Post on 22-Jan-2018
TECHNICAL REPORT Control and Prediction of Blast Fragmentation
and its Impact on Comminution
JAMES DUNFORD 630024723
Abstract Blasting is a fundamental part of the comminution process in mining. Controlling and forecasting the fragmentation from a blast through design and modelling will help in the optimisation of the comminution circuit for any operation. Optimising the fragmentation and comminution processes is paramount to overall success of an operation.
Table of Contents Introduction ................................................................................................................................... 1
Section 1 – Bench blast theory ................................................................................................... 2
A. Geometrical controls ............................................................................................................ 2
B. Explosive properties .............................................................................................................. 2
C. Rock mass properties ........................................................................................................... 3
Section 2 – Comminution Theory .............................................................................................. 4
A. Three Laws of Comminution ................................................................................................. 4
B. Bonds Law, Workman and Eloranta Study ........................................................................... 4
Section 3 – Effect of varying geometric, explosive and time controls .................................. 5
A. VOD Explosive ..................................................................................................................... 5
B. Detonator choice and delay ................................................................................................. 5
C. Blast pattern ......................................................................................................................... 6
D. Bench Height ........................................................................................................................ 6
E. Bench Inclination .................................................................................................................. 6
F. Sub-Drill and Stemming ....................................................................................................... 6
G. Burden and Spacing ............................................................................................................. 6
Section 4 – Models for fragmentation prediction ..................................................................... 7
A. Kuz-Ram ............................................................................................................................... 7
B. Two component model ......................................................................................................... 8
C. Crushed zone model ............................................................................................................ 9
D. Model comparison .............................................................................................................. 10
E. TCM vs CZM ...................................................................................................................... 10
F. ROM ................................................................................................................................... 10
Section 5 –Case study ............................................................................................................... 11
A. KCGM .................................................................................................................................. 11
Conclusion .................................................................................................................................. 12
1 | P a g e
Figure 1: Bench blast geometry and
terminology [3]
Surface mining operations use benches for
slope stabilisation and haul roads. A simple
layout of the typical bench blast geometry
with terminology is shown in Figure 1
above. In bench blasting there a variety of
key factors that will impact on rock
breakage. Burden, spacing and hole
diameter are the main influences. With rock
type, explosive choice and detonator timings also having an impact.
Using the geometric design, the explosive
properties and the rock mass properties it
is possible, empirically, to predict
fragmentation from a blast. The report will
look at three fragmentation models and compare their benefits and limitations.
Figure 2: Radial crack formation (left) and
compressive stress waves (right) [4]
Introduction
Blasting, in all forms of mining, can
be considered as the first stage of
any comminution process. The aim
of blasting is to reduce the size of
rock mass material. Further
processing and size reduction are
achieved by comminution. In
principal all mines from metal to
industrial minerals and quarries use
blasting to fragment the rock mass.
The particle size from blasting will
determine the next stages of
production. Not all blasting practices
aim to reduce material to its smallest
size. Specifically, some rock blocks
are required to be larger size in
quarrying. On the other hand, metal
mining requires fine material for
optimising the mill and improving the liberation of the required mineral.
The scale of blasting in surface
mining is much greater than
underground resulting in a larger
mining rate for surface operations
compared to underground.
Underground mining is highly
selective and blasting usually follows
a special design in order to minimise
dilution. Surface mining is non-
selective and therefore all grades of ore are taken and dilution is high [2].
This report will focus predominately
on surface blast designs and
fragmentation prediction from
surface blasting. This is because
surface blast design has a greater
impact on the stage of comminution
because of its larger scale. A case
study has been selected for
discussion looking at optimising fragmentation for comminution.
2 | P a g e
Section 1 – Bench Blast Theory This section will briefly discuss the theory
of bench blast design. Key attention paid to
the geometrical controls, the explosive and
detonator choice and the impact of rock mass on design.
Blasting theory dictates that there are 3
principal stages of affecting the rock in a
blast. In the first stage high pressure upon
detonation expands the blast hole by
crushing the blast hole walls (Figure 2). In
the second stage compressive stress
waves emanate in a 360 degree arc from
the hole with a velocity equalling that of
sonic wave velocity in the rock. The
compressive waves reflect off a free face
creating tensile stresses in the burden. In a
correct design the tensile stress exceeds
the tensile strength of the rock resulting in
breakage (Figure 2). The third stage in the
blast results from the gas volume entering
the crack formations in the rock mass. The
volume of gas enters at such a high
pressure (Figure 3) that it expands the
cracks. With a correct calculation of burden
the rock will be thrown forward as a result. [4]
Figure 3: Gas penetration of crack formation
[4]
A. Geometrical Controls As shown in Figure 1 there are a number
of geometrical factors in bench blast design
that effect blast fragmentation. These are
all known as controllable variables as they
are empirically calculated in the design.
The most important is hole diameter. Blast
hole diameter is selected based on the
desired fragmentation. Larger diameters
offer better drilling economy but
consequently give increased burdens,
spacing’s and stemming resulting in larger
boulders. Large scale mines can have
holes up to 400mm. In UK surface
operations the most common drill hole size
is 110mm. The Burden is the space
between the hole and the free face. This is
calculated by using a multiplier for the type
of rock to be blasted in the range of 30-45,
and multiplying this number by the
diameter of the hole.
The spacing is the space between each
hole. This is calculated using a ratio factor
for the rock. Usually its 1 multiplied by the
burden but in heavily jointed rock this ratio
could be 1.25. As an example in a
limestone quarry for a 110mm hole
diameter the rock multiplier would be 37.
This gives a burden of 4.07 meters. In good
conditions the spacing would be equal to 1
multiplied by the burden resulting in 4.07
meter spacing. Sub drill is there to ensure
an even floor as its design is to remove the
toe of the bench, therefore it has no impact on fragmentation.
Stemming will have an impact on
fragmentation as it’s an area with no
column charge. Stemming is usually equal
to burden. The large the hole diameter
equals a larger burden and consequently a
larger stemming area. An area that has no
explosive so fragmentation would be poor in this region.
B. Explosive properties
An explosive is a substance (solid, liquid or
a mixture) that has the capability of
developing high pressures through the
3 | P a g e
formation of gases at high temperatures when a substantial stimulus is applied to it.
The choice of explosive depends on the
rock mass type and the desired
fragmentation for the rock mass.
Explosives have a variety of properties, the
key properties for blasting are; Velocity of
detonation (VOD), weight strength
(compared with ANFO), and explosive sensitivity.
VOD is the speed at which detonation
travels through and explosive. Weight
strength is the comparison between
strength of any weight explosive compared
with the same weight of Ammonium Nitrate
Fuel Oil (ANFO). Sensitivity is the required
input energy to get complete detonation reliability.
In surface mining the most common form of
explosive is ANFO either in liquid form or in
cartridge form for waterproofing. ANFO is
the cheapest bulk explosive. Bulk
emulsions and slurries are ANFO based
and have greater weight strengths and
VOD compared to ANFO. They are also
suited to wetter conditions. They are more
expensive but offer better fragmentation opportunities (See Section 3).
In the early history of mining, blasting was
conducted with black powder. Black
powder is an explosive that deflagrates
(<1000 m/s) rather than detonates (an explosive detonates with VOD >1000 m/s).
Black powder was a non-water proof
explosive and delays for drill holes were
initiated with safety fuses. Delays varied
with the length of safety fuse, this method
is very inefficient and unreliable. Fast
forward to more recent times and
explosives have become stronger in
comparative bulk strength. ANFO based
explosives detonate and require a
mechanical shock in order to do so. This is “kick” is provided by detonators.
Detonators for bulk explosives can come in
three forms. Electric with pyrotechnical
delay element utilising an electronic firing
mechanism. Shock tube (NONEL) with
pyrotechnical delay element and shock
firing mechanism coupled with UNIDET
delay action connectors. Finally electronic.
Electronic or programmable detonators
have no pyrotechnical delay element but
instead use a microchip to get precision
delay timings as low as 1ms. Detonators
are chosen on cost effectiveness and delay
precision. The effect of detonator timings
on fragmentation and further detonation theory are seen in section 3.
C. Rock mass properties
Blasting liberates rock blocks from the rock
mass structure whilst creating new
fractures within the intact material.
Describing blastability of a rock mass
requires the information of mechanical and
structural properties of the rock [7]. Blasting
will usually fragment the rock into fine and coarse sizes. (See section 5)
Rock mass properties such as uniaxial
compressive strength and density e.c.t.
contribute toward empirical calculation for
fragmentation prediction and geometrical blast design.
The mechanical properties of rock
influence the Blastability [7]. These can be
measured in lab testing but can be limited
in accuracy because of sample size.
Samples are usually taken from muck piles of blasted rock.
The structural properties of the rock mass
look at the properties such as jointing,
fracturing and roughness. These
measurements are taken empirically
through engineering judgement at the face [7].
Micro fracture networks within rock and
variations in grain size are important
factors in the comminution process. They
develop as a secondary unseen effect from
blasting. It is realistic to assume that blast
fragmentation distribution and micro
fracture networking from blasting will impact crushing and grinding processes [8].
4 | P a g e
Section 2: Comminution Theory Comminution is the process of reducing the
size of an object like rock. Principally
through crushing or grinding. Comminution
is responsible for 53% of a mines energy
consumption. Therefore optimising the
fragmentation form the blast to reduce
energy consumption in the mill is of great
importance to mining engineers [9].
Calculating the energy consumed in
comminution has been discussed for many
years and three laws and a general rule
have been established for varying particle
sizes. These are; Rittinger, Kick and Bond.
A. Three Laws of Comminution
Rittingers law (1867 & Equation 1)
specifies that the fragmentation work from
crushing or grinding is directly proportional
to the work done [10]. See Appendix for list of variables.
𝑊 = 𝐾 (1
𝑑−
1
𝐷) = 𝐾(𝑆𝑓 − 𝑆𝑖)
Equation 1
Kicks law (1885 & Equation 2) specifies
that the energy required is directly
proportional to the volume reduction of particles before and after crushing [10].
𝑊 = 𝐾. 𝐿𝑜𝑔 (𝐷80
𝑑80
)
Equation 2
Bonds Law (1952 & Equation 3) is the
most common method of calculating work
in crushing and grinding. It specifies that
the work consumed is proportional to new
crack lengths produced by fragmentation.
As developed cracks result in rock breakage [10].
𝑊 = 10𝑊𝑖 (1
√𝑑80
−1
√𝐷80
)
Equation 3
The summary chart shown below highlights
the work (KWh/t) against the dimension of a particle for each law.
Figure 4: Summary Chart [10]
B. Bonds Law, Workman and
Eloranta study
The primary benefit of Bonds equation is
the fact that the work index (Wi) has been
measured for most rock types. A study
conducted by Workman and Eloranta
highlighted an example of work indices for
stages of comminution for taconite ore. The
blast was conducted using ANFO and a
work index of 14.87 kWh/ton. The table
below shows the results of the study [11].
Table 1: Results from Workman and Eloranta study [10]
The study concluded that in energy cost
breakdown for fragmentation, blasting
accounted for 1% of the total whereas
grinding accounted for 77%. The study
showed that decreasing the feed size into
the primary crusher will decrease the
energy cost, hence the blasting stage is
vitally important for saving money in comminution stage.
5 | P a g e
Section 3: Effect of Varying
Geometric, Explosive and Time
controls The previous section shows that blasting
impacts on the energy consumption in the
crushing and grinding stages of
comminution. By varying the explosive
controls in the blast better fragmentation
can be achieved. “Chiappetta (1998)
summarised his extensive blasting experience in the following: [
For competent rock the factors affecting fragmentation are ranked in order: [11]
1. Specific charge
2. Explosive distribution
3. Explosive type
4. Delay timing 5. Joint system and orientation
In softer conditions the factors are ranked
as follows: [11]
1. Joint system and orientation
2. Explosive type
3. Specific charge
4. Explosive distribution 5. Delay timing”
Delay timings have an effect on
fragmentation but are predominately there to decrease the vibration from the blast.
A. VOD Explosive
The VOD of an explosive is linked to the
size of the blast hole diameter. ANFO is
more sensitive to diameter change than
emulsions. Lower VOD will result in less
energy transfer to surrounding rock
resulting in poor fragmentation. Therefore
high VOD emulsions are preferable to
ANFO. VOD and density influence the
pressure wave generated in the blast and
this wave influences fragmentation. ANFO
is a common explosive type used in
blasting because it’s cheaper the other bulk
explosives. Knowing VOD plays a large
role in fragmentation it’s important that
blast hole diameter is correctly chosen to
give the peak VOD for ANFO used. Factors
like vibration also play a part in the size of the blast hole. [11]
B. Detonator Choice and Delay
Electronic detonators have bought delay
timings down to within 1 millisecond. The
result is precision timings between holes.
Short delay periods produce more uniform
and finer fragmentation compared with longer half second delays.
Shock tube detonators and electronic
detonators rely on delay connectors or
pyrotechnical elements for delays. These
can be within 10 milliseconds but cannot be
as precise as electronic as the delay
element will always have some deviation
from its promised timing. Despite this they
are more common than electronic mainly because of cost.
The optimum delay between holes has
been researched and many put it at 3-6
milliseconds pre one meter of burden [12].
This optimum is shown to reduce increase
the distribution of fines in the muck pile.
The delay optimum is linked to the creation
of crack network that propagates from the
blast. When rock is blasted from a hole it
moves away from the area blasted. This
makes it less vulnerable to the
mechanisms of fragmentation in the blast.
Shorter delays negate this issue. However
delays that are shorter than the optimum
between burdens actually supress
fragmentation due to interference with the stress fracture network in the rock.
Optimising delays also depends on the
rock, weaker rock requires longer delays in
order limit the interference in the stress
network. A curve produced by Bergman
(1974) demonstrations the fragmentation
against delay timing for a blast in granite.
The test was single row and small scale not
large enough to test longer delays. The
model showed that as delay increased from
zero delay the “degree” of fragmentation
reaches its maximum value rapidly and
then attenuates off. The shorter delays
create the strong movement of rock and
6 | P a g e
depth dependant create good fragmentation.
C. Blast Pattern
Blast patterns are usually square or
rectangular in design. Staggered patterns can also be used. (See Figure 5)
(Square/Rectangular pattern)
(Staggered pattern)
Figure 5: Blast pattern variation
For fragmentation the optimum design is
staggered because the triangular pattern
allows better distribution of explosive
energy and for more margin on delay sequencing [13].
D. Bench Height
Bench height is a key parameter in blast
hole diameter and burden calculation. In
the UK quarries are limited to a 15m bench
height whereas metal mines are limited
only by the size of the excavator. The
bench height to burden ratio highlights the
fragmentation potential. If the ratio is 1 then
the fragmentation will be coarse and
blocky. A ratio between 3 and 5 is utilised
in most quarrying and mining operations.
E&JW Glendenning’s in the UK use a
burden to height ratio of 3.3 [14]. If the bench
height is to large then fragmentation will be
blocky because of increased drilling error in
blast hole and explosive consumption varies with increased depth [13].
E. Bench Inclination
Inclining the drill holes can give better
fragmentation as the blast energy covers a
larger area of rock mass and isn’t
dissipated into the air or base of the blast.
Inclination is also done for slope stability.
F. Sub drill and Stemming
Length of sub drill for surface operations is
a function of the burden value however in
most practices it’s roughly 1 to 1.5 meters
in length. It is used to create a clean
surface at the toe. If to large the blasted
material will create heavily fragmented rock
that will impact the next level of the
operation. Stemming has a larger impact on fragmentation.
Stemming is used to avoid the explosive
gas pressure wave from escaping out the
top of the hole forcing the energy to the
surrounding rock mass. It is commonly
made of 6-10mm aggregate. If the
stemming column at the top of the hole is
to large then blocky material will result from
the blast as no blast energy could reach the
material. If the stemming is too small the
energy will be forced out the top of the hole
and not the adjacent rock mass generating
fly rock and poor fragmentation. Stemming
should be equal to the burden but in weak
conditions 1.25 lots of the burden size
would be used. E&JW Glendenning’s use a
burden of 3.7m the same value as the
calculated burden for the hole diameter
chosen (110mm) [14].
G. Burden and Spacing
Like all the parameters mentioned the
choice of burden and spacing will be
empirically calculated based on hole
diameter and rock type. They can be varied
if the delay timings are accurate i.e. in an
electronic system. Choosing the optimum
burden and spacing is important for
fragmentation. If the burden is too small
then fly rock issue are created and material
is lost. If the burden is to large then the
resulting fragmentation will be blocky and
coarse due to resistance of gas pressure
penetration into the desired rock mass area.
Small spacing’s between holes will create
superficial crate breakage and excessive
crushing between holes. This has the
potential to cause blasts to break into
7 | P a g e
adjacent holes and create misfires.
Moreover the material will then be block in
some areas and may not be thrown forward
making the digability of the muck pile poor.
If the spacing is too large then the fracturing
between the holes will be poor creating
coarse blocks. [14]
Section 4: Models for Prediction
of Fragmentation The following section will highlight three
empirical methods of fragmentation
prediction. The standard Kuz-Ram model
and the JKMRC models of TCM and CZM.
The input parameters for modelling
fragmentation are geometrical design, the
explosive properties and the rock mass
properties [3]. Rock mass properties are
harder to obtain and really on engineering
judgement therefore models are
fundamentally limited in their accuracy by
this issue. Each model will only predict
sieve size and doesn’t consider the
weakening of material or the shape of the
particle, both properties are useful for
planning the comminution process.
Although this is a fundamental draw back,
the calculations and distribution curves are relatively simple and fast to obtain.
A. Kuz-Ram Model
A commonly used model based on the
average fragment size (X50) derived by
Kuznetsov in (1973), and a Rosin-Rammler distribution. [3]
The size distribution of fragmented rock is calculated using Equation 1.
𝑃(𝑥) = 100 (1 − exp (−𝑙𝑛2 (𝑋
𝑋50
)𝑛
))
Equation 4
P(x) = Percentage of material less than the size X (%)
n = uniformity index
X = size of material (m)
X50 = average fragment size (m)
Average fragment size is calculated in Equation 5.
𝑋50 = 𝐴 × (𝑉0
𝑄)
0.8
× 𝑄16 × (
𝐸
115)
1930
Equation 5
A = Rock factor
V0 = Volume of blasted rock (m3)
Q = charge weight (kg)
E = strength of explosive (% ANFO)
The rock factor, A, is used to modify the
average fragmentation based on the rock
type and blast direction. The rock factor is calculated by Equation 6. [3]
𝐴 = 0.06 × (𝑅𝑀𝐷 + 𝐽𝐹 + 𝑅𝐷𝐼 + 𝐻𝐹)
Equation 6
RMD = Rock Mass Description = 10
(powdery / friable), JF (if vertical joints) and 50 (if massive)
JF = Joint factor = JPS + JPA = Joint Plane Spacing + Joint Plane Angle
JPS = 10 (if vertical joint spacing, Sj < 0.1 m), 20 (if Sj < oversize) or 50 (if Sj >oversize)
JPA = 20 (if dip out of face), 30 (if strike is perpendicular to the face), or 40 (if dip into face)
RDI = Rock Density Influence = 0.025*ρ (kg/m3)-50
HF = Hardness Factor = Emodulus/3 (if Emodulus <50(GPa)) or σc (MPa)/5 (if Emodulus > 50 (GPa)) [3]
The uniformity index (n) is calculated using Equation 7. [3]
8 | P a g e
𝑛 = (2.2 − 14 × (𝐵
𝐷)) × (1 − (
𝑊
𝐵)) × √(
1 +𝑆𝐵
2)
× (0.1 + 𝑎𝑏𝑠 (𝐵𝐶𝐿 − 𝐶𝐶𝐿
𝐿))
0.1
× (𝐿
𝐻)
Equation 7
B = burden (m),
S = spacing (m),
D = charge diameter (mm),
W = standard deviation of drilling accuracy (m),
BCL = bottom charge length (m),
CCL = column charge length (m),
H = bench height (m) and
L = Total charge length (m).
“The uniformity index, n, determines the
shape of the fragmentation curve. High
values on n gives uniform sizing i.e. small
amount of fines and oversized material, normally n ranges from 0.8-2.2.” [3]
Table 2: Effect of blasting parameters on n [3]
B. Two Component Model (TCM) This model is based upon the Kuz-Ram
model. Studies have demonstrated that
Kuz-Ram underestimates the fines part of
fragment distribution [3]. Fragmentation
occurs by more than one mechanism as
specified in the blasting theory. Therefore
when modelling fragmentation from
blasting it must be concluded that more
than one distribution should be accounted
for. It can be considered that adjacent to
the blast hole fragmentation occurs through
compressive shear failure resulting in fine
distribution. Whereas further from the blast
hole the rock is subject to tensile failure and
the fragmentation is coarser. [3] A rough
fragmentation curve demonstrates these
two distributions below.
Figure 6: Fragment size distribution
modelling two distributions.
Calculations for TCM are similar to Kuz-
Ram with the difference being two
component function for modelling coarse
and fine fragmentation distributions. A
breakdown of the components to the
following equations can be found in the Appendix.
The component of shear compression (Fc)
is calculated by using the area of the
crushed zone adjacent to the blast hole and
dividing it by the total blast area. (See Equation 8)
Parameter N increases as parameter…
Burden/Hole Decreases
Drilling accuracy Increases
Charge Length/Bench Height Increases
Spacing/Burden Increases
Staggered Pattern Increases by 10%
9 | P a g e
𝐹𝑐 = 𝑟𝑐
2 × 𝜋
𝐵 × 𝑆
Equation 8
The overall equation for the TCM model is shown below.
𝑝(𝑥) = 100 (1 − (1 − 𝐹𝑐 ) exp (−𝑙𝑛2(𝑥
𝑎)
𝑏
)
− 𝐹𝑐 exp (−𝑙𝑛2(𝑥
𝑐)
𝑑
))
Equation 9
C. Crushed Zone Model (CZM)
CZM is very similar to TCM by utilising two
functions to describe the total
fragmentation distribution. The difference
lies in the fact that TCM uses two
distributions simultaneously. Whereas
CZM uses one distribution for coarse and
one for fine. These two distributions join at
a character size known as Xc. This is
dependent on rock mass property. (See Figure #) [3]
Figure 7: Fines and coarse size distribution for
the CZM
Parameters for the following equations are
found labelled in the appendix. These
equations are used to work out the coarse
and fine distribution separately before
plotting them on a graph similar to Figure
7.
𝑃(𝑥) = 100(1 − exp ( (1 − 𝑃(𝑥𝑐))
× (𝑥
𝑥𝑐
)𝑛𝑐𝑜𝑎𝑟𝑠𝑒
))
Equation 6: Coarse particle distribution
𝑛𝑐𝑜𝑎𝑟𝑠𝑒 = (2.2 − 14 × (𝐵
𝐷)) × √(
1 +𝑆𝐵
2)
× (𝐿
𝐻)
Equation 10: Uniformity index for coarse
particle distribution
“The fines part of the fragment size
distribution originates from a crushing zone
that is described by a cylinder around the
explosives in the blast holes. The radius of
the crushed zone is calculated as the
distance from the borehole to the point
where the radial stress exceeds the
compressive strength, σc, of the rock. The
stress, σx, at distance x, around the blast holes” [3]
𝜎𝑥 = 𝑃𝑑 × (𝑟
𝑥)
2
Equation 11: Stress calculation
𝑟𝑐 = 𝑟 × √𝑃𝑑
𝜎𝑐
Equation 12: Crushed zone radius
𝑃𝑑 = 𝜌𝑒 ×𝐶2
𝑑
4
Equation 13: Detonation pressure
𝐹𝑐 =𝑉𝑜𝑙𝑢𝑚𝑒 𝐶𝑟𝑢𝑠ℎ𝑒𝑑
𝑉𝑜𝑙𝑢𝑚𝑒 𝑜𝑓 𝐵𝑙𝑎𝑠𝑡
Equation 14: Fraction of crushed material
The fine particle distribution is calculated using the equation below.
10 | P a g e
𝑃(𝑥) = 100 (1 − exp (ln(1
− 𝑃(𝑋𝑐 )) (𝑋
𝑋𝑐
)𝑛𝑓𝑖𝑛𝑒
))
Equation 15: Fine particle distribution
𝑛𝑓𝑖𝑛𝑒 =
ln (𝑙𝑛(1 − 𝐹𝑐 )
𝑙𝑛(1 − 𝑃(𝑋𝑐 )))
ln (1𝑋𝑐
)
Equation 16: Uniformity index for fine
particle distribution
This equation above is calculated by
rearranging Equation 15 and applying
known fractions of crushed material with size of 1mm. [3]
D. Model Comparison
Kuz-Ram, TCM and CZM are all viable
models for fragmentation prediction. Kuz-
ram underestimates fine particle
distribution in the fragmented blast. Fine
particles are a significant feature in the
decision behind comminution processes.
Underestimation of their quantity will result
in the wrong selection of grinding
equipment or grinding media this could
lead to inefficient milling of the ore.
Overall each model requires significant
input parameters. The required lab and
field tests make them unsuitable for daily
blast planning but for certain individual
blasts such as blasts in weaker ground,
they can be utilised to provide information
to aid in increasing efficiencies in the milling.
Table 3 shows the input parameters
needed for each model. Availability
corresponds to the handiness of the
parameter to be measured on site or in a
laboratory. Good corresponds to
measurable on site, fair requires surveying and poor requires laboratory testing. [3]
E. Case study Comparison TCM vs
CZM
A comparison test was conducted in Hall
and Brunton (2001) focusing on TCM and
CZM modelling and comparing those
methods to run-of-mine (ROM) image
analysis with a split system [3]. Data from 14
blasts in rock strength 81-161MPa (UCS)
was collated and the following conclusions were found:[3]
The CZM generally provides a
better estimation of ROM measured
by Split for the 14 blasts.
Both the TCM and CZM generally
estimate a coarser fragmentation
than that measured by the Split
system.
The CZM generally varies less from
the Split results in the fine to
intermediate size range, 1-100 mm.
The CZM requires more easily
obtained input parameters than the TCM does.
F. ROM
Run of mine (ROM) blasted muck pile that
will be put into the mill feed. Images are
used to quantify the blasted material to aid
in optimising the feed Figure 8 shows
comparison of ROM measure, JKMRC and
Kuz-Ram. It shows JKMRC is closer to the measured ROM.
Figure 8: ROM measured vs JKMRC and Kuz-Ram
11 | P a g e
Section 5: Optimisation of
Fragmentation for a
Comminution Circuit
A. Case Study – KCGM [15]
With KCGM’s ore type JKMRC method for
fragmentation prediction was chosen to
estimate ROM size distributions using a set
blast specification. This is shown in Table 4.
Burden (B) 5m
Spacing (S) 5.8m
Hole Depth (L) 11.3m
Hole Diameter (D)
165mm
Column Charge Length (CCL)
7.2m
Explosive Energan 2620
Density 1100 Kg/m3
VOD 4550 ms-1
Powder Factor 0.58 Kg/m3
Table 4: Blast specifications for Case study [15]
The ROM predictions were then compared
to image analysis from two trucks with blasted muck.
Figure 9: ROM Prediction vs Image analysis [15]
The predicted ROM was then used to
predict the SAG mill performance to
validate the model. The results showed that
the model was within 90% of the actual for
F80 (mm) and over predicted for the other
SAG mill variables. After validation the
model was then tested on three separate blast designs shown in Table 5.
Table 3: Availability of input parameters for fragmentation models. [3]
12 | P a g e
Table 5: Blast designs for ROM model [15]
Figure 10: ROM graph prediction for blast designs [15]
The case study with the model was able to
predict the SAG mill processing and the
results were that design 2 for the blast,
improved throughput, however despite a
50% increase in powder factor Design 3
also has an increase in throughput but not
as great as design 2. Both blast design
generate more sub 10mm material that
doesn’t require grinding further. It’s also
shown in the simulation that the particle
size of 50mm and greater is produced in
lower quantity and much lower distribution
of 100mm+. Oversize in general is reduced in quantity. [15]
Conclusion The report shows the fragmentation from
blasting is affected by a variety of factors.
Currently engineers are able to quantify the
variables and use them to model and
predict the fragmentation from a blast.
Combining predictions with Bonds law it is
possible to calculate the energy required in
a comminution circuit. With the KCGM case
study shown in Section 5 the modified
Kuz-Ram or JKMRC models are valid for
fragmentation prediction. Results have
shown that the predictions were within a
15% accuracy. From this model and
quantified data engineers are now able to
predict how changes in blast design effect
not only fragmentation but the energy
required for a comminution set up. This
information will help engineers design a
more efficient mill system that is tailored to
the fragmentation produced. Alternatively
tailoring blasts for the comminution circuit.
The benefit comes down to cost savings
through efficiency. Hole Diameter is one of
the most important factors when controlling
the blast. Hole diameter ultimately controls
burden and spacing. Section 3 shows that
varying spacing’s and burdens has a large
effect on fragmentation size. The case
study in Section 5 showed that the powder
factor wasn’t a key driver towards smaller
fragmentation. This is true for all designs
with smaller burdens and spacing’s
because too much explosive can create
crush zones around other holes limiting the
propagation of the pressure waves. VOD
has the greatest impact as shown in
Section 3. Section 3 highlights that a lot of
variables can have significant impact on
fragmentation. However it’s important to
note that gaining the optimum
fragmentation may result in a number of
other issues. Increased noise levels and
vibrations may result from choosing a
stronger explosive. Decrease in drilling
rate may occur from staggering holes.
Therefore in conclusion optimising
fragmentation may impact other aspects of
blasting process and for the best results these should be taken into account
Hole Dia mm
Design 1 2 3
Burden (B) (m)
5 5 4
Spacing (S) (m)
5.8 5.8 5
Hole Depth (L) (m)
11.3 11.3 11.3
Explosive HANFO Emulsion Emulsion
Density (Kg/m3)
1100 1250 1250
VOD (m/s) 4550 6000 6000
Powder Factor (Kg/m3)
0.58 0.66 0.96
13 | P a g e
References [1]: Swebrec, (2015). Swedish Blasting Research Centre. [image] Available at: http://www.ltu.se/centres/swebrec?l=en
[Accessed 3 Mar. 2016].
[2]: Dunbar, W. (2016). Basics of Mining and Mineral processing.
[3]: P.Bergman (2005) Optimisation of Fragmentation and Comminution at Boliden Mineral, Aitik Operation. (Published PHD
Thesis) Luleå University of Technology, Department of Civil and Environmental Engineering, Division of Rock Engineering
[4]: Wetheralt, Dr. (2016). Quarry design: Surface Design 4.
[5]: Wetheralt, Dr. (2016). Quarry design: Surface Design 1.
[6]: Cardu, M. and Seccatore, J. (2014). Evidences of the influence of detonation sequence on rock fragmentation by blasting.
Part 1. Ouro Preto: REM, pp.337-341.
[7]: Kanchibotla, S., Valery, W. and Morrell, S. (n.d.). Modelling fines in b last fragmentation and its impact on comminution. 1st
ed. [ebook] Queensland: Julius Kruttschnitt, pp.1-20. Availab le at:
http://www.metso.com/miningandconstruction/mct_service.nsf/WebWID/WTB-120105-22576-A523A/$File/009.pdf [Accessed
15 Mar. 2016].
[8]: Workman, L. and Eloranta, J. (n.d.). The Effects of Blasting on crushing and Grinding Efficency and Energy consumption .
1st ed. [ebook] pp.1-10. Availab le at:
http://www.elorantaassoc.com/download/Papers/E&A_Effects_of_Blasting_on_Crushing_and_Grinding_Eff iciency_and_Energy
_Consumption.pdf [Accessed 15 Mar. 2016].
[9]: Pascoe, R. (2015). Mine to Mill.
[10]: Thecementgrindingoffice.com. (2016). Comminution and Laws of Comminution. [online] Available at:
http://www.thecementgrindingoffice.com/lawsofcomminution.html [Accessed 16 Mar. 2016].
[11]: Ouchterlony, F. (2003). Influence of b lasting on the size distribution and properties of muckpile fragments, a state -of-the-
art reviews. 1st ed. Swebrec: Lulea University of Technology, pp.5-60.
[12]: Cunningham, C. (2005). The Kuz-Ram fragmentation model 20 years on. 1st ed. Modderfontein: African Explosives
Limited, pp.205-206.
[13]: Arshad Rajpot, M. (2009). The Effect of Fragmentation Specification on Blasting Cost. Masters of Science (Engineering). Queens University Ontario.
[14]: Gibbs, N. (2015). Blasting Specifications.
[15]: Morrell, S., Kanchibotla, S., Valery, W. and O'Loughlin, P. (n.d.). Exploring the Effect of Blast design on SAG Mill Throughput at KCGM. 1st ed. KCGM, pp.1-16.
14 | P a g e
Appendix Parameter Symbol Parameter
P(x) Percentage of material less than
the size X (%)
x size of material (m)/ sieve size/ distance from
blast hole
Fc part of rock that fails by shear
compression
a mean fragment size in tensile failure region
b uniformity coefficient in tensile failure
region
c mean fragment size in
compressive failure region
d uniformity coefficient in
compressive failure region
rc crushed zone
radius (m)
B burden (m)
S Spacing (m).
P(xc) Percent passing at characteristic
size, xc, (%)
xc characteristic size (m)
ρe density of
explosives (kg/m3)
Cd Velocity of detonation (m/s).
Pd detonation
pressure
r radius