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Characterising the Blasting Properties of Iron Ore
Andrew ScottScott Mine Consulting Services Pty Ltd
14th July, 2015
What is it all about?
• How to predict blast fragmentation• The role of rock mass properties
– in blast design– in fragmentation modelling
• What is different about iron ore?• Blasting properties of iron ore• Treating iron ore as a mixture• Sources of data• Greenfield case study.
• Why predict blast fragmentation?
How are blasts designed?
• Early blast design rules targeted “satisfactory” blast performance, including fragmentation
• There are myriad qualitative blast design rules that influence the geometry of a design
Diameter Burden
Explosive Density
Rock Factor
B B
S
FreeFace
FreeFace
Stemming
Sub-drill
BurdenHoleLength
BenchHeight
• Production blasts are usually designed as simple variants of the previous blast with changes made on a qualitative basis.
• The “rock mass” has little prominence in most of these design rules
How are blasts designed?
• Early blast design rules targeted “satisfactory” blast performance, including fragmentation
• There are myriad qualitative blast design rules that influence the geometry of a design
Diameter Burden
Explosive Density
Rock Factor
B B
S
FreeFace
FreeFace
Stemming
Sub-drill
BurdenHoleLength
BenchHeight
• Production blasts are usually designed as simple variants of the previous blast with changes made on a qualitative basis.
• The “rock mass” has little prominence in most of these design rules
How to predict blast fragmentation
• A model is a quantitative framework that presents a simplified “version of reality” that allows the relationships between “cause” and “effect” to be understood
• Two development paths– An empirical or engineering approach– A mechanistic or fundamental approach
• We need a model!
Mechanistic approaches
• Fracture mechanics, hydro‐dynamics, physics, chemistry, …..sophistry…..
• Data describing dynamic rock behavior requires sophisticated tests
• Computing requirements are intensive and it is not yet possible to routinely model practical field problems using these tools.
Onederra et al (2010)
• Attempt to simulate the dynamic fracture processes
A successful example ‐ the Kuz‐Ram Model
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1 . ∗.
Rock Factor
Mean Fragment Size
Charge Weight Powder Factor
Relative Explosive Strength
Rosin Rammler Equation
The blasting properties of a rock mass• Properties affecting “blastability”
– Strength – how difficult is it to break the rock?
– Density – relationship between volume and mass.
– Structure – how broken is it already?– Stiffness, porosity, energy‐breakage relationships, moisture content, etc, etc
• Generally combined into an “index” or “rock factor”
0.0
0.2
0.4
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0.8
1.0
1.2
0 50 100 150 200 250 300
Stre
ngth
Fac
tor
Unconfined Compressive Strength - MPa
Strength
0.60
0.70
0.80
0.90
1.00
1.10
0 10 20 30 40 50 60
Stru
ctur
e Fa
ctor
Fractures per metre
Structure
0.60
0.70
0.80
0.90
1.00
1.10
1.20
1.30
1.40
0 1 2 3 4 5
Dens
ity F
acto
r
Density t/bcm
Density11.5 ∗ ∗ ∗ 1
What is different about Iron Ore?• Traditional blasting research has focused on hard, competent rock more like magnetites than traditional WA iron ores
• These ores are highly variable in terms of strength, structure and density – exactly the properties that affect blasting performance!
• This variability is not just between types, but can also occur within a mine bench!
What is different about Iron Ore?• Traditional blasting research has focused on hard, competent rock more like magnetites than traditional WA iron ores
• These ores are highly variable in terms of strength, structure and density –exactly the properties that affect blasting performance!
• This variability is not just between types, but can also occur within a mine bench!
Blasting Properties of Iron Ores
Type Strength (MPa)
Fracture Frequency
Densityt/bcm Rock Factor
Magnetite 180 2 3.5 10.1
Massive Haematite 150 2 3.4 9.2
Blocky Haematite 130 4 3.2 7.9
Banded Iron 110 10 3 6.5
Haematite / Goethite 70 5 3.1 5.4
Goethite / Limonite 25 20 2.9 1.9
Treated as a single species
• 12 m bench, 251 mm dia. blast holes• 7.0 x 7.9 m pattern• Heavy ANFO explosive• 0.73 kg/bcm powder factor
If fired with a single blast design:
Treated as a mixture
• A host matrix or continuous phase• A “hard” component• A proportion of in‐situ fines
Examination suggests that many ores are made up of separate components or “mixtures”. It is possible to identify:
It is possible to identify these components in core and allocate blasting properties to each. In the field the properties of the individual components do not appear to change significantly within the one ore type, but their proportion may change significantly.
Mixtures Blocky Haematite Matrix Hards Fines Proportion 47.5% 47.5% 5% Density 3.0 3.2 Strength 40 120 Fracture Frequency 5 3 ROM Size Boulders X80 X50 Fines Previous Analysis 2.5 573 mm 213 mm 12% Component Model 2.5 470 mm 130 mm 23%
Haematite / Goethite Matrix Hards Fines Proportion 30% 60% 10% Density 2.9 3.0 Strength 20 60 Fracture Frequency 10 5 ROM Size Boulders X80 X50 Fines Previous Analysis 1.3 460 mm 174 mm 17% Component Model 0.6 360 mm 74 mm 33%
Goethite / Limonite Matrix Hards Fines Proportion 52.2% 32.5% 15% Density 3.0 3.2 Strength 20 30 Fracture Frequency 20 10 ROM Size Boulders X80 X50 Fines Previous Analysis 0 193 mm 53 mm 32% Component Model 0 190 mm 30 mm 44%
0
100
200
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700
Heamatite Heam / Geot Geot / Limon
Millim
etres
X80
Single
Mixture
0
50
100
150
200
250
Heamatite Heam / Geot Geot / Limon
Millim
etres
X50
Single
Mixture
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Heamatite Heam / Geot Geot / Limon
Fines
Single
Mixture
Sources of Data – Drill Core
• Strength• indices• UCS / stiffness• PLS• Sonic velocities• Breakage parameters
• Structure• RQD• FF• Geotechnical logging
• Density• Intact• Porosity
Sources of Data – Active Pits
Ramos, Hatherly and Montiero, ACFR, 2009
Face Sampling and Mapping Logging Drill Cuttings
Monitor Drill Performance
Surface and down hole geophysics
Performance in the adjacent block and updated geological models
Practical Example – Greenfield Site
Form Weathering Proportion Strength MPa
Fracture Frequency
Density (t/bcm)
Massive Fresh 14% 12 2 2.67 Blocky Fresh 58% 8 5 2.67 Broken 28% 4 15 2.67
Core from a 12 m zone from a channel iron deposit
Conclusions
• Some quite useful blasting models exist• All models require appropriate data if they are to generate useful predictions
• Most iron ores occur as complex mixtures of lithologies and properties• The components of these mixtures are often of consistent character within a blasting domain, but vary in their relative proportions
• The blasting characteristics of each component of the mixture can be quantified• The overall fragmentation result can be generated from the weighted average of the fragmentation achieved for each component.
• Automated data collection, blast design and field implementation remains an alluring challenge!