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