other hand, generation of new cracksis not needed and the fragmentation is achieved by theexplosion gas pressure which opens the joints to trans-form a large rock mass into several loose blocks. He alsocommented that the blasting efficiency was affected to alesser degree by the internal friction, grain size and

porosity compared to rock strength. Pal Roy and Dha(1996) proposed a fragmentation prediction scale basedon the joint orientation with respect to bench face. Scot(1996) reported that the blast-controlling rock massproperties include the strength parameters, the mechanical properties like modulus of elasticity, Poisons ratioshock wave transmission capability, the size and theshape of the natural block and the required fragment sizereduction by blasting. Thornton et al. (2002) categorisedthe parameters influencing fragmentation in three groupslike; (i) rock mass properties, (ii) blast geometry and (iii)explosive properties. Hall and Brunton (2002) claimedthat the JKMRC models provided better prediction thanKuz-Ram model due to improved estimation of the finesto intermediate size (< 100 mm) of the fragmentationdistribution. The models calculate the coarse and finesdistribution independently based on experimental observations made the developers and a semi-mechanisticapproach. Hudson (1992) developed a rock engineeringsystems methodology for providing both a usefuchecklist for the influential factors of rock engineeringprojects. Rock mass properties are among the mosimportant contributory factors in fragmentation.

Aler et al. (1996)studied evaluation of blast fragmen

tation efficiency and its prediction by multivariate analysisprocedures. Their proposed methodology of evaluatingthe blasting efficiency was essentially based on the

comparison of the block size distribution in the rock massand that of the corresponding muck pile after blasting.Theevaluation of blasting efficiencies is ultimately done bycalculating two ratios: Fragmentation Index and Frag-mentation Quality Factor. Latham and Lu (1999) outlinedan energy-block-transition model for characterising theblast process. A blastability designation model wasdesigned which reflected the intrinsic resistance of therock mass are relatively constant to blasting. Hamdi andMouza (2005) studied a methodology for rock masscharacterisation and classification to improve blasresults. They aimed the characterisation of the two rockmass components which are discontinuity network and

rock matrix. The discontinuity network was describedusing the 3D stochastic simulations of discontinuitynetworks using the SIMBLOC program methodology. Therock matrix microstructure was characterised by the meansof the experimental determination of several mechanicaand physical parameters. Wang et al. (2008) studied thenumerical analysis of blast-induced stress wave propagation and related spalling damage in a rock plate or wallGheibie et al. (2009) developed a new Modified Kuz-Ramfragmentation model which a prefactor of 0.073 isincluded in the formula for prediction of X50 and its use athe Sungun Copper Mine. In the model, a Blastability Index


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Kilic et al. 1215

Ankara

Krka

Krka

0 5 10 15 20 km

N

Figure 1.The location map of Krka borax open-pit mine.

(BI) was used to correct the calculation of the UniformityIndex of Cunningham. The new model has a twoparameter fragmentation size distribution that can beeasily determined in the field. Zhu (2009) simulated theprocess of rock fracture and fragmentation in craterblasting and bench blasting and found a betterunderstanding of the dominant parameters that controlthe results of crater blasting and bench blasting. It wasnoted findings reported by different researchers such asBelland (1966), Just (1973), Singh and Sarma (1983),Karpuz et al. (1990), Wang et al. (1992), Lizotte andScoble (1994), Jimeno et al. (1995), Hustrulid (1999),

Esen et al.

(2003) and Bond and Whittney (1959). It isevident from the above literature that greater theexplosive energy utilised in blasting finer will be theproduct. But the product size depends not only on theexplosive energy input but also the initial size of the rockto be fragmented. In widely jointed rocks, the averageblock size is more and hence, more explosive energymust be utilised to obtain the desired product size.

In this study, the mine of Krka Borax which is theNorth-West of Turkey and is 246 km far away fromAnkara was investigated (Figure 1). The tincal (Na2B4O7,

10H2O) mineral of borax ore deposits is produced in thealtitude 1150 m. The current depth, width and length ofthe open pit mine are 110, 800 m and 2 km respectivelyThe thickness of ore deposits varies from 2 m in North to150 m in South of the area (Etibank, 1970). Oreproduction has been made as benches. The height of aneach bench of 6 m was divided into 4 sections. 3 blastingin an each section and totally 48 blasting in 4 bencheswere applied. Blast holes length of 6.5 m and diameter o0.16 m are charged with gelatine dynamite and ANFO.

The main purpose of the investigation is to determinethe influence of rock mass properties on blasting in Krka

Borax mine. Firstly, geology of the study area, physicaand mechanical properties of rocks were determinedSecondly, same blasting conditions were chosen todetermine the affecting of rock properties. Many factorsaffect the blastability of rock masses and it is thereforeconsidered to be a composite intrinsic property of therock mass. Blasting conditions in a variety of rock massproperties were assessed because rock masses haveinherently different resistance to fragmentation byblasting. Thirdly, statistical analyses between rock massproperties and blasting fragmentation were developed and


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Figure 2. The geological map of the Krka borax open-pit mine around, Yaln(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 Riverwere outcropped in Krka borax open pit mine (Figure 2).Five different stratigraphic units which are brecciarhyolite, rhyolotic tuff, massive layered limestone,dolomitic marl, clay and borax sequence, olivined basalt,non-consolidate tuff and alluviums were determined ascan be seen in Figure 3 (Yaln, 1988). The borax oredeposits were observed in the Sarkaya formation thatcontains different lithological units. Borax layer, mainlytincal mineral (Na2B4O7, 10H2O), is framed downwardsand upwards by a series of marl and clay followed oflimestone dating from Upper Miocene. The from lower to

upper of Sarkaya formation have the series of lowerlimestone, marl and clay, tincal minerals, marl and clayand series of upper limestone respectively.

The borax ore deposits are represented in threedifferent forms: breccia, layered and massive ores.Breccia ore deposits have 2 - 3 mm thickness ofangulated mineral granules that were surrounded by claymatrix. Layered ore shows thin layer ore alternate withclay beds. A massive ore deposit presents as a vitreousaspect and has not shown sedimentary structure. Thecontent of the layer of borax ore deposits is on average25.3%. The average density of the ore is 1.92 t/m

3and its

hardness is 1.9. The proven and probable reserves of oredeposits are 62.341 and 437.747 million tonnesrespectively.

Structural geology of study area consists of Neogene

sediments, which is over the schist and limestone, whichis lower level of ore deposits approaches to exploitationas a fold. The ore deposit is cut by normal type faultswhose principal directions are N-S ad NE-SW (Baysal1972).

Physical and mechanical properties of rocks

In mining area, discontinuity direction and dips of formations before the blasting were measured in each miningbench. The proposed methodology of fragmentationsefficiency is to compare block size in terms of rockproperties in the same blasting method (Figure 4). Themethodology occur three different stages. First stage isthat rock mass characterization such as dip and directionspace, filling material of discontinuities were measuredand classified according to visual inspection andmeasuring results of geologic compass. The number ojoint sets, orientation, dimension and intensity, distribution of discontinuities and intact rock properties such asunit volume weight, porosity, water absorption, uniaxia

compressive (UCS), tensile (t) and cohesion (c

strengths and internal friction angle () were determinedin the four sections of an each bench (Table 1).


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Kilic et al. 1217

Figure 3. The generalised stratigraphic section of the study area,(Yaln, 1988).

The dip, direction, length and space of discontinuitieswere measured and discontinuities were classified into assets (Bieniawski, 1974; Barton et al., 1974; Hudson,

1993) and were analysed by standard graphical repre-sentations. In order to analyse discontinuities inter-sections for block size distribution, discontinuities areassimilated to flat discs and the orientation of discs wassimulated in this model. These intersections give rise tothe formation of traces, vertices, edges and faces.Second stage is that image analysis techniques wereused to estimate the block size distribution. The photo-graphs of rock blocks were taken and blocks in eachphoto are manually digitised and each of them wasmeasured as maximum and minimum width (Figure 5).The analyses of fragmentation size after blasting were

evaluated and the results were given in Table 2According to percentages of block fragmentation, thebest efficiency of block fragmentation ratio in first bench

however, the worst efficiency of that in fourth bench wereobserved. The results have shown that big blocks givessmall rock fragmentation size better than small blockbefore the blasting. Third stage is that assessment oblock fragmentation and rock mass properties wereanalysed by the statistical methods.

STATSTCAL ANALYSS AND DSCUSSONS

The effects of rock physico-mechanical properties beforeblasting and block fragmentation after blasting on the


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Figure 4.Flow sheet of the proposed methodology of blast fragmentation.

Table 1.The physico-mechanical properties of rocks in benches before the blasting.

Unit volume

weight (,g/cm)

WaterAbsorption

(w, %)

Uniaxialcompressive

strength (, MPa)

Tensilestrength

(t, MPa)

Cohesion(c, MPa)

Int. friction

angle (, )

I.Bench

A 1.99 10.0 19.7 4.45 4.7 34.7

B 1.99 10.4 19.9 4.39 4.69 36.9

C 2.05 12.3 21.3 4.46 4.94 37.0

D 1.97 8.5 19.0 4.43 4.57 37.9

II.

Bench

A 2.02 10.8 20.3 5.29 4.78 39.0

B 2.01 11.2 20.5 5.16 4.85 38.6

C 2.07 13.1 22.0 5.18 5.11 38.8

D 1.99 9.0 19.6 5.29 4.72 39.7

III.Bench

A 2.04 11.5 22.7 5.48 4.96 41.2

B 2.04 12.0 23.0 5.35 4.95 40.2

C 2.1 14.0 25.0 5.32 5.2 40.2

D 2.01 9.6 20.0 5.51 4.84 41.2

OF.

Bench A 2.07 12.3 23.9 5.97 5.07 42.2

B 2.07 12.8 24.2 5.84 5.06 41.3

C 2.13 15.0 26.1 5.81 5.3 41.1

D 2.04 10.3 22.9 5.97 4.96 42.5

blasting efficiency were analysed by statistical methods.The tests results were made regression analysis for allthe blasting and rock properties. The equation of thebest-fit line at the 95% confidence limit and thecorrelation factor (R

2) were determined for each using

least squares regressions. It was made the statisticalanalysis on the four benches. The block fragmentationcan be estimated from the best empirical correlations withthe rock properties. Good relations were generally foundbetween block fragmentation and physico-mechanical

properties of these rocks using the method. Especiallyhigh correlation values were found between blockfragmentation and tensile strength and internal frictionangle each bench of the study area. Before and afterblasting, block sizes were compared by statisticaanalysis and the results were interpreted.

According to statistical results, a logarithmic relationship (R

2= 0.73) between block size before blasting and

rock fragmentation size after blasting were found inFigure 6. As seen in Figure 6, when block size before the


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Kilic et al. 1219

Figure 5.Before (a) and after (b) blasting.

Table 2.Percentages of block fragmentation after blasting.

I. Bench (%) II. Bench (%) III. Bench (%) OF Bench (%)

A

A1 56.4455.47

0.95

50.0449.24

0.98

30.0529.33

3.33

38.3026.87

10.4A2 54.54 48.14 25.10 17.74

A3 55.45 49.54 32.86 24,59

B

B1 63.0562.33

1.03

53.5652.20

1.28

36.7832.66

3.59

35.7231.25

3.50B2 62.82 51.02 30.18 28.72

B3 61.15 52.03 31.04 32.31

C

C1 57.8557.21

0.71

49.8050.42

0.75

41.9038.66

3.40

38.2532.58

7.03C2 57.35 50.21 35.12 24.72

C3 56.44 51.25 38.96 34.78

D

D1 59.7560.05

1.88

46.9647.69

0.65

31.7627.83

4.13

28.7022.76

5.54D

2 62.06 48.19 23.52 21.85

D3 58.34 47.92 28.23 17.74

blasting increases, blasting efficiency increases.A compa-rison of the Block Fragmentation (BF) sieve size results offour benches and previous works of Kuz-Ram, CorrectedKuz-Ram and Bond-Ram is illustrated in Figure 7.According to Figure 7, the following important observa-tions can be made. The BF directly assessed using thephoto-scanline method appears to lie near the average ofthe predictions from the other three techniques. The BFpredictions from the Kuz-Ram and Corrected Kuz-Rammodels from the far upper and far lower boundaries whilethat from the Bond-Ram model based on the blastabilityassessment is approximately in the middle of the rangeformed by BF from the Kuz-Ram and the Corrected Kuz-Ram models. Also, the BF from the corrected Bond-Rammodel are close to the BF assessed using the photo-scanline technique for the study blasting. Especially thefirst bench presents similar with Bond-Ram and also itgives the best efficiency of block fragmentation ratio infirst bench however, the worst efficiency of that in fourthbench were observed. The average block fragmentation

sieve size of 2 and 3 benches shows similar values withKuz-Ram and Corrected Kuz-Ram.

Table 3 shows the test results, regression analysis andcorrelation factor between block fragmentation and rockphysicomechanical properties (unit volume weightwater absorption, uniaxial compressive strength, Braziliantensile strength, cohesion and internal friction angle).

The first bench data was analysed using regressionanalysis methods. Although correlation values betweenblock fragmentation and Brazilian tensile strength of R2 =0.82 was found high, correlation values between blockfragmentation and unit volume weight of R = 0.14, wateabsorption of R = 0.18, uniaxial compressive strength oR = 0.12, cohesion strength of R = 0.16 and internafriction angle of R = 0.47 were found low. The goodrelation between block fragmentation and tensile strengthwas found (Figure 8).

In second bench, high correlation values as can beseen in Figures 9 and 10 were found between rock fragmentation and Brazilian tensile strength of R = 0.91 and


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Figure 6.The relationship between block fragmentation and block dimensionbefore blasting.

Figure 7. Comparison of block fragmentation with some previousmodels.

internal friction angle of R = 0.84. Furthermore unit

volume weight of R = 0.18, water absorption of R =0.51,uniaxial compressive strength of R = 0.55 and cohesionof R = 0.34 were determined.

In third bench, high correlation values were foundbetween block fragmentation and all of the rock physico-mechanical properties. The correlation factors weredetermined for unit volume weight of R = 0.91, waterabsorption of R = 0.90, uniaxial compressive strength ofR = 0.82 Brazilian tensile strength of R = 0.84, cohesionof R = 0.90 and internal friction angle of R = 0.75. Theempirical equations between block fragmentation and unit

volume weight and cohesion are shown in Figures 11 and

12.In fourth bench, high correlation values were found

between block fragmentation and tensile strength of R =0.86 and internal friction angle of R = 0.96. The otherrelations are unit volume weight of R = 0.69, wateabsorption of R = 0.88, uniaxial compressive strength oR = 0.77 and cohesion of R = 0.64.

After statistical analyses, it was observed that goodrelations were determined between block fragmentationsize and tensile strength, internal fraction angle in albenches. Data of all benches were evaluated as a whole


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Kilic et al. 1221

Table 3.The statistical analysis results between block fragmentation and rock properties.

I. BENCH

Relation of rock properties Equation R

Unit volume weight (, g/cm) - Block fragmentation (BF, %) = -0.0043.BF + 2.253 0.14

Water absorption (w, %) - Block fragmentation (BF, %) w = -0.1462.BF + 18.897 0.18

U. Compressive strength (, MPa) - Block fragmentation (BF, %) = -0.0968.BF + 25.662 0.12

Tensile strength (t, MPa) - Block fragmentation (BF, %) t= -0.0092.BF + 4.9751 0.82

Cohesion (c, MPa) - Block fragmentation (BF, %) c = -0.0208.BF + 5.9496 0.16

Internal Fiction Angle (, ) - Block fragmentation (BF, %) = 18.142.Ln(BF) - 37.257 0.47

II. BENCH


Unit volume weight (, g/cm) - Block fragmentation (BF, %) = 1.1411.BF0.1467

0.14

Water absorption (w, %) - Block fragmentation (BF, %) w = 0.0007.BF2.4855

0.46

U. Compressive strength (, MPa) - Block fragmentation (BF, %) = 12.042.Ln(BF) - 26.381 0.25

Tensile strength (t, MPa) - Block fragmentation (BF, %) t= -0.0292.BF + 6.6769 0.76

Cohesion (c, MPa) - Block fragmentation (BF, %) c = 3.3064e0.0078.BF

0.22

Internal fiction angle (, ) - Block fragmentation (BF, %) = -0.2192.BF + 49.877 0.91III. BENCH


Unit Volume Weight (, g/cm) - Block fragmentation (BF, %) = 0.0075.BF + 1.8058 0.92

Water Absorption (w, %) - Block fragmentation (BF, %) w = 0.3558.BF + 0.353 0.90

U. Compressive Strength (, MPa) - Block fragmentation (BF, %) = 0.3868.BF + 10.251 0.82

Tensile Strength (t, MPa) - Block fragmentation (BF, %) t= -0.018.BF + 5.9926 0.84

Cohesion (c, MPa) - Block fragmentation (BF, %) c = 0.03.BF + 4.0232 0.90

Internal Fiction Angle (, ) - Block fragmentation (BF, %) = -3.4526Ln(BF) + 52.651 0.75

OF BENCH


Unit Volume Weight (, g/cm) - Block fragmentation (BF, %) = 0.007.BF + 1.8776 0.69Water Absorption (w, %) - Block fragmentation (BF, %) w = 0.6371.BF

0.8921 0.88

U. Compressive Strength (, MPa) - Block fragmentation (BF, %) = 0.2635.BF + 16.8 0.77

Tensile Strength (t, MPa) - Block fragmentation (BF, %) t= -0.0176.BF + 6.3958 0.86

Cohesion (c, MPa) - Block fragmentation (BF, %) c = 0.7058Ln(BF) + 2.7432 0.64

Internal Fiction Angle (, ) - Block fragmentation (BF, %) = -0.1492.BF + 46.008 0.96

data and valid empiric formulae were developed in allblasting (Figures 13 and 14). Formulae between blockfragmentation and tensile strength (equation 6), internalfriction angle (equation 7) were found in below:

8281,60375.0 += BFt R = 0.83 (6)

694.451457.0 += BF R = 0.82 (7)

where t= Brazilian tensile strength of rock; BF = block

fragmentation and = internal friction angle.Block fragmentation can be determined by using these

formulae that were obtained from the values of Braziliantensile strength and internal friction angle in laboratoryconditions. As seen in equations 6 and 7, the relationship

between block fragmentation and tensile strengthinternal friction angle were found linear and inverse ratioThis inverse ratio shows that the values of tensilestrength and internal friction angle are low; the size o

block fragmentation is big. It means that determinedtensile strength and internal friction angle in laboratoryconditions, lower Brazilian tensile strength and internafriction angle of rocks having the bigger block fragmen-tation size in the same blasting conditions.

Conclusions

In this study, blasting efficiency was assessed due torock properties, block size of rock mass and muck pileThe proposed methodology of fragmentation efficiency is


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Figure 8. The relationship between tensile strength and blockfragmentation (I. Bench) (all horizontal error bars indicate standarddeviations of the block fragmentation).

Figure 9. The relationship between tensile strength and blockfragmentation (II. Bench).

to compare block size in terms of rock properties in thesame blasting conditions. When planning the developmentof dimension in blasting, it is clearthat large blocks cannotbe produced of they are not there in the first place.Furthermore, in characterising domains of a rock massfor rock blasting development, much greater use can bemade of an entire rock mass block size assessment thana single representative measure of block size such as the50 or 100% passing size. The physical and mechanicalproperties of rocks were determined and then sameblasting method was chosen to determine to the effectsof rock properties. Benches were divided into 4 sectionsand each section has 3 blasting in mining area. It meansthat totally 48 blasting in 4 benches were applied. The

Figure 10.The relationship between internal friction angle andblock fragmentation (II. Bench).

Figure 11.The relationship between unit volume weight and blockfragmentation (III. Bench).

image analysis techniques were used to estimate theblock size distribution. A comparison of the Block Frag-mentation (BF) sieve size results of four benches andprevious works of Kuz-Ram, Corrected Kuz-Ram and

Bond-Ram were found similar with Bond-Ram in firsbench and also the best efficiency of block fragmentationratio but the worst efficiency of that in fourth bench wereobserved.

Determining of the effects of rock physico-mechanicaproperties before blasting and rock fragmentation afteblasting on the blasting efficiency were analysed bystatically methods. Good relations were generally foundbetween block fragmentation and physico-mechanicaproperties of these rocks using the method. The blockfragmentation can be estimated from the best empirica


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Figure 12. The relationship between cohesion and blockfragmentation (III. Bench).

Figure 13.The relationship between tensile strength and blockfragmentation (all benches).

correlations with the rock properties. The results haveshown that big blocks gives small rock fragmentationbetter than small block before the blasting. Formulae

between block fragmentation and tensile strength, internalfriction angle were developed and also relationships werefound linear and inverse ratio.

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Kilic et al. 1223

Figure 14.The relationship between internal friction angle and

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influencia de las propiedades del macizo rocoso en la eficiencia de voladura

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