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Estimation of fines generated by blasting - Applications for the mining

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Article  in  Transactions of the Institution of Mining and Metallurgy, Section A: Mining Technology · December 2006
DOI: 10.1179/174328606X158810 · Source: OAI

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Estimation of fines generated by blasting – applications for the
mining and quarrying industries

I. Onederra, S. Esen and A. Jankovic

This paper introduces an engineering approach to continuous improvement analysis and applications. The
estimate the proportion of fines generated during the practical application of the proposed modelling framework
blasting process. The proposed framework is based on is demonstrated with an engineering study aimed at
the combination of two Rosin-Rammler based assessing the impact of blast fragmentation on the overall
distribution functions to model the full range of production of fines in a hard rock quarry. Results from
fragments expected to be produced during this process. simulations showed that less crushing requirements due to
This particular approach, which has been successfully an overall increase in fragmentation contribute to a
applied for a number of years by the Julius Kruttschnitt decrease in the specific crushing energy and hence a
Mineral Research Centre (JKMRC), has been reduction in power consumption requirements. This
improved with the introduction of a new model to predict analysis helped demonstrate the importance of addressing
the potential volume of crushed material resulting from the impact of blast fragmentation distribution on overall
the crushing and shearing stages of blasting. Other quarry productivity requirements; and highlights the
sources of fines including liberation of infilling from importance of adopting a holistic approach when
discontinuities, particle collisions and post-blast addressing the blast optimisation problem.
processes have been excluded to simplify the modelling I. Onederra (for correspondence – I.Onederra@ uq.edu.au), S.
process. Validation analysis of the proposed framework Esen and A. Jankovic are at the Julius Kruttschnitt Mineral
has shown that there is good agreement between model Research Centre, The University of Queensland, St Lucia,
predictions and the measured distribution of fines. In Brisbane, Queensland, Australia.
three distinct cases, results verified the hypothesis that a © 2004 Institute of Materials, Minerals and Mining and
single index of uniformity can be used to describe the Australasian Institute of Mining and Metallurgy. Published by
distribution of fragments in the range of 1 mm through Maney on behalf of the Institutes. Manuscript received 18
to the expected post-blast mean fragment size (x50). August 2004; accepted in final form 20 October 2004.
Although some limitations have been noted, the Keywords: Fines, blasting, volume, particle size, Rosin-
approach appears to provide useful approximations for Rammler model

INTRODUCTION suggest that by providing an appropriate size

Blasting activities in mines and quarries have been distribution to crushing and grinding circuits, a
placing significant emphasis on the ability to tailor measurable increased throughput and/or reduced power
fragmentation to improve downstream processes. In draw can be obtained.12 This may entail a requirement to
many of these operations, the impact of fines has been increase the proportion of finer material in production
clearly identified. For example, the generation of blasting activities.
excessive fines in operations adopting in situ leaching as The need to be able to predict the amount of fines from
the main ore processing method, may hinder recovery as blasting has driven the development of an improved
certain fines tend to affect the permeability of leaching engineering model. The model being proposed is based on
pads. Leaching performance may be affected if the findings from both model-scale and full-scale data.
proportion of material that is less than 150 µm exceeds Model-scale data were obtained from a comprehensive
12% in the feed to the agglomerators.24 Similarly, the experimental programme,3 whilst full-scale studies have
efficiency of coal processing is strongly related to the been compiled from surveys conducted over a number of
generation of fines of less than 0·5 mm. Increased fines years by researchers of the Julius Kruttschnitt Mineral
content in run-of-mine feed leads to higher handling and Research Centre (JKMRC).
processing costs, low yields, increased product moisture
content, and in many cases a reduced product value.10
The same can be said of quarry operations where FRAGMENTATION MODELLING
material of less than 2·4–15 mm in size may be FRAMEWORK
considered to be of no value and hence wasted. For a number of years, the JKMRC has been applying
Whilst fines may be detrimental to some operations, two empirical models to estimate muckpile frag-
in large-scale metalliferous mining there is evidence to mentation distributions in surface blasting operations.

DOI 10.1179/037178404225006191 Mining Technology (Trans. Inst. Min. Metall. A) December 2004 Vol. 113 A237
Onederra et al. Estimation of fines generated by blasting

These empirical models are the two-component model Kuz-Ram based distribution with the proposed combined
(TCM)8 and the crushed zone model (CZM).15 These distribution functions. This figure also highlights the main
models are a hybrid between the well-known Kuz-Ram modelling parameters, namely the fines inflection point
approach6 and two specific fines predictive models. A (fc), the expected mean fragment size (x50) and the ‘coarse’
comparison of these two models conducted by Hall and uniformity index (nc), also referred plainly in literature as
Brunton14 has highlighted some deficiencies in their the uniformity index (n). In this paper, a thorough
predictive capabilities, due principally to some limitations description of a revised approach to determine the fines
in their estimations of fines and intermediate size inflection point fc is given. The determination of the other
fractions. Their conclusions indicated that there was a two key modelling parameters (i.e. the mean fragment
need to review and further improve ways of predicting the size, x50 and the ‘coarse’ uniformity index, nc) follows the
distribution of fines and, in particular, estimations of well-documented Kuz-Ram approach2,5,6,8,15 and is,
crushing in the vicinity of detonated blastholes. This study therefore, not covered here.
has been part of that process.
Building on the hybrid approach incorporated in the The fines inflection point (fc)
CZM model, the expected distribution of fragments in Literature indicates that fines present in a muckpile
the fines and coarse regions is modelled by two separate tend to originate from the near field crushing zone,
functions. These two functions are based on the well- fracturing (shearing) zones as well as possible
established Rosin-Rammler distribution23 and given by: liberation from rock mass discontinuities.9,11,25 The
x
nf fines inflection point is introduced to consider these
R _ x i = 1 - e - 0.693 a x k
50
Eq. (1) sources and is given by:
for values of x less than or equal to x50
f c = %Fines(- 1 mm) = c V c V
+ V b # 100 + F
m 7 rA Eq. (4)
1

nc
x where Vc is the volume contribution of the crushed
R _ x i = 1 - e - 0.693 a x k Eq. (2)
50
zone, Vb is the volume contribution from breakage
for values of x greater than x50 (major radial cracks), Vt is the total volume being
blasted and Fr is a rock mass fines correction factor.
where R(x) is the proportion of the material passing a The fines inflection point is based on the
screen of size x, x50 is the post-blast mean fragment hypothesis that, for most conditions, the coarsest
size, nc is the uniformity index for the coarse end of the particle size expected to be generated during the
distribution and nf is the fines uniformity index which crushing and shearing stages of blasting would be 1
is given by: mm, and that the percentage passing fraction would
n f
be directly proportional to the volume of crushed
LN c x m
- 0.693 and/or sheared rock material surrounding a detonated
nf = Eq. (3)
blasthole.
LN c x150 m
As depicted in Figure 2, the estimation of the
where fc is the proportion of the material passing a volume of crushed and/or sheared rock material
screen of size 1 mm or the fines inflection point. follows simple geometric calculations given by (i) the
The modelling framework is graphically illustrated in radius of crushing and thus the volume of a cylinder
Figure 1 by comparing the standard Rosin-Rammler or of crushed rock; and (ii) the distribution of major

1 Key parameters of the proposed fragmentation modelling framework

A238 Mining Technology (Trans. Inst. Min. Metall. A) December 2004 Vol. 113
 Onederra et al. Estimation of fines generated by blasting

Table 1 Physical and mechanical properties of rock types

Case study Rock type sc (MPa) T (MPa) ρ (kg m–3) Ed (GPa)

26
1. Coal blasting Coal 20 2·0 1440 9·6
2. Mount Cootha18 Hornfeld 200 16 2730 83·0
3. Ok Tedi Mine1 Monzodiorite 55 7·8 2600 34·0
4. Cadia Hill Gold15 Monzonite 127 9·0 2600 77·0
5. Escondida Mine7 Porphyry ore 22 3·0 2616 15·2
6. Porgera Gold Mine4 Hornblende Diorite 138 13·0 2725 70·0

T, tensile strength; ρ, density.

radial cracks, which are assumed to be evenly where Pb is the borehole pressure (Pa), computed from
distributed around a borehole, planar and also non-ideal detonation theory, K is the rock stiffness
continuous along the length of the explosive charge. (Pa) and σc is the uni-axial compressive strength (Pa).
These two components define the total volume of a Rock stiffness K is defined assuming that the material
‘star’-shaped crushed region (i.e. Vc + Vb). within the crushing zone is homogeneous and
In the proposed modelling framework, a rock mass isotropic and is given by:
correction factor (Fr) has been introduced to address
the hypothesis that fines may also be liberated from K= Ed Eq. (7)
1 + yd
rock mass discontinuities.9 However, an approach to
determine this parameter has not been developed, as where Ed is the dynamic Young’s modulus (Pa) and υd
there is insufficient quantifiable evidence to support is the dynamic Poisson’s ratio.
this. To simplify the modelling structure, the Fr As discussed by Esen et al.,11 this model has been
parameter is, therefore, currently disregarded and the shown to have better predictive capabilities than other
modelling process involves only the determination of documented approaches. Its validity has also been
Vc and Vb. confirmed with data obtained from full scale blasting
conditions.
Given this improved modelling approach, the relative
The crushed zone model to determine Vc
role of the crushed zone in the overall contribution of fines
The determination of Vc is based on an improved
was investigated with the back analysis of several case
model to predict the radius of crushing generated by a
studies. Table 1 gives a summary of the physical and
detonated blasthole reported by Esen et al.11 This
mechanical properties of the rock types at each site, and
model is given by the empirical relationship:
Table 2 presents a summary of the explosive and blast
0.219 design parameters adopted in each case.
rc = 0.812ro _ CZI i Eq. (5)
Results from this preliminary back analysis are
given in Table 3. The analysis shows that following the
where rc is the crushing zone radius (mm), ro is the
ISRM rock classification system, categorised by
borehole radius (mm) and CZI is defined as the
Young’s modulus (<www.rockmass.net>), in the soft
crushing zone index. This is a dimensionless index
(low strength) rock types, the proportion of fines due
that identifies the crushing potential of a charged
to the crushed zone relative to the total amount of
blasthole and is calculated from:
3 fines, are in the range of 9·1–19·6% (Cases 1, 3 and 5).
_ Pb i In the medium-to-hard (high strength) rocks, the
CZI = Eq. (6)
_ K i # v 2c range is 8·5–9·2% (Cases 2, 4 and 6). This analysis

2 Volume of crushed material around a blasthole

Mining Technology (Trans. Inst. Min. Metall. A) December 2004 Vol. 113 A239
Onederra et al. Estimation of fines generated by blasting

Table 2 Explosive and design parameters

Hole Detonation Explosive Charge Burden ×

diameter velocity density length spacing ×
Case study Explosive (mm) (m s–1) (kg m–3) (m) bench height (m)

1. Coal blasting 26
Emulsion 150 5340 1180 5.4 7 × 7 × 9·5
2. Mount Cootha18 Emulsion 102 5447 1200 11·5 3·5 × 4 × 14
3. Ok Tedi Mine1 Emulsion 251 5000 1150 10·0 7·4 × 8·5 × 15
4. Cadia Hill Gold15 Emulsion 229 4950 1200 12·0 6 × 7 × 15
5. Escondida Mine7 Emulsion 270 5020 1050 7·5 7·4 × 8·5 × 15
6. Porgera Gold Mine4 Emulsion 200 4500 1250 5·3 5·5 × 6·2 × 12

clearly supports the hypothesis that in full scale The strain at the blasthole wall, εs, can be
blasting operations, the crushed zone around a approximated by Katsabanis:16
blasthole is not the only significant source of fines, _1 - y i Pb
and that in most cases, the contribution of breakage fs = Eq. (9)
2 _1 - 2y i to 2p + 3 _1 - y i cPb
can be expected to be significant.
As the proposed approach seeks to estimate the where Pb is the explosion or borehole pressure (Pa); ρ
proportion of fines only present in the muckpile, post- is the rock density (kg m–3); vp is the P-wave velocity
blast sources such as excavation, handling, mechanical (m s–1); γ is the adiabatic exponent of the detonation
sieving and crushing are not relevant to the modelling products; and υ is the Poisson’s ratio of the rock.
framework being proposed. However, fines generated The length or radial extension of cracks is
by the breakage process itself must be considered. In determined empirically with the stress attenuation
order to address the issue of incorporating the function proposed by Liu and Katsabanis,19 assuming
contribution of overall breakage on the proportion of that the crack will arrest when the induced stress is
fines (i.e. Vb in the proposed framework), a simplistic equal to the static tensile strength or the rock material.
crack model has been adopted. This model is In this case, the following relationship is proposed:
proposed as a preliminary engineering tool to estimate 1

C 1 = ro c PT s m - rc
z
the parameter Vb as discussed below. Eq. (10)
eq

The crack model to determine Vb where Ts is the static tensile strength of the rock (Pa),
The following approach assumes that the source of ro is the blasthole radius (m), rc is the radius of
fines from overall breakage is directly proportional to crushing (m), φ is the pressure decay factor and Peq is
a volume of crushed material bounded by major blast the equilibrium pressure (Pa), or the pressure
induced fractures. The number of near field radial experienced at the end of the crushing zone which is
cracks (C) around the blasthole is estimated following given by:
the approach proposed by Katsabanis:16 z

Peq = Pb c rroc m Eq. (11)

C = f s c TPb m Eq. (8)
The pressure decay factor φ is a function of rock
d

where εs is the strain at the blasthole and Td is the and explosive properties. It is a negative number that
dynamic tensile strength of the rock (Pa), which is has been found to be in the range of –1·24 to –1·65 for
assumed to be in the range of 4–8 times the static value. a wide range of explosive and rock combinations.19 A

Table 3 Role of the crushed zone in the generation of fines

Case study rc Vc Blast % –1 mm % –1 mm Relative proportion

(mm) (m3) volume (crushed (measured Measurement of fines from the
(m3) zone) total fines) technique crushed zone (%)

1. Coal blasting26 746 9·34 465·5 2·00 17·0 Mobile screening after excavation 11·8 (Vb, Fr, E&H, S)
and handling
2. Mount Cootha18 122 0·45 197·23 0·21 2·3 Primary crusher product 9·1 (Vb, Fr, E&H, C)
3. Ok Tedi Mine1 573 9·83 944·6 1·00 11·0 Split* with fines correction from 9·1 (Vb, Fr, E&H, C)
crusher product
4. Cadia Hill Gold15 301 2·92 631·8 0·46 5·0 Split with fines correction from 9·2 (Vb, Fr, E&H, C)
crusher product
5. Escondida Mine7 1085 27·3 944·6 2·90 18·0 Split with fines correction from 16·1 (Vb, Fr, E&H, C)
crusher product
6. Porgera Gold Mine4 229 0·71 406·6 0·17 2·0 Split with fines correction from 8·5 (Vb, Fr, E&H, C)
crusher product

* Split refers to the Split Engineering image analysis technique.17

Vb, contribution from the fracturing or breakage process; Fr, contribution of fines liberated from rock mass discontinuities;
E&H, excavation and handling; S, mechanical sieving; C, crushing.

A240 Mining Technology (Trans. Inst. Min. Metall. A) December 2004 Vol. 113
 Onederra et al. Estimation of fines generated by blasting

Table 4 Comparison between new modelled results and measured values

Case study & rock type rc Number Volume crushed Blast % –1 mm % –1 mm

(mm) of cracks (C) Vc + Vb (m3) volume (m3) (model) (measured)

1. Coal 746 43 38·1 465·5 8·2 17

2. Hornfeld 122 2 2·81 197·23 1·43 2·3
3. Monzodiorite 573 6 60·5 944·6 6·4 11
4. Monzonite 301 3 29·3 631·8 4·6 5
5. Porphyry ore 1085 23 107 944·6 11·3 18
6. Hornblende Diorite 229 2 4·85 406·6 1·2 2

first approximation can be obtained with the The adopted criteria for validation involved a direct
following empirical relationship: comparison between the measured and predicted 10%
- 0.33 and 20% passing fractions (i.e. P10 and P20). The
op
z =- _ 0.0085E d + 0.9955i d Eq. (12) adoption of P10 and P20 values as a comparison
VOD n
benchmark is justified by their common use as input
where Ed is the dynamic Young’s modulus (GPa), vp is parameters in comminution simulation tools for the
the p-wave velocity (m s–1) and VOD is the confined design and optimisation of crushing and grinding
velocity of detonation of the explosive charge. circuits. Table 5 gives a summary of the input
In order to make preliminary verifications of the parameters available and used in the analysis.
proposed crack model, all of the case studies In case study 1, fragmentation assessment and blast
described in Table 3 have been re-analysed and new monitoring work have been reported by Hall13 and
crushed volume predictions have been made and involved the application of image analysis techniques for
summarised in Table 4. material greater than 258 mm. Below this size, the
As shown in Table 4, there is now better agreement material was initially screened in the field, followed by sub-
between the measured and the modelled proportion of sampling and laboratory screening down to 0·36 mm.
fines at the assumed cut-off point of 1 mm. Discrepancies In case studies 2 and 3, reported by Onederra and
are within the expected errors associated with sampling Corder,22 two important blasting/ore domains were
and modelling assumptions. In general, in all rock types, identified and surveyed in benches 2755S1 and
the predicted fines inflection point is lower when compared 2875N11 of the pit. In both of these domains, the
to the measured total fines. This is more pronounced in the proportion of fragments less than 1 mm in size (i.e.
weaker rock types where further degradation can be fines inflection point) was measured from laboratory
expected from handling, transportation and crushing, as sieving of the primary crusher product or what is
has been previously demonstrated by Djordjevic et al.10 referred to as belt cut sampling.
For the conditions described above and following
the procedures outlined earlier, the zones contributing
VALIDATION OF THE PROPOSED FINES to crushing given by the Vc and Vb parameters were
MODELLING FRAMEWORK calculated and the fines inflection point (fc)
The approach to predict the fines inflection point (fc) determined in each case. Table 6 summarises the
and the derivation of a single index of uniformity (nf) model results together with the measured values.
to describe the distribution of fines between this point As shown in Table 6, in all three cases the predicted
and the mean fragment size is validated in this section. fines inflection point values are reported below the
A comparison between model predictions and measured values. This is considered to be a logical
measurements conducted in three full-scale blasts outcome, as the proposed fines modelling framework
outside the original database has been carried out. does not consider the contribution of fines given by

Table 5 Descriptive parameters of case studies

Case study

1 2 3
Quarry blast13 Open pit – Blast 2755S122 Open pit – Blast 2875N1122
Explosive Emulsion Heavy ANFO Heavy ANFO
Hole diameter (mm) 109 270 270
VOD (m s–1) 5345 5100 5100
Explosive density (kg m–3) 1150 1250 1250
Charge length (m) 11·3 7·2 7·2
Burden × spacing × bench height (m) 3·6 × 4·2 × 13·5 6·5 × 6·5 × 16 7·0 × 7·0 × 16
Rock type Foliated phyllite Porphyry ore Porphyry ore
σc (MPa) 71 (parallel to foliations) 58 61
T (MPa) 11·0 6·0 6·0
ρ (kg m–3) 2700 2500 2500
Ed (GPa) 30·0 37·0 37·0

Mining Technology (Trans. Inst. Min. Metall. A) December 2004 Vol. 113 A241
Onederra et al. Estimation of fines generated by blasting

Table 6 Comparison between modelled and measured fines inflection point values for three full scale blasts

Volume Fines inflection point

Number of crushed Blast % –1 mm % –1 mm
Case study rc (mm) cracks (C) Vc + Vb (m3) volume (m3) (model) (measured) Difference
19
1. Quarry blast 240 5 8·36 202·95 4·1 4·9 0·8
2. Blast 2755S113 606 8 54·2 676 8·0 11·4* 3·4
3. Blast 2875N1113 592 8 60·2 833 7·2 12·3* 5·1

*Primary crusher product (belt cut sampling).

particle collisions and degradation of the rock material Figure 3 shows a comparison between the predicted
from loading, handling, transportation, and dumping. and measured fines, highlighting the 10% and 20% passing
In cases 2 and 3, differences between predicted and fractions. A parity chart of measured versus modelled
measured fc values of 3·4% and 5·1% may be perceived as cumulative percentage passing for fragments in the range
gross underestimations of the proposed model. However, of 1–63 mm is also included. It should be noted that, in all
the friable nature of the complex porphyry ore was cases, the fines uniformity index (nf) and the subsequent
expected to be subject to further degradation from modelled distribution of fines was determined with the
loading, handling and dumping prior to crushing. This measured post-blast mean fragment size (x50). This was
susceptibility to degradation was confirmed by the considered adequate in order to assess the validity of the
measured differences between the primary crusher hypothesis proposing that a single index of uniformity can
product and SAG mill feed fragmentation. This difference be used to describe adequately the distribution of
was of the order of 5–8% for the –1 mm size fraction in the fragments from 1 mm through to the expected post-blast
N11 and S1 domains, respectively.22 mean fragment size (x50).

3 Comparison between modelled and measured fines in three full scale blasts
Case study P10 Difference % P20 Difference % Model Model
(mm) (mm) Error (mm) (mm) Error Measured Measured

1. Quarry blast19 4·5 4 –0·5 –12·5 15·5 13* –2·5 –19·2

2. Blast 2755S113 1·7 N/A N/A N/A 8·5 9·8+ 1·3 13·3
3. Blast 2875N1113 2·0 N/A N/A N/A 9·5 11+ 1·5 13·6

*Laboratory sieving; +calibrated SPLIT image analysis system.

A242 Mining Technology (Trans. Inst. Min. Metall. A) December 2004 Vol. 113
 Onederra et al. Estimation of fines generated by blasting

Table 7 Blast design parameters for simulated conditions

Blast 1 Blast 2

Explosive Emulsion Emulsion

Hole diameter (mm) 109 109
Detonation velocity (m s–1) 4968 4968
Explosive density (kg m–3) 1180 1180
Charge length (m) 11·3 11·3
Burden × spacing × bench height (m) 3·6 × 4·2 × 13·5 3·0 × 3·5 × 13·5
Powder factor (kg m–3) 0·61 0·88

As shown in Figure 3, the proposed fragment size point (fc) adequately. Further work is being conducted to
distribution function appears to be an adequate address the above limitation and refine the overall
descriptor of the expected distribution of fines generated predictive capabilities of the model.
in full-scale blasting conditions. The parity chart shows
that although the model may in some cases
underestimate and overestimate the proportion of fines APPLICATION OF THE PROPOSED FRAG-
generated by blasting, overall trends are being captured MENTATION MODELLING FRAMEWORK
by this single uniformity index. In terms of the predictive To demonstrate the practical application of the proposed
errors associated with specific size fractions such as P10 fragmentation modelling framework, fragmentation
and P20, for case 1, the error is of the order of –12·5% distributions for two blasts have been modelled and used
and –19·2%, respectively, whilst for cases 2 and 3, the as input to processing simulations. This cross-disciplinary
average predictive error for P20 is about 13·5%. This is modelling work was aimed at assessing the impact of blast
considered adequate for engineering design purposes fragmentation on the overall production of fines in a hard
given the expected variability of rock material and rock quarry. The analysis focused on quantifying the
explosive performance within the blasted volume. relative contribution of blasting to the total production of
Whilst the above cases support the hypothesis that in fines or waste material and it is based on conditions found
full-scale blasting conditions the use of a single index of at the Mount Cootha Quarry summarised in Table 1 and
uniformity is appropriate to describe the distribution of documented by Kojovic et al.18
fragments from the fines inflection point (fc) to the mean Quarry processing simulations were conducted
fragment size (x50). Recent large-scale field trials following two specific requirements. The first related to
conducted in more massive and competent rock masses20 the production of fine aggregates (product range, 18 mm
have shown that an approach based on a single to 2·4 mm), with waste considered to be any material less
uniformity value may produce an overestimation of the than 2·4 mm. This required the implementation of three
proportion of fines, particularly in the range of 10–100 stages of crushing similar to that illustrated in Figure 4.
mm. Results from sieved muckpiles under these The second simulation considered the production of
environments have shown that in the fines region there coarser aggregates (product range 32 mm to 10 mm),
could be at least two marked changes in uniformity which with waste considered to be any material less than 10
describe the natural breakage characteristics of the rock mm. This required the implementation of only two
material. A preliminary comparison of these data with stages of crushing.
the proposed fines distribution function has confirmed Table 7 describes the blast design parameters
this. However, it is important to highlight that for the adopted in this modelling exercise. Geotechnical
repeatable documented cases, the proposed star-shaped properties measured at the Mount Cootha Quarry are
crushed model was able to estimate the fines inflection described in Table 1. Results of the expected muckpile

4 Example of a three stage crushing circuit at the Mount Cootha quarry (after Kojovic et al.18)

Mining Technology (Trans. Inst. Min. Metall. A) December 2004 Vol. 113 A243
Onederra et al. Estimation of fines generated by blasting

fragmentation distributions given by the proposed Table 8 Processing simulation results

fragmentation modelling framework are shown in
Processing method Fine processing Coarse processing
Figure 5. Waste: less Waste: less
As discussed earlier, the results of the blast than 2·4 mm than 10 mm
fragmentation model shown in Figure 5 have been
Blasting scenario Blast 1 Blast 2 Blast 1 Blast 2
used as input into two quarry processing simulation ROM P80 (mm) 192·5 145·6 192·5 145·6
options using the JKSimMet program. This program ROM –2·4 mm (%) 6·6 9·3
has been developed from extensive JKMRC ROM –10 mm (%) 13·7 18·1 13·7 18·1
experience in the field of comminution and has now PCP P80 (mm) 135·5 123·1 107·6 102·4
become an industry standard tool for design and PCP –10 mm (%) 14·9 18·6 16·3 19·7
PCP –2·4 mm (%) 7·1 9·5
optimisation of mineral processing activities.21 A Primary crusher (kW) 17·2 15 21·4 18
summary of the simulation results for both blasting SCP P80 (mm) 33·8 33·2 35·2 33·4
scenarios and the two processing options are shown in SCP –10 mm (%) 30·7 33·2 15·9 15·8
Table 8 and Figures 6 and 7. SCP –2·4 mm (%) 13·3 15·1
The application of the proposed fines modelling Secondary crusher (kW) 53·8 49·7 86·4 83·4
Tertiary crushers (kW) 192·3 188·7
framework in conjunction with quarry processing
simulation models have shown that any increase in the Final products
proportion of fines generated during the blasting –18+10 mm (%) 33·1 32·4
process does not translate directly into an equivalent –11·2+6·8 mm (%) 16·5 16·2
increase in the amount of fines or waste product –6·8+2·4 mm (%) 26·6 26·6
–2·4 mm (%) 23·8 24·8
downstream (i.e. after crushing). This is because a –32+18 mm (%) 44·8 43·2
significant proportion of fines may be generated –18+10 mm (%) 24·2 23·7
during the crushing stages of the production of the –10 mm (%) 31 33·1
required products.
As shown in Figure 6, the impact of crushing on Total (kWh t–1) 2·63 2·53 1·08 1·01
fines (waste) generation is more pronounced in the
ROM, run-of-mine; PCP, primary crusher product
finer quarry processing circuit, where three stages of SCP, secondary crusher product.
crushing are required. The amount of fines generated
in crushing is about 1·6–2·6 times of that produced by
crushing energy and hence a reduction in power
blasting for blasts 2 and 1, respectively. In the coarser
consumption requirements. This suggests that, in the
processing circuit (Fig. 7), fines generated from
case where finer aggregate products are required, the
blasting have a more significant contribution to the
environmental and cost benefits of decreased power
total production of waste material. As shown, the
consumption must be weighed against the penalty of
amount of fines produced in crushing are about
increasing the amount of fines generated after
0·8–1·3 times of that produced by blasting for blasts 2
processing. As shown in Figure 6, a 2·7% increase in
and 1, respectively.
the amount of fines due to the higher intensity blast,
The analysis shows that in both cases, less crushing
translates only to a 1% increase in the total amount of
requirements due to an overall increase in
waste, but at the same time a 4% reduction in the
fragmentation contribute to a decrease in the specific
power consumption requirements. For the coarse

5 Modelled fragmentation distributions for blast 1 and blast 2

A244 Mining Technology (Trans. Inst. Min. Metall. A) December 2004 Vol. 113
 Onederra et al. Estimation of fines generated by blasting

6 Simulation results describing the proportion of fines (waste product) generated by blasting and processing in the
three stage crushing circuit

7 Simulation results describing the proportion of fines (waste product) generated by blasting and processing in the
two stage crushing circuit

aggregate production option (Fig. 7), higher intensity stages of blasting. Other sources of fines including
blasting results in a 2·1% increase in waste product but liberation of infilling from discontinuities, particle
a 6% reduction in power consumption. Because of the collisions and post-blast processes have been excluded
finer fragmentation in blast 2, there would be an to simplify the modelling process.
increase in loading and hauling productivity which Based on the back analysis of a number of full-
has not been quantified in this paper. It is important scale blasting surveys, this study has confirmed that
to add that this will have an impact on the total cost of upon detonation of an explosive, the region of
production as documented by Kojovic et al.18 crushing around a blasthole is not the only source of
fines. This has justified the inclusion of a factor that
considers the contribution to fines by the overall
CONCLUSIONS fracturing process.
An engineering approach to predict the proportion of The overall modelling framework has been
fines generated during blasting has been presented. validated with three distinct case studies. Results from
The improved ‘hybrid’ approach introduces a new this analysis have shown that there is good agreement
model to predict the potential volume of crushed between model predictions and the measured
material resulting from the crushing and shearing distribution of fines, verifying the hypothesis that a

Mining Technology (Trans. Inst. Min. Metall. A) December 2004 Vol. 113 A245
Onederra et al. Estimation of fines generated by blasting

single index of uniformity can be used to describe the optimisation at Porgera gold mine’, JKMRC internal
distribution of fragments in the range of 1 mm report, 2001.
through to the expected post-blast mean fragment size 5. S. H. CHUNG and P. D. KATSABANIS: ‘An integrated
(x50). Some limitations have been noted, particularly approach for estimation of fragmentation’, Proceedings of
the 27th annual conference on explosives and blasting
with regards to the possible overestimation of fines in
technique (ISEE), Vol. 1, 2001, 247–256.
more massive and competent rock types. However, the
6. C. V. B. CUNNINGHAM: ‘The Kuz-Ram model for
approach appears to provide useful approximations prediction of fragmentation from blasting’, Proceedings of
for continuous improvement analysis and engineering the first international symposium on rock fragmentation
applications. Further work is continuing to identify by blasting, Lulea, Sweden, 1983, 439–453.
other possible limitations and thus improve the 7. D. DAVID, I. BRUNTON and D. THORNTON: ‘Mine to
framework’s predictive capability. mill surveys of Minera Escondida Ltd’, Internal JKTech
The practical application of the current framework report, Job No 99251, 2001.
has been demonstrated with a cross-disciplinary 8. N. DJORDJEVIC: ‘Two-component of blast
modelling study. The study was aimed at assessing the fragmentation. Fragblast 1999’, South African Institute of
impact of blast fragmentation on the overall Mining and Metallurgy, Johannesburg, South Africa,
1999, 213–219.
production of fines in a hard rock quarry. Results have
9. N. DJORDJEVIC: ‘Origin of blast induced fines. Min.
indicated that any increase in the proportion of fines
Technol. (Trans. Inst. Min. Metall. A), 2002, 112,
generated during the blasting process does not A143–A146.
translate directly into an equivalent increase in the 10. N. DJORDJEVIC, J. ESTERLE, D. THORNTON and D. LA
amount of fines or waste product downstream (i.e. ROSA: ‘A new approach for prediction of blast induced
after crushing). This is because a significant coal fragmentation’, Mine to Mill 1998 Conference, The
proportion of fines may be generated during the Australasian Institute of Mining and Metallurgy,
crushing stages of the production of the required Brisbane, Australia, 1998, 175–181.
products. The impact of blasting will depend on the 11. S. ESEN, I. ONEDERRA and H. BILGIN: ‘Modelling the
final product requirements. Further analysis also size of the crushing zone around a blasthole’, Int. J. Rock
showed that less crushing requirements due to an Mech. Min. Sci., 2003, 40, 485–495.
12. C. GRUNDSTROM, S. S. KANCHIBOTLA, A. JANKOVICH
overall increase in fragmentation contribute to a
and D. THORNTON: ‘Blast fragmentation for maximising
decrease in the specific crushing energy and hence a
the sag mill throughput at Porgera Gold Mine’,
reduction in power consumption requirements. Proceedings of the 27th Annual Conference on Explosives
The application case study has helped demonstrate and Blasting Technique, ISEE, Orlando, Florida, USA,
the importance of addressing the impact of blast 2001, 383–399.
fragmentation distribution on overall quarry 13. J. HALL: ‘A critical comparison of blast fragmentation
productivity requirements. This highlights the models’, unpublished Masters of Engineering Science
importance of adopting a holistic approach when thesis, University of Queensland, 2003.
addressing the blast optimisation problem and the key 14. J. HALL. and I. BRUNTON: ‘Critical comparison of
role that engineering modelling tools, such as those JKMRC blast fragmentation models’, Proceedings of the
proposed in this paper, can play in this process. EXPLO 2001 Conference, Hunter Valley, NSW, 2001,
207–212.
15. S. S. KANCHIBOTLA, W. VALERY and S. MORRELL:
‘Modelling fines in blast fragmentation and its impact on
ACKNOWLEDGEMENTS crushing and grinding’, Explo ‘99 – A conference on rock
The authors would like to thank Prof. E. T. Brown, breaking, The Australasian Institute of Mining and
Mr Ian Brunton and Dr G. Chitombo for their Metallurgy, Kalgoorlie, Australia, 1999, 137–144.
comments and suggestions. The authors also wish to 16. P. D. KATSABANIS: ‘Explosives technology – open pit and
thank Assoc. Prof. Dr H. Aydin Bilgin of the Middle underground blasting’, Part D, Chapter 5, Canada,
East Technical University, Ankara, Turkey for his Queen’s University, 1996.
collaborations with the JKMRC. 17. J. KEMENY, K. GIRDNER, T. BOBO and B. NORTON:
‘Improvements for fragmentation measurement by digital
imaging: accurate estimation of fines’, Sixth International
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1. C. BAILEY, D. THORNTON and M. DUNGLISON: ‘Mine SAIMM, 1999, 103–110.
to mill surveys of OK Tedi Mining Limited’, Internal 18. T. KOJOVIC, S. MICHAUX and C. MCKENZIE: ‘Impact of
JKTech report, Job No 99244, 2000. blast fragmentation on crushing and screening operations
2. M. BAILING, Z. SHIQI, Z. DINGXIANG and G. CHUJI: ‘A in quarrying’, Proceedings of the EXPLO 1995
study of bench blasting in rhyoporphyry at a reduced scale Conference, Brisbane, QLD, 1995, 427–435.
and the statistical analysis of the regularity for 19. Q. LIU and P. D. KATSABANIS: ‘A theoretical approach to
fragmentation distribution’, Proceedings of the First the stress waves around a borehole and their effect on rock
International Symposium on Rock Fragmentation by crushing’, Proceedings of the Fourth International
Blasting, Lulea, Sweden, 1983, 857–872. Symposium on Rock Fragmentation by Blasting –
3. H. A. BILGIN, S. ESEN and M. KILIC: ‘Patarge Project, Fragblast-4, 1993, 9–16.
Internal Report (in Turkish)’, Barutsan A.S., Elmadag, 20. P. MOSER, M. OLSSON, F. OUCHTERLONY and A.
Ankara, Turkey, 1999. GRASEDIECK: ‘Comparison of the blast fragmentation
4. I. BRUNTON, A. JANKOVIC, S. KANCHIBOTLA, T. from lab-scale and full-scale tests at Bararp’, (ed. R.
LICINA, D. THORNTON and W. VALERY: ‘Mine to mill Holmberg), Proceedings of EFEE 2nd world conference

A246 Mining Technology (Trans. Inst. Min. Metall. A) December 2004 Vol. 113
 Onederra et al. Estimation of fines generated by blasting

on explosives and blasting technique, Prague, Czech blasting activities. He currently holds the position of Senior
Republic, 2003, 449–458. Project Engineer at the Julius Kruttschnitt Mineral
21. T. J. NAPIER-MUNN, S. MORRELL, R. D. MORRISON Research Centre (JKMRC), University of Queensland,
and T. KOJOVIC: ‘Mineral communition circuits their Australia. He holds a BE (Hons) from the University of
operation and optimisation’, JKMRC, The University Melbourne, a MEngSc from the University of Queensland
of Queensland, Brisbane, Australia, 1996. and has recently completed studies towards a PhD in mining
22. I. ONEDERRA and G. CORDER: ‘Mine to mill at engineering. Italo has worked in industry-funded R&D and
Laguna Seca, Minera Escondida Limitada’, JKTech consulting projects involving more than 24 mining
Report, Job No 03185, 2003. operations in Australia and overseas – including Chile,
23. R. ROSIN and E. RAMMLER: ‘Laws governing fineness Argentina, Brazil, South Africa and Botswana.
of powdered coal’, J. Inst. Fuels, 1933, 7, 29–36.
24. A. SCOTT, D. DAVID, O. ALVAREZ and L. VELOSO: Sedat Esen gained his BSc (1994) and MSc (1996) degrees in
‘Managing fines generation in the blasting and crushing Mining Engineering from the Middle East Technical
operations at Cerro Colorado Mine’, Mine to Mill 1998 University, Ankara, Turkey and holds a PhD degree (2004)
Conference, The Australasian Institute of Mining and in Mining Engineering from the JKMRC, the University of
Metallurgy, Brisbane, Australia, 1998, 141–148. Queensland, Australia. He has applied research and
25. V. SVAHN: ‘Generation of fines around a borehole: a consulting experience in blasting engineering design,
laboratory study’, (ed. Wang Xuguang), Proceedings of analysis and optimisation. He is currently a researcher at the
the 7th international symposium on rock fragmentation Swebrec, the Swedish Blasting Research Centre at Luleå
by blasting – Fragblast 7, Beijing, China, Metallurgical University of Technology (LUT). His research activities
Industry Press, 2002, 122–127. include detonation, fragmentation damage, blast design
26. D. THORNTON, S. KANCHIBOTLA and J. ESTERLE: ‘A optimisation, mine-to-mill and environmental problems due
fragmentation model to estimate run-of-mine to the blasting.
distribution of soft rock types’, Proceedings of the 27th Aleksandar Jankovic is currently Metso Minerals Process
Annual Conference on Explosives and Blasting Technology Asia Pacific's Manager of Development and
Technique, ISEE, Orlando, Florida, USA, 2001, 41–53. Process Engineering. He gained his Master of Technical
Science degree from the University of Belgrade in 1991 and
Authors his PhD from the University of Queensland in 1997. He then
worked for Mount Isa Mines as a project metallurgist before
Italo Onederra has over eight years' experience in the areas joining the JKMRC in 1999 to work on Mine-to-Mill
of rock breakage, excavation engineering and mining related projects such as Century, Cadia, Alumbrera, Mount
geomechanics, with particular expertise in the continuous Isa, Ernest Henry, Fimiston and the optimisation of SAG-
improvement of both underground and open pit drilling and Ball mill grinding circuits as well as tower mill modelling.

Mining Technology (Trans. Inst. Min. Metall. A) December 2004 Vol. 113 A247

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