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The world leader in serving science
AN INNOVATIVE & PRACTICAL
APPROACH TO SAMPLING
OF SLURRIES FOR METTALURGICAL
ACCOUNTING
Bernardo Ossandn Araya
J ess Caro Romero
Thermo Fisher Scientific Chile
23th
November 2006
PROCEMIN 2006
IV Taller Procesamiento de MineralesSantiago, Chile
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Combining Two Industry Leaders
Even Stronger Partner for Customers
Industry transforming
Exciting growth opportunities
World-class capabilities
$2.6 to $9.5 Billion in sales
11,000 to 30,000 employees
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Thermos Analytical Technologies
enable our customers to make the worlda healthier, cleaner and safer place
Drug Discovery
Forensic Science
Environmental TestingQuality Control
Petrochemical
Minerals Mining
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Thermo FisheFull offer to the Mining and Mineral Processing Industry
Lab Software
Solutions
Density Gauges
Lab
Analyzers
Flow Meters
Slurry Analyzers
Conveyor
Sampling & Analysis
Systems
Thickener Interface
Gauge
Slurry Sampling
Systems
Dry Material
Analyzers
Lab Sample
Prep Equipment
Level Gauges
Belt Scales &
Accessories
Solution Analyzers
Product
Solutions
Enviromental
Analyzers
Ai r/Gas/Water
Portable Analyzers
Laboratory
Mine
Environmental
Concentrators
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Metallurgical Sampler
In the Mining operations the following type of samples are collected :
Small samples are required after each shift for material
balancing/accounting
Small samples are requiered intermittently for plant/process control
and for calibration of on-line analyser
Continuous samples are required to feed on-line analyser, particle size
or elemental analysers
Any sampling system being used for Metallurgical accounting must be
accurate & representative (1).
(1).- FF Pitard-Pierre Gys Sampling Theory and Sampling Practice.1993
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Metallurgical Sampler
The Metallurgical sampling is a process where representative
samples are collected for chemical analysis in laboratory
These analysis results allow to prepare the metallurgical balance of
the plant
The mass conservation law says that metals present in the Feed must
be present in Concentrate and/or Tailings.
All mineral processing plant require metallurgical samplers in order
to determinate the process recovery.
FeedPROCESS
Final Concentrate
Tailings
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Metallurgical Sampler
There are three types of sampling :
Non probabilistic sampling, where a given part of the lot have has zero
chance of being selected
Probabilistic sampling, where all parts of the lot have a chance to be
part of the sample, and
Equi-Probabilistic sampling, where all parts of the lot have an equal
chance to be part of the sample.
Sampling is correct (ie., unbiased) when, and only when, samplingsystem is equi-probabilistic.
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Traditional Mettalurgical Samplers
Primary SamplerSecondary sampler. Vezin model.
Traditional Samplers
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Metallurgical Sampler
SamStat:Sampling Station
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SamStat Compliance with Sampling Theory
Each stage complieswith the samplingtheory and reducesthe flow rate by afactor of 20
SamSat uses severalstages to reduce the
slurry stream to a smalland easily manageableflow-rate
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SamStat Compliance with Sampling Theory
The primary flow enters
the SamSat and getsdirected downwards bythe first baffle
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SamStat Compliance with Sampling Theory
The bottom opening isquite small and the totalflow gets accelerated andenters the second section
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SamStat Compliance with Sampling Theory
The high turbulence created
by the increased flow-ratehomogenises the slurry
The baffle of the secondsection directs the flow
upwards
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SamStat Compliance with Sampling Theory
From the high turbulencearea the flow goes overthe weir and reaches the
sample cutters.
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SamStat Compliance with Sampling Theory
The cutters are equallydistributed over the width of thesampler to have the same area
of influence and to minimizeGrouping and SegregationError
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SamStat Compliance with Sampling Theory
Each cutter collects the entireheight of the stream to ensureequal vertical distribution of the
sampled amount
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SamStat Design
The last stage works the sameway as the previous one.
For bigger streams up to20.000m3 additional stagescan be added
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SamStat Design
FlowWeir
HeightTank Width
Baffle
OpeningWeir width
Slurry above
Weir
Head Drop
Across Baf fle
Slurry Height
DS
Slurry
Height in AS
Slurry
above
baffle
opening
Height
of Tank
Freeboard
%
Baffle
Height
Velocity
facing
cutters
Velocity
in DS
Q E D O W S HD H1 H2 H3 HT Fb Bh Vds
m3/s m m m m m m m m m m % m m/s m/s
Velocity
D
Fb Baffle Height Cutter
Slurry level
HD m/s
HT Slurry level
H1 S
Q H3 H2
Vds Weir
O E
Deareation Section Analisis Section
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SamStat Design Sampling Theory
Total Error = Sampling Error + Preparation Error + Analysis Error
Sampling with Mettalurgical quality must be Equi-probabilist icThis means all parts of a the lot have equal chance to be become part of the
sample.
Sampling is correct (ie., unbiased) when, and only when, sampling system
is equi-probabilistic
Total =Sampling2 +Preparation2 +Analysis2
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Errors in Slurry Sampling
Weighted Error (WE): results from non-uniformity of the density or
flow rate-rate of the sampled material
Intregation Error (IE1): results from the long-range distribution
heterogeneity of the sampled material.
Periodic Error(IE2): results from frequent periodic quality
fluctuations of the sampled material.
Fundamental Error (FE): results from the Constitution
Heterogeneity of the sampled material.
Grouping & Segregation Error (GE): results from small-scale
Distribution Heterogeneity of the sampled material.
Delimitation Error (DE): results from an incorrect shape of the
volume boundaries of the material taken across the stream.
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Errors in Slurry Sampling (cont.)
Extraction Error (EE): results from the design of the cutter blades,
the opening of the cutter and the general design of the cutter.
Preparation Error (PE1): results from accidental losses alongincrement transportation pipes.
Preparation Error (PE2): results from accidental contamination
along increment transportation pipes.
Preparation Error (PE3): results from unintentional mistakes.
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Sampling Theory
A10. Preparation Error (PE3)B9. Preparation Error (PE2)
A8. Preparation Error (PE1)
A7. Extraction Error (EE)
A6. Delimitation Error (DE)
B5. Grouping & Segregation Error (GE)
A4. Fundamental Error (FE)
A3. Periodic Error (IE2)A2. Integrated Error (IE1)
A1. Weighted Error (WE)
SamStat
Samplers
Sampling errors
A = Error are negligible; B = Error are small; C = Error may be large
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Sampling Theory
SamStat provide better primary sampling for feeding analysers or cross-cut sampler(2)
(2).- Sampling System for large flow slurry. FF Pitard-Report March 20th, 1999
A10. Preparation Error (PE3)B9. Preparation Error (PE2)
A8. Preparation Error (PE1)
A7. Extraction Error (EE)
A6. Delimitation Error (DE)
B5. Grouping & Segregation Error (GE)
A4. Fundamental Error (FE)
A3. Periodic Error (IE2)A2. Integrated Error (IE1)
A1. Weighted Error (WE)
SamStat
Samplers
Sampling errors
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ProcessStream Inlet
First Stageof Sampling
Controller
Third Stageof Sampling
Second Stage
of Sampling
ProcessStream Inlet
First Stageof Sampling
Controller
Third Stageof Sampling
Second Stage
of Sampling
Slurry Sampling (SamStat/Anstat)
Benefit :
Statistically Correct Sampling Essential for Metallurgical Accounting
Lowest Hydraulic Head Loss Cheaper to engineer into plants
Reliable with Lowest Maintenance Static Cutters have no moving parts so extremely reliable
Easy to inspect and clean
Simple Cutter Reeplacement On-Line
Mechanical Cross-Cut Sampler in Small Scale (400 mm) so reliable
No sample transport no additional pumps and no no blocked samples lines
In addition to Dedicated Analyser provides, integrated Sampling and On-Line Analysis
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AnStat de 4 Etapas1,400 - 23,000m3/hr
SamStat Sizes
AnStat de 2 Etapas
10 80 m3/hr
AnStat de 3 Etapas
80 1,400m3/hr
Th A S
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Thermo AnStatEscondida Phase IV Rougher Feed, 115,000 tpd
Th S St t
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Thermo SamStatMinera Los Pelambres . Final Tailings . 145.000 tpd
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