This is an example of a formal lab report on Interference and Diffraction done for my Physics class. This document demonstrates my ability to technically report findings from experiments.
This is an example of a formal lab report on Interference and Diffraction done for my Physics class. This document demonstrates my ability to technically report findings from experiments.
Educating, connecting, networking
This way MobileDiagnosis Project is acting by education and connection in a global network the rural isolated communities, for permit rural development, and for improve locally,the local work-force. The students trained with MobileDiagnosis® method,will be future trainers for their community, without having to leave their community anymore
We moeten het begrip innovatie terug renoveren. Innovatie is niets meer of minder dan de som van creativiteit plus ondernemerschap. Die creativiteit kan vanuit de wetenschappelijke of technologische hoek komen, maar even goed uit een business idee of maatschappelijke hoek alsook uit de creativiteit die ingebakken zit in de creatieve sectoren.
We hebben dan ook renaissance mensen nodig die op elk van die drie domeinen kunnen meespelen of toch minstens meepraten: technologie - business - creativiteit
Determination of undrained shear strength of cohesive soil using lab vane shear test.
1. The formula for shear strength is based on following assumptions:
● Shearing Strength in the Horizontal and Vertical directions are the same.
● At the peak value, Shear Strength is equally mobilized at the end surface as well as at the center,
● The shear surface is cylindrical and has a diameter equal to the diameter of the vane.
2. The test gives the undrained strength of the soil. The undisturbed and remolded strength obtained are also useful for evaluating the sensitivity of soil. The data acquired from vane shear test can be used to determine: Undrained shear strength, Evaluate rapid loading strength for total stress analysis, Sensitivity of soil to disturbance, Analysis of stability problems with embankment on soft ground.
3. With increase in water content undrained shear strength decreases for given soil sample.
4. It is a quick test so it can be assumed as an undrained test.
Educating, connecting, networking
This way MobileDiagnosis Project is acting by education and connection in a global network the rural isolated communities, for permit rural development, and for improve locally,the local work-force. The students trained with MobileDiagnosis® method,will be future trainers for their community, without having to leave their community anymore
We moeten het begrip innovatie terug renoveren. Innovatie is niets meer of minder dan de som van creativiteit plus ondernemerschap. Die creativiteit kan vanuit de wetenschappelijke of technologische hoek komen, maar even goed uit een business idee of maatschappelijke hoek alsook uit de creativiteit die ingebakken zit in de creatieve sectoren.
We hebben dan ook renaissance mensen nodig die op elk van die drie domeinen kunnen meespelen of toch minstens meepraten: technologie - business - creativiteit
Determination of undrained shear strength of cohesive soil using lab vane shear test.
1. The formula for shear strength is based on following assumptions:
● Shearing Strength in the Horizontal and Vertical directions are the same.
● At the peak value, Shear Strength is equally mobilized at the end surface as well as at the center,
● The shear surface is cylindrical and has a diameter equal to the diameter of the vane.
2. The test gives the undrained strength of the soil. The undisturbed and remolded strength obtained are also useful for evaluating the sensitivity of soil. The data acquired from vane shear test can be used to determine: Undrained shear strength, Evaluate rapid loading strength for total stress analysis, Sensitivity of soil to disturbance, Analysis of stability problems with embankment on soft ground.
3. With increase in water content undrained shear strength decreases for given soil sample.
4. It is a quick test so it can be assumed as an undrained test.
Determination of undrained shear strength of cohesive soil using lab vane shear test.
1. The formula for shear strength is based on following assumptions:
● Shearing Strength in the Horizontal and Vertical directions are the same.
● At the peak value, Shear Strength is equally mobilized at the end surface as well as at the center,
● The shear surface is cylindrical and has a diameter equal to the diameter of the vane.
2. The test gives the undrained strength of the soil. The undisturbed and remolded strength obtained are also useful for evaluating the sensitivity of soil. The data acquired from vane shear test can be used to determine: Undrained shear strength, Evaluate rapid loading strength for total stress analysis, Sensitivity of soil to disturbance, Analysis of stability problems with embankment on soft ground.
3. With increase in water content undrained shear strength decreases for given soil sample.
4. It is a quick test so it can be assumed as an undrained test.
Accelerometers
Accelerometers are devices that produce voltage signals proportional to the acceleration experienced. There are several techniques for converting acceleration to an electrical signal. The most general technique is described first and more recent techniques will be considered later.
This presentation will cover the basics and differences between self-contained and transformer or instrument rated meter sites. Also discussed are transformer rated meter forms, test switches and CT's, Blondel's Theorem and why this matters to metering, meter accuracy testing in the field, checking the health of your CT's and PT's, and Site Verification (and not just meter testing).
Undertand requirements of normality in ANSI/ASQ Z1.9 and how that affects analysis of meter test data.
Review typical meter test data distributors and how to determine if meter test data is normal
Introduction to working with non-normal data
Presentatie door Pooyan Ghasemi en Mario Martinelli, Deltares, op de Geo Klantendag 2018, tijdens de Deltares Software Dagen - Editie 2018. Donderdag, 7 juni 2018, Delft.
Similar to The Affect Of Radiometric Truck Discrimination On Reconciliation (20)
The Affect Of Radiometric Truck Discrimination On Reconciliation
1. The Aff t f R di
Th Affect of Radiometric T
t i Truckk
Discrimination on
Reconciliation
J Carpenter, S Hackett, N Anderson
International Uranium Conference
Perth, 2011
XstractGroup.com
Xstract - Excellence from the Outset
ENVIRONMENT GEOLOGY MINING PROCESSING VALUATION RISK TECHNOLOGIES
2. Introduction
• The intention of this
presentation is to:
– Di
Discuss th i
the importance
t
of sample support to
grade control
– Demonstrate some
methods that can be
used for “change of
change
support”
3. What is change of support?
• Support is another name for volume
• The most obvious support change in a mining operation is the
difference in support between the block model used for planning
and the truck volumes that are actually mined
Planning using a Block Model... ...mining using Trucks
4. Mining is a selection process
• Mining is a selection process;
– Define a cutoff
– Using this criterion, select material above the cutoff and send it
criterion
to the mill, and
– Send material below the cutoff to the waste stockpile.
• In
I some open cut uranium mines, radiometric truck
t i i di t i t k
discriminators are used to sort each truckload leaving the
pit
• This creates a situation where “Perfect Selection” may be
assumed
5. Why is support important?
• Example:
100 tonne
blocks;
1600 0.35 % Cutoff
tonnes at
0.4%
400 tonne
blocks;
1600 0.35 % Cutoff
tonnes at
0.4%
6. Why is support important?
• The outcome of
applying the selection
criteria (a cutoff of
0.35%) has a
pronounced effect on
the mined grade and
tonnages
• Fewer tonnes,
higher grade
7. Real Data
• Some real data comes from ERA’s
Ranger #3 Uranium mine, located
approximately 250km east of
Darwin, Northern Territory, Australia
at latitude 120 41’ S, longitude 1320
55’
• Ranger 1 Anomaly 3 (colloquially
g y ( q y
known as Ranger #3) is situated in
Early Proterozoic sediments of the
South Alligator Group
g p
Table adapted from Kendall (1990)
8. Real Data
Large blocks are the
block model
Small blocks
are trucks
9. Global Results
• The results show that the estimate of what will be mined is
very close to what was actually mined
• This is an excellent outcome:
Blocks: 8.08 million tonnes at 0.043 % U3O8
Trucks: 8.02 million tonnes at 0.042 % U3O8
10. Support and selection criteria
• However, when we apply a cutoff grade of 0.12% U3O8 we
find that there is a deviation away from what the block
model has predicted
p
Blocks: 803,120 tonnes at 0.232% U3O8
Trucks: 774,800 tonnes at 0.278% U3O8
• Outcome: Fewer tonnes, higher grade
11. Predicting the tonnes and grade
• Before a new area is mined it would be highly desirable to
predict the tonnes and grade that will be mined on the truck
scale
• How do we predict the tonnes and grade of material on a
truck support above a cutoff grade?
t k t b t ff d ?
12. How to predict the tonnes and grade
• We can use Geostatistics
• I will demonstrate 2 methods:
– Affine Correction
– Conditional Simulation
13. Demonstration of change of support
• In order to demonstrate some
examples of change of support,
a data set has been created by y
simulation. It is necessary to do
this for a few reasons:
– Confidentiality of company
data
– Real data has additional
complexities
14. Simulated Data
• A data set has been created by a geostatistical simulation
• There is a single bench with a mining height of 5 metres and a
g g g
bulk density of 2.8 t/m3
• There is a cutoff grade of 0.12% U3O8
• The mine is mined by open cut using 130 tonne trucks (which
equates to a support of 3 by 3 by 5 metres)
• The simulation has been sampled on 25 by 25 metre and 50 by
50 metre centres – this is the drillhole data
15. Simulated Data – 1 metre spacing
N = 354,690
Mean U3O8 grade = 0.152%
Minimum value = 0.023%
Maximum value = 0.278%
Variance = 2.13 x 10-3 (%)2
16. Simulated Data – Reblocked to 3 by 3 m
N = 39,480
Mean U3O8 grade = 0.152%
Minimum value = 0.023%
Maximum value = 0.276%
Variance = 1.51 x 10-3 (%)2
17. Simulated Data – Reblocked to 25 by 25 m
N = 574
Mean U3O8 grade = 0.152%
Minimum value = 0.074%
Maximum value = 0.238%
Variance = 0.79 x 10-3 (%)2
18. Grade and Tonnage at Cutoff 0.12% U3O8
• Applying a cutoff of 0.12% U3O8 for the three supports of
simulations:
• Point support: 3.66 Mt at 0.173% U3O8
• 3 by 3m support: 3.93 Mt at 0.167% U3O8
• 25 by 25m support: 4.38 Mt at 0.159% U3O8
b 25 t 4 38 t 0 159%
• We will call these the “TRUE” values
ill al es
19. Sample Data
N = 329
Mean U3O8 grade = 0.152%
Minimum value = 0.024%
Maximum value = 0.278%
Variance = 2.24 x 10-3 (%)2
20. Semi-Variograms for U3O8
SAMPLES SIMULATED VALUES Cross validation:
Mean of error = 0.0003%
Mean squared error =
0.0021(%)2
Mean kriging variance =
0.0019(%)2
(small mean error,
theoretical variance within
10% of true variance)
21. Kriged estimate over bench
N = 574
Mean U3O8 grade = 0.153%
Minimum value = 0.092%
Maximum value = 0.220%
Variance = 1.00 x 10-3 (%)2
22. Kriged estimate over bench
• Applying a cutoff of 0.12% U3O8 for the kriged estimate:
• Kriged 25 by 25m support: 4.37 Mt at 0.159% U3O8
• “True” 25 by 25m support: 4.38 Mt at 0.159% U3O8
y pp
23. First method of change of support – Affine
Correction
• Using an Affine Correction to predict the tonnes and grade:
• Kriged 3 by 3m support: 4.03 Mt at 0.165% U3O8
• “True” 3 by 3m support: 3.93 Mt at 0.167% U3O8
• Close! But no thumbs up
24. Discussion on Affine Correction
• The Affine correction is rarely used in practice
• The reason behind this is that estimates are always
“normalised” – the histogram of the estimates are more
“bell shaped” than the samples
bell shaped
• The normalising effect is due to the Central Limit Theorem
• The change in the shape of the histogram makes this
method less reliable
25. Second method of change of support –
Conditional Simulation
• Using the sample data, 10 conditional simulations were made
• A conditional simulation is any method that maintains the
following 5 conditions:
– The simulation h the same statistics as the data
h l has h h d
– The simulation has the same spatial statistics as the data
– The simulation has the same multivariate statistics
– The simulated value and the data value are the same at the
same location
– Th simulated variable considers th geology
The i l t d i bl id the l
26. Second method of change of support –
Conditional Simulation
• If we make a simulation with a sufficiently dense grid of
points,
points we can re-block the simulations on different
re block
supports
• The 10 conditional simulations are on a 1 by 1 m grid, same
as the original simulation, then re-blocked to the 3 and 25m
dimensions
27. Second method of change of support –
Conditional Simulation
• We don’t have one answer –
we have 10 equally probable
answers!
28. Conditional Simulation – 25 by 25m reblock
25 by 25m blocks from simulation - Grade 25 by 25m blocks from simulation - Tonnage
Comparison Comparison
0.163 4550000
0.162 0.162 4,488,750
4500000
0.162 4,471,250
cted Grade for 5 by 5m blocks
cted Grade for 5 by 5m blocks
4450000 4,427,5004,427,500
0.161 0.161
4,410,000
4400000 4,370,000
4,380,000
0.160 0.160
0.16 4,348,750
4350000 4,322,500
0.159
0 159
b
b
0.159 0.159 0.159
0.159
0.159
0.159 4300000 4,287,500
4,243,750
0.158 4250000
0.157
4200000 4,182,500
0.157
4150000
Predic
Predic
0.156
4100000
0.155
4050000
0.154 4000000
29. Conditional Simulation – 3 by 3m reblock
3 by 3m blocks from simulation - Grade 3 by 3m blocks from simulation - Tonnage
Comparison Comparison
0.168 4100000
0.167 0 168
0.168
4,047,7504,049,136
0.167 4050000
cted Grade for 5 by 5m blocks
cted Grade for 5 by 5m blocks
0.167 0.167 4,030,000
4,012,344
4,005,414
4000000 3,987,0183,988,656
0.166 0.166 0.166 3,969,378
0.166
0.165 3,951,864
0.165
0 165
b
b
3950000 3,930,000
0.165
0.165 0.165
3900000
0.164
3,865,806
3,859,254
0.164
3850000
Predic
Predic
0.163
3800000
0.162 3750000
30. Conclusions
• It is important to consider the change of support for mine
planning purposes
• It is possible to perform change of support using
geostatistical methods; e.g. Affine correction, Uniform
eg correction
Conditioning, Multiple Indicator Kriging, Disjunctive Kriging,
Conditional Simulation to name a few
• They all do the same thing – predict the tonnes and grade
above a cutoff for a certain support
31. Final Comment
• If we want to know the support on 3 metres, why don’t we
just estimate into 3 metre blocks?
• Why not? Because the answer will be about the same as if
we estimate into 25 metre blocks!!
• Kriged 25 by 25m support: 4.37 Mt at 0.159% U3O8
• Kriged b 3
K i d 3 by 3m support: 4.26 Mt at 0.159% U3O8
t 4 26 t 0 159%
• Affine corrected 3 by 3m support: 4.03 Mt at 0.165% U3O8
32. References
KENDALL, C. J. (1990). Ranger Uranium Deposits. In: Geology of the Mineral Deposits of
Australia and Papua New Guinea. Vol 1 ed. F. E. Hughes, pp. 799 – 805. The
Australian Institute of Mining and Metallurgy, Melbourne.