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TRANSCRIPT
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Incorporation of a Fractal
Breakage Mode into the BrokenRock ModelDosti Dihalu and Bas Geelhoed
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Purpose of this presentation
To investigate how the variance changes withparticle size reduction (comminution) Broken Rock Model (Minnit 2007)
the breakage pattern of a particle is regular, thefragments will all have the same size and weight
Here proposed: Fractal Broken Rock Model
the breakage pattern of a particle is a fractal, thefragments will have unequal sizes and weights
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Outline
1. Introduction1a. Sampling
1b. Theory of Sampling (TOS)
1c. Developments in TOS
2. Methodology: FBRM
3. Worked-out example4. Future Work
5. Conclusions
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1. Introduction
1a. Sampling1b. Theory of Sampling (TOS)
1c. Developments in TOS
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1. IntroductionVariance Estimator
2 2
2 21
3
1( ) (A )
f (B )
(C )
ba tc h N
i i b a tch
ib a tch b a tch
b
qV m c c
q c M
g cD
M
K D
M
V = the relative varianceq = the inclusion probability of each particlecbatch = the concentration of property of interest in the population
Mbatch = the (total) mass (or weight) of the populationm i = the mass of the i-th particle in the populationc i = the concentration of property of interest in the i-th particle ofthe populationf = shape factor (unitless quantity)g = size range factor (unitless quantity)
= the liberation factor (unitless quantity)c = the mineralogical factor (specified in the same units asdensity, e.g. g/cm 3 or kg/m 3)
D = nominal size dimension of the particle (specified in units oflength)M = mass of the sample (specified in units of mass)K = fg cD 3-bb = an exponent that can be selected freely, but in practice willbe set to a value that describes how the variance predictionchanges with D
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2. Methodology: FBRM (A)
(B)
(C)
(D)
Model yields 2 N fragmentsof varying particle mass m i
A. particle undergoes N breaking stagesB. particle is broken infragments by generating arandom number (r 0) between 0and M 0C. 2 new fragments (mass M 0,1= r 0 ,mass M 0,2 = M0-M0,1
D. each of the 2 fragments isbroken (breakage point offragment M 0,i = r 0,i ) in fourfragments of mass M 0,1,1 , M0,1,2 ,M0,2,1 , and M 0,2,2
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2. Methodology: FBRM Program
INPUTParticle massParticle concentrationPurity of inclusionNumber of breakinggenerationsMode (BRM/FBRM)
OUTPUT
Fragment number Fragment massFragment concentration
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3. Worked-Out Example
(step 1) population A: 15 particles (c 1, m 1) and 15 others(c 2, m 2)(step 2) population B by breaking population A according to FBRM(step 3) Calculate sampling variance of population B ( Gys formula).(step 4) Calculate for each particle i of population B D i and D.(step 5) Repeat steps 2, 3, and 4 for varying breaking generations N(step 6) Plot the Var(FSE) vs D and deduce the K and b value graphically .
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3. Worked-Out Example-Concentration
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3. Worked-out example
Particlenumber
Particle mass Particleconcentration
Purity ofinclusion
1-15 50 20 0.99
16-30 50 5 0.99
Starting population:
D indicates the 95 th percentile value ofthe total collection of obtained D is (Gy, 1979).
In this experiment, the maximum number of breaking generations (N max) was set to N max=10.
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LOG(VAR(FSE)) = 0.88 * LOG(D) - 3.53
-4
-3,8
-3,6
-3,4
-3,2
-3
-2,8
-0,3 -0,2 -0,1 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7
L O G ( V a r (
F S E ) )
LOG(D)
3. Worked-out example-Variance vs Diameter
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3. Worked-out example-Interpretation of Results
It can be concluded that - at least in thisexperiment- either the parameter b, or theparameter K, or both b and K at the sametime, depend on the particle size D.
Based on this graph, the best choice ofparameter b (that provides the best fit) is thevalue of b=0.88 2.5 (see also Franois-Bongaron & Gy, 2002)
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4. Future Work Using the FBRM to investigate how the parameters f,
g, , and c from Gys theory change with D (Equation1B).
Upscaling the one-dimensional fractal breakage
model to a three-dimensional fractal breakagemodel. Implementing more realistic particle concentration
profiles in addition to the step function that is usedhere.
Implementing a more realistic way of assigning adiameter (D i) to each output fragment.
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