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Characterising Rock Mass Properties for Fragmentation
Modelling
Andrew Scott and Italo Onederra Fragblast 11 - 25th August, 2015
What is it all about? • Current basis of blast design? • Current blast fragmentation models • The rock mass data on which these depend • Sources of data
Exploration Operating mines Other disciplines Emerging technologies
• Dealing with variability • Extending models for specific breakage
characteristics.
Basic blast design • Most blast design rules target “satisfactory”
blast performance!
• There are myriad qualitative blast design rules that influence the geometry of a design
• The “rock mass” has little prominence in most of these design rules – the ranges in suggested factors range from “Very Hard” to “Low Strength” rock.
Diameter Burden
Explosive Density
Rock Factor
B B
S
Free Face
Free Face
Stemming
Sub-drill
Burden Hole Length
Bench Height
Spacing (S) Large diameter ANFO S = (24 to 33) D (Very hard to low strength rocks) S/B = (1.14 to 1.18 ) B Large diameter Emulsion S = (34 to 45) D (Very hard to low strength rocks) S/B = (1.13 to 1.18 ) B Small diameter B = (38 to 51) D (Very hard to low strength rocks) S/B = (1.15 to 1.31 ) B Staggered pattern S = 1.15B Common S = (1 to 2) B S/B = 1.15 recommended for broad shallow blasts where the free face is the surface S/B > 1.15 is preferred where a free face can be utilised for relief
How to predict blast fragmentation • We need a model!
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
Mechanistic model parameters
Development of empirical fragmentation models
The Kuz-Ram development path
Some observations • The data provided for modelling must suit the
assumptions relied upon in the model • Avoid using nominal values for rock mass
properties to represent large volumes of rock • Acknowledge the variability found in rock mass
properties • Ensure an adequate description of rock mass
structure – ensure that the structures that control breakage have been included.
• Draw on data from other disciplines – geology, metallurgy, geotech
Exploration • Take advantage of guidance
from available surface geological mapping, aerial geophysics etc.
• Vast majority of useful data will come from drill core supplemented by chip drilling
• Drilling is controlled by resource geologists who also allow metallurgists and geotechnical engineers some access to the core – the blasting engineer is well down the pecking order!
Rock Strength • Dynamic properties are really needed but are not easy to
measure and we don’t have the design formulae to use them! • Static strength parameters are normally used in empirical
blasting models Unconfined Compressive Strength
– Often biased to high values – Limited statistical representation
Point Load Strength – Easy to measure but greater variability – Relates well to energy - breakage data
Field indices – Can vary in interpretation from person to person – Often represented as measured data in data bases
• Need to seek relationships between strength data and other rock mass properties (lithology, alteration, geophysical properties, etc) to extrapolate data beyond sample locations.
Structure • Ideally we want to know the “in-situ size
distribution” of the intact rock mass
• This is very complex!
• What does it mean to blast these materials?
• What is their RQD?
• What is their Fracture Frequency?
• What is their in-situ size distribution?
Presentation of data and statistics
Strength - Augite Basalt
0%
10%
20%
30%
40%
50%
< 25 25 - 49 50-74 75-99 100-149 >150
UCS MPa
Freq
uenc
y
The presentation of data needs to ensure that it will be interpreted correctly.
An average rock strength of 75 MPa will actually have a distribution of strengths.
The actual strength will vary with location (lithology, alteration etc) and may need to be represented on a spatial basis.
A range of strengths will result in a range of blasting results: • Most rock will blast like 75 MPa rock • 12% will blast like 125 MPa rock • 10% will blast like 20 MPa rock
Interpreting in-situ structure
0%
5%
10%
15%
20%
25%
30%
35%
40%
2 4 6 8 10 12 14 16 18 20 >20
Fracture Frequency
HMD HBM PH FR ABOVE
0%
10%
20%
30%
40%
50%
60%
70%
2 4 6 8 10 12 14 16 18 20 >20
Fracture Frequency
FT HMD HBM PO FR BELOW
0
5
10
15
20
25
0 50 100 150 200 250 300 350 400 450
Frac
ture
s pe
r met
re
Depth - m
135XC08 - Fracture Frequency
Data Acquisition • Data acquisition techniques are required that are:
Less dependent on personal effort Remote Capture variability as well as spot values
• Examples of emerging technologies for this purpose include: Blast hole drill monitoring Photogrammetry and laser based survey and mapping techniques. Down-hole and surface geophysics
Ramos, Hatherly and Montiero, ACFR, 2009
SMCS
Strata Characterisation While Drilling
Has been technically feasible for many years, but only now being used routinely in a few operations.
Remote Structural Mapping Systems work, but current developments focus on making the process less technically demanding in both the field and office.
Appropriate analytical tools are needed to interpret the data and present it in a suitable form for blast design.
Fine Breakage Behaviour • Rock breaks in distinctive patterns when the fragments are unaffected by
macro-structures • Michaux demonstrated self-similar behaviour between crushing, small
scale blasting and production blasting for the same rock
• Michaux argues that results from fine crushing tests can be used to extend fragmentation curves below 1 mm in size.
Michaux developed a crushing test procedure to characterise this fine breakage behaviour
Model extended to cover dust…
Fines from inherent clays
• Cerro Colorado mine in Chile had excessive fines in their copper heap leach
• Clay minerals were bound within the rock matrix and liberated with rock breakage
• “Dean David Index” (DDI) developed from a specific crushing test to quantify the clay generated during blasting
• DDI was incorporated into the fragmentation and crushing models to guide changes to practice to limit fines generation.
Conclusions
• Best fragmentation model is one formulated to specifically address the problem being studied
• Essential that the rock mass properties used are consistent with the underlying assumptions relied on by the model
• Rock mass data needs to be shared between disciplines • Important to adequately account for variability • All models need to be calibrated and checked for reality • Established models can be extended to account for properties or
mechanisms not usually addressed.