Ventilation, Heat, Moisture and Gas
Flow Modeling with MULTIFLUX
Presenters:
George Danko, Professor
Pedram Rostami, PhD Graduate Research Assistant
Jon Fox, PhD Graduate Research Assistant
Contributors:
Davood Bahrami, Assistant Research Professor
Ray Grymko, MS student
William Asante, MS student
Date: June 21st, 2012
Location: Salt Lake City, UT
Progress Summary
1) Task 1.2. User interface design for MULTIFLUX (Task 1.2c. )
• Progress: Continued the Graphical User Interface (GUI) development
• Plan for next quarter: Continue the user interface implementation
2) Task 1.4. Gas liberation/storage/application model-element (Task 1.4c. )
• Progress: Studied and conceptually designed the gas contaminant adsorption
model-elements in MULTIFLUX.
• Plan for next quarter: Continue the study, apply it in numerical examples;
design experimental comparison with data from mines.
3) Task 2.1 Development-end Ventilation application(Task 2.1c. )
• Progress: Further studied characterization of the development-end module
and presented the results to SME Annual Meeting. Also studied the effect of
local cooling at Banshee drift at Barrick’s GoldStrike mine as an industrial
application.
• Plan for next quarter: Continue with testing of the development-end
template with the GUI.
4) Task 2.2 Ventilation with combined compressed air power application(Task 2.2a. )
• Progress: This task is complete
• Plan for next quarter: No activity is planned
2
Progress Summary
5) Task 4.1 MULTIFLUX model results comparison with monitored data(Task 4.1c. )
• Progress: Designed, coded and tested the gas contaminant model elements in MULTIFLUX.
• Plan for next quarter: Continue modeling and comparison with data from mines.
6) Task 5.1 A self-calibrating, time-dependent ventilation model concept(Task 5.1a. )
• Progress: Studied the effects of time-dependent intake temperature variations.
• Plan for next quarter: Continue the modeling work; expand the solution to humidity
variations.
7) Task 6.1. MULTIFLUX model application to DPM prediction(Task 6.1a. )
• Progress: Studied the effects of time-dependent variations of concentrations in underground
drifts.
• Plan for next quarter: Continue modeling work
8) Task 7. MULTIFLUX model application in education
• Progress: (Offered a graduate course using MULTIFLUX, Mine 701 )
• Plan for next quarter: The education program continues
9) Task 8. Publications and reporting
• Progress: Presented one SME paper at the SME annual meeting. Submitted the 2nd progress
report in Phase 3. Worked on completing and submitting four papers to the 14th North
American Mine Ventilation Symposium (NAMVS) in Utah.
• Plan for next quarter: Continue with publications and reporting
3
Mackay Team Overview
• Industry contributions and publications
• Goals, research approach & findings this year
 Equivalent and hydraulic diameters
 Transient temperature variations
 Contaminant spread and transient, modeling approach
 Complex Ventilation and Contaminant Simulation with
MULTIFLUX
 VOD simulation with MULTIFLUX
 MULTIFLUX GUI development
 Side-by-side comparison of MULTIFLUX
 Development end MULTIFLUX sub-model template
4
Project Participants
•
PI
•
Co-PI
•
Co-PI
•
GRA
•
GRA
•
GRA
•
GRA
•
GRA
•
Industrial Partner
George Danko, PhD, University of Nevada, Reno
1664 N. Virginia St., Mailstop 173, Reno, NV 89557
Phone: (775)784-4284; Fax: (775)784-1833; E-Mail: danko@unr.edu
Davood Bahrami, Ph.D., University of Nevada, Reno
1664 N. Virginia St., Mailstop 173, Reno, NV 89557
Phone: (775)784-4210; Fax: (775)784-1833; E-Mail: dbahrami@unr.edu
Pierre Mousset-Jones, Ph.D., University of Nevada, Reno
1664 N. Virginia St., Mailstop 173, Reno, NV 89557
Phone: (775)784-6959; Fax: (775)784-1833; E-Mail: mousset@unr.edu
Pedram Rostami, PhD student
1664 N. Virginia St., Mailstop 173, Reno, NV 89557
Phone: (775)784-4209; Fax: (775)784-1833; E-Mail: prostami@unr.edu
Jon Fox, PhD student
1664 N. Virginia St., Mailstop 173, Reno, NV 89557
Phone: (775)784-4185; Fax: (775)784-1833; E-Mail: jefox@unr.edu
Raymond Grymko, MS student
1664 N. Virginia St., Mailstop 173, Reno, NV 89557
Phone: (775)784-4209; Fax: (775)784-1833; E-Mail: rgrymko@unr.edu
Rajeev Gunda, MS student
1664 N. Virginia St., Mailstop 173, Reno, NV 89557
Phone: (775)784-4209; Fax: (775)784-1833; E-Mail: rajeev.gunda@amec.com
William Asante, MS student
1664 N. Virginia St., Mailstop 173, Reno, NV 89557
Phone: (775)784-4210; Fax: (775)784-1833; E-Mail: eponition@yahoo.com
Barrick Goldstrike Mining Co.
5
Industry Professional Contributions
• Rajeev Gunda (MS Mining, August ’11) –
Employed at AMEC, Phoenix, AZ – Ventilation
Engineer, starting November 2011.
• Raymond Grymko (MS Mining, August ’12) –
Employed at Vale Inco, Sudbury, Ontario,
Canada – Ventilation Engineer, starting June
2012.
6
Publications
1) Bahrami D., Danko G., Fox J., Robertson K., 2012 “Development-End Cooling
Study.” 14th US/North American Mine Ventilation Symposium, Salt Lake City,
Utah.
2) Danko G., and Bahrami D., 2012. “Convective, Diffusive and Dispersive Transport
of Gaseous Constituencies by Ventilation.” 14th US/North American Mine
Ventilation Symposium, Salt Lake City, Utah.
3) Danko G., Bahrami D., and Mousset-Jones P., 2011 “Ventilation and climate
simulation with the MULTIFLUX code.” The 2nd International Conference on
mining, Mine Safety and Mine Environment Protection, Xi'an, Shaanxi, China.
4) Danko G., and Bahrami D., 2011 “Ventilation, Heat, Moisture and Gas Flow
Modeling with MULTIFLUX.” Third Outreach Seminar, Barrick Goldstrike Mine,
Nevada.
5) Danko G., and Bahrami D., Asante W. K., Rostami P., and Grymko R., 2012
“Temperature variations in underground tunnels.” 14th US/North American Mine
Ventilation Symposium, Salt Lake City, Utah.
6) Fox J., Danko G., and Bahrami D., 2012 “Development End Characterization
Through Response Curves.” SME Annual Meeting, Seattle, Washington.
7
Project Goals
1. To apply the MULTIFLUX air flow, heat, moisture, and gas
transport simulation model to ventilation tasks in deep, hot
underground mines and demonstrating its capabilities in
accurate predictions.
2. To use MULTIFLUX in selected cases by demonstrating
improvement in safety and costs.
3. To make MULTIFLUX easy to use as a new mine ventilation and
contaminant transport model.
4. To educate students and technical professionals how to use it.
8
Description of the research approach
• Add new, necessary components to the MULTIFLUX
software and model originally developed and qualified for
nuclear waste repository ventilation, heat and moisture
simulations.
• Provide the ventilation engineer with an easy–to–use
graphical interface for model definition and input data
entry.
• Interpret and animate the results graphically.
• Apply the MULTIFLUX model to industrial mine
ventilation tasks including applications with Barrick
Goldstrike, our research partner.
• Work with a total of six students as research assistants.
9
Project Findings
1) MULTIFLUX is used in predicting the performance of a spot cooler at the Barrick
GoldStrike mine. An advanced modeling approach was used to predict the cooling
effect of an air chiller if it is installed outby from the working face. The net results
show that the spot cooler with 11oC of chilling capacity is cooling the air at the
working face by about 6oC.
2) An artificial numerical dispersion error in the simulation results and systematic
solution error in the travel time of concentration front , both depending on the
discretization scheme and the refinement of the grid were found. But a solution used
in MULTIFLUX can be made free of both errors even if relatively large grid sizes are
used.
3) The test cases and benchmarking applications reviewed show that MULTIFLUX
captures the relevant heat and moisture transport processes excellently than
methods which use the simple Gibson age function.
4) MULTIFLUX outperforms Ventsim, which provides only an approximate, but not an
exact solution for the transient model. Therefore, we believe that MULTIFLUX is a
correct transient model for the contaminant spread in a mine airway.
5) With no temperature history effect in MULTIFLUX, its results are in very good
agreement with the other models, namely, with perfect, near-perfect, and very good
agreement with Vuma, Climsim, and Ventsim, respectively, but when MULTIFLUX is
modeled with temperature history effect very significant disagreements are obtained
with the other models.
6) Pre-modeling the development end allows for fine mesh evaluation throughout the
mine-wide ventilation model. Results of modeling yields response functions for
10
primary air mass parameters, which respond to intake air mass variations.
Transport Model Elements For
Conservative Scalar
• Transport processes
The transport of a chemically non-reactive, single-component substance
Scalar substance may be:
• Bulk Mass
• Water vapor Concentration
• Contaminant Concentration
• Heat
Six transport modes which are of interest in mine ventilation:
• Advection
• Diffusion
• Dispersion
• Convection
• Accumulation or discharge ( Source or Sink)
11
Numerical Applications
Two mine ventilation examples are presented to
demonstrate the performance of the numerical
solution method used in MULTIFLUX for
simulating
traveling
of
contaminant
concentration with the ventilating air;
1) A simple air flow network with a diagonal
airway
2) A single drift
12
Network Example 1 : Contaminant travel in MULTIFLUX with
D=0.05 m2/s and Ventsim with default
configuration
20
(B)
(C)
Concentration (%)
(A)
15
MULTIFLUX, 0 dis
Ventsim, default c
10
5
0
(D)
(E)
0
500
1000
1500
Time (seconds)
2000
(F)
13
Network Example 2 : Contaminant travel in MULTIFLUX with
D=0.0 m2/s and Ventsim with default configuration
A
B
C
E
D
Concentration (%)
20
MULTIFLUX, 0 disp.
Ventsim, default config.
15
Locations:
A: x=10 m
10
B: x=250 m
C: x=500 m
D: x=750 m
5
0
A
E: x=1000 m
0
500
1000
1500
Time (seconds)
C
B
D
2000
2500
E
1m/s
1000m
14
Network Example 1 : Contaminant travel in MULTIFLUX with
D=0.05 m2/s and Ventsim with default configuration
A
20
B
C
D
MULTIFLUX, D=0.2 m/s 2
Ventsim, default config.
Concentration (%)
E
Locations:
15
A: x=10 m
B: x=250 m
C: x=500 m
10
D: x=750 m
E: x=1000 m
5
0
A
0
500
1000
1500
Time (seconds)
C
B
2000
D
2500
E
1m/s
1000m
15
Conclusions
• An artificial, numerical dispersion may occur in the simulation results
of fast-traveling concentration transients transported by advection.
Numerical dispersion is an error in the simulation, depending on the
discretization scheme and the refinement of the grid.
• In addition to the numerical dispersion, another, systematic solution
error may appear in the travel time of the concentration front. This
error also depends on the discretization scheme and the refinement of
the grid.
• A solution used in MULTIFLUX, a new mine ventilation, heat, moisture,
and contaminant transport model and code, was presented which can
be made free of both numerical dispersion and the systematic error in
concentration travel time even if relatively large grid size is used.
16
Pedram Rostami
• Equivalent and hydraulic diameters
• Transient temperature variations
• Contaminant spread and transient, modeling
approach
• Complex Ventilation and Contaminant
Simulation with MULTIFLUX
17
Equivalent and hydraulic diameters
• Equivalent diameter of a rectangular opening is defined
as the diameter of a circular opening having the same
pressure loss.
• The hydraulic diameter, dh, is used to determine the
dimensionless Reynolds number to see if a flow is
turbulent or laminar.
dh = 4*A/P
• Since equivalent diameter results in simplified
calculations, current ventilation programs use this instead
of the actual geometry of the drifts.
18
Results and concluding remarks
• Shape and size analysis
– various shapes and sizes of mine airways were studied
• Infinitely long wall (flat model),
• original size rectangular-shaped model
• double-size rectangular model were studied and analyzed.
– Study results show the rectangular (including square)
models have a heat flux percentage difference of
about 5% with the equivalent diameter size cylindrical
models.
• There is no need to consider the actual drift
geometry. Equivalent diameter is sufficiently
accurate for airflow calculations.
19
Transient temperature variations
Flywheel effect in underground mining
• The thermal flywheel is effectively storage and release of heat from
the intake air into the intake airways as a function of the diurnal
and seasonal change in surface temperatures
• It can be considered as a damping effect.
• Heat stored by hot intake air into intake airway walls is released in
the cooler time periods (mostly evenings)
– This lowers the predicted underground temperatures during the day
(compared to theoretical values) but
– increases the underground temperatures (when wall temperatures are
now hotter than intake air temperatures) during the night (effectively a
phase shift)
• Currently used mine ventilation and climate models, apply the
Gibson function for wall heat flux without superposition.
– a step-change model element that erases the true temperature history
• Refer to ”Temperature variations in underground tunnels” by G.
Danko, D. Bahrami, P. Rostami, W. K. Asante, and R. Grymko
20
50
45
45
40
40
35
35
Temperature(oC)
50
o
Temperature( C)
Comparison between History and No
History Effects on Simulation Results
30
25
50
20
49.5
Intake
1km with history
1km without history
VRT=28oC
49
15
48.5
10
48
5
47.5
0
10
20
25
50
20
49.5
50
48.5
10
48
5
47.5
0
60
46.5
46.5
46
40
46
44.5
5
6
7
8
9
Temperature(oC)
45
10
20
47
45
45.5
Intake
3km with history
3km without history
VRT=28oC
1549
30
40
Time(months)
50
1km & 5m3/s
47
30
30
40
Time(months)
50
60
3km & 50m3/s
45.5
35
45
30
10
25
50
44.5
11
12
5
6
7
8
9
10
11
12
20
49.5
Intake
5km with history
5km without history
VRT=28oC
49
15
48.5
10
48
5
0
47.5
10
20
30
40
Time(months)
50
60
5km & 100m3/s
21
Comparison between Temperature Mesh
With and Without Temperature History
With History at 50m3/s
airflow rate.
Without History at 50m3/s
airflow rate.
22
Contaminant spread and transient
modeling
• Barrick Goldstrike, modeling approach is described in the
following.
• Type of contaminants: SO2 and CO are selected as the
two problematic gases.
• Sources of contaminants:
•
•
•
•
Strata
Operating machinery
Blasting operations
Ventilation recirculation
23
Mine Overview
North
Meikle, Level
1075
Rodeo, Level
4040
24
Rodeo
North
Working Zones
CO2 Monitoring Station
SO2 Monitoring Station
CO
Monitoring Station
Active Face
Junction
25
Meikle
Working Zones
North
Active Face
Junction
26
Heat and Water Distribution
Mine
Electric
Production
Energy
Diesel
number of compresse
per day
Consumpti Consumption
work zones d air (cms)
(TPD)
on per
per mine (l/s)
mine**
Other
Diesel
Total
Diesel required processed
Total Heat
Diesel heat
processed
Source/Sin
processed
air per mine water per Junction
sources/sinks
per mine (W) water per mine
k (cms)
water
(kg/s)
mine
(W)
(kg/s)
(kg/s)
(kg/s)
Rodeo
627
3
0.2832
1.32E+06
0.011547545
429383.9302
0.022542656
0.207855818
5.33E-01
1498
0.2832
429383.9302
5.55E-01
Rodeo
836
4
0.3776
1.76E+06
0.015396727
572511.9069
0.030056875
0.277141091
7.10E-01
1482
0.3776
572511.9069
7.40E-01
Rodeo
418
2
0.1888
8.78E+05
0.007698364
286255.9535
0.015028438
0.138570545
3.55E-01
1483
0.1888
286255.9535
3.70E-01
Rodeo
418
2
0.1888
8.78E+05
0.007698364
286255.9535
0.015028438
0.138570545
3.55E-01
1479
0.1888
286255.9535
3.70E-01
Meikle
422
2
0.346
1.22E+06
0.015614667
580615.7653
0.030482328
0.281064 1.97E+00
117
0.346
580615.7653
1.99626
Meikle
211
1
0.173
6.11E+05
0.007807333
290307.8827
0.015241164
0.140532 9.83E-01
120
0.173
290307.8827
0.99813
Meikle
211
1
0.173
6.11E+05
0.007807333
290307.8827
0.015241164
0.140532 9.83E-01
142
0.173
290307.8827
0.99813
Meikle
211
1
0.173
6.11E+05
0.007807333
290307.8827
0.015241164
0.140532 9.83E-01
165
0.173
290307.8827
0.99813
Meikle
211
1
0.173
6.11E+05
0.007807333
290307.8827
0.015241164
0.140532 9.83E-01
127
0.173
290307.8827
0.99813
Meikle
211
1
0.173
6.11E+05
0.007807333
290307.8827
0.015241164
0.140532 9.83E-01
137
0.173
290307.8827
0.99813
Meikle
211
1
0.173
6.11E+05
0.007807333
290307.8827
0.015241164
0.140532 9.83E-01
141
0.173
290307.8827
0.99813
Meikle
211
1
0.173
6.11E+05
0.007807333
290307.8827
0.015241164
0.140532 9.83E-01
149
0.173
290307.8827
0.99813
Total:
4200
20
2.5954
10330000
0.112607
1098
2.5954
4187178.688
11.0188
4187178.688
0.219826881
2.026926
10.799
** Electrical power consumption is not considered in the heat simulation. The electricity is
assumed to be used mainly by, hoisting, pumps and lighting of the mine.
27
Complex Ventilation and Contaminant
Simulation with MULTIFLUX
Background
• Dispersion of contaminant gas can happen due:
– Along the length of the airway through natural dispersion.
– From low velocity flow to high velocity in the center of the
airway.
– In the Cross-sectional area of the airflow depending on the
concentration zone.
– And finally the convective dispersion from the forced air.
• Current codes use a simple algorithm which distributes
Contaminants in a linear velocity fashion, and assumes
perfect mixing at intersections.
• This method is fine for studies through broad mine areas,
but is not recommended for analysis of contaminant
diffusion on a small scale level
28
Spatial Issue
• Due to the location of a source and ventilation system
spatial inhomogeneity arises.
• In addition to this spatial variability there is also
temporal variability
– processes coming on and going off line and ventilation
rates changing with time.
• While the worker is moving in this complex
environment the concentration level of air he is
breathing may be different from the average.
• What is a safe zone!
– Exposure is limited or not harmful!
• Where is the safe zone?
29
Average Concentration level
30
Methodology
• A CFD model needs to be established.
• This master model will be used to run various
scenarios.
• Results will be compared and analyzed.
• Considering the geometry source terms,
machinery and obstacles in the airway we can:
– Propose a distance in which the flow is mixed enough
and any measurements of contamination would
represent the average value.
31
Temporal Issue
• When and at what concentrations level?
– Be able to predict arrival time and concentration
levels at any given point in the mine network.
• We need:
– Calculate a dispersion coefficient that represent all
types of diffusions mentioned before in the
airway.
– Use the representing dispersion coefficient for a
larger scale contaminant modeling.
– Model In a non-CFD code.
32
• Concentration
• Arrival time
• Dilution
33
Methodology
• CFD model will be established using gathered
data from the mine.
• This master model will be verified and used again
in various ventilation scenarios to calculate the
dispersion coefficient and compare the findings
to the spatial issue.
• The calculated parameters will be used in future
predictions of contaminant arrival and
concentrations at a given point using MULTIFLUX
code.
34
Data collection and calibration of the
model
• This investigation of contaminant behavior can be achieved by gathering
required data from actual mine scenario.
• This data collection set is one the most crucial steps in modeling and
verification of findings.
• Two sets of database are needed to address the temporal and spatial
issues.
• FIRST SET
– The first data set includes three stations located 100meters apart from each other in a
long airway.
– We need to take 10 measurements of velocity and contamination concentrations in each
station for three different scenarios of, 1) no airflow, 2) laminar and 3) turbulent.
• SECOND SET
– The second set of data base would include measurements of velocity and concentrations
before and after the contaminant source. We need to know the airway properties
(geometry, obstructions and heat transfer properties), to find a distance from which the
measurements would represent the average of the mixture.
35
36
37
Jon Fox
• VOD Simulation with MULTIFLUX
• MULTIFLUX GUI Development
• Side-by-side comparison of MULTIFLUX,
Ventsim & Vuma vs. VnetPC/Climsim
• Development end MULTIFLUX sub-model
template
38
VOD Simulation with MULTIFLUX
• Define control architecture.
• Vary one big underground booster fan.
• Study mass flow cross effects among affected
ventilation districts.
39
Mine-wide ventilation control flow chart
Gas
Sensors
(CO
CO2
SO2
.
.
.
)
Airflow
rate and
direction
Sensors
(Qv
Qm)
Temperature
and
humidity
Sensors
(WBT
DBT)
Diesel
Particulate
Sensors
(DPM)
Equipment
location
and
monitoring
Sensors
(Wi-Fi tags)
Mine
personnel
location
Sensors
(Wi-Fi tags)
Mine
design and
production
schedule
Manual
observation
Check: Threshold Limit Values, Time Weighted Averages, Short Term Exposure Limits, Ceiling Limits
Mine
display
system
Mine
monitoring
database
servers
Automatic
emergency
control (fire,
evacuation)
Administrative
reporting
Mine
ventilation
and
climate
control
model
Automatic
ventilation
control
(VOD)
Event-based
manual
control
(Emergency
VOD timeof-day)
Mine data communication network (Ethernet, DH+, fiber-optic...)
and Manual communication system (Leaky feeder, tunnel radio, Wi-Fi, ultra-low frequency...)
Major
exhaust
fans
Booster
fans
Room fans
Blast gas
fans
Air doors,
regulators
Air
conditioners,
chillers
Notification
to mining
personnel
(Cap lamps)
40
Change in Airflow Directions From Variable Fan Modulation
• Modulate twin Joy M84 booster fans at 1450 level
– Variable frequency modeled @ 50%
41
Change in Airway Velocities Due To Fan Modulation
Modulate twin Joy M84 booster fans at 1450 level
Variable frequency modeled at 50% pressure
Affected Airways - Percentage Change in Airflow Rate
Affected airways are shown in red
Start
280
End
286
ΔQab
-26.622
%Δ
-101%
305
227
15.675
179%
Start
280
286
411
418
410
412
415
1270
1280
1286
1287
1288
1289
1291
1197
1198
1201
1206
1208
1248
1196
811
989
991
1462
1012
399
End
286
296
410
411
412
415
417
1258
1270
1280
1286
1287
1288
1289
1196
1197
1198
1201
1206
1208
1291
808
988
989
1502
1015
1492
ΔQab
-26.622
-26.622
-33.943
-33.943
-33.943
-33.943
-33.943
-23.28
-23.28
-23.28
-23.28
-23.28
-23.28
-23.28
-23.263
-23.263
-23.263
-23.263
-23.263
-23.263
-23.263
-29.569
-12.632
-12.632
-10.644
-10.377
-4.7941
% Δ Previous New
-101%
26.412 -0.20943
-101%
26.412 -0.20943
-157%
21.575 -12.368
-157%
21.575 -12.368
-157%
21.575 -12.368
-157%
21.575 -12.368
-157%
21.575 -12.368
-147%
15.831 -7.4483
-147%
15.831 -7.4483
-147%
15.831 -7.4483
-147%
15.831 -7.4483
-147%
15.831 -7.4483
-147%
15.831 -7.4483
-147%
15.831 -7.4483
-147%
15.793 -7.4704
-147%
15.793 -7.4704
-147%
15.793 -7.4704
-147%
15.793 -7.4704
-147%
15.793 -7.4704
-147%
15.793 -7.4704
-147%
15.793 -7.4704
-207%
14.304 -15.265
-138%
9.1362 -3.4963
-138%
9.1362 -3.4963
-174%
6.1307 -4.5137
-195%
5.3298 -5.0474
-137%
3.5036 -1.2906
Start
475
1062
1061
1056
1421
1342
1902
1043
1044
1046
1047
1045
1051
1057
658
429
1342
400
324
226
329
325
323
332
336
1462
305
End
ΔQab
% Δ Previous
478
-6.721 -192%
3.4943
1061 -3.9417 -129%
3.0483
1056 -3.9167 -130%
3.0056
1057 -3.9167 -130%
3.0056
1455 -12.983 -592%
2.1931
1209 -11.912 -819%
1.454
1867 -0.22717 -122% 0.18642
1042 -3.0427 -1676% 0.18154
1043 -3.0427 -1676% 0.18154
1044 -3.0427 -1676% 0.18154
1045 -3.0427 -1676% 0.18154
1046 -3.0427 -1676% 0.18154
1047 -3.0427 -1676% 0.18154
1051 -3.0427 -1676% 0.18154
757 -0.17297 -114%
0.1514
425 0.32736 157% -0.20841
1244
11.912 819%
-1.454
398
4.6321 218% -2.1234
226
6.0118 175% -3.4439
227
6.0118 175% -3.4439
323
6.0118 175% -3.4439
324
6.0118 175% -3.4439
325
6.0118 175% -3.4439
329
6.0118 175% -3.4439
332
6.0118 175% -3.4439
1458
10.644 174% -6.1307
277
15.675 179% -8.7679
42
New
-3.2267
-0.89347
-0.91109
-0.91109
-10.789
-10.458
-0.04075
-2.8611
-2.8611
-2.8611
-2.8611
-2.8611
-2.8611
-2.8611
-0.02156
0.11896
10.458
2.5087
2.5678
2.5678
2.5678
2.5678
2.5678
2.5678
2.5678
4.5137
6.9068
Conclusions
• Careful model exercises are needed VOD to understand
cross-effects on dynamic changes.
• Variations of VOD control components must be carefully
evaluated.
• Future research findings will drive new developments in
ventilation control architecture.
43
MULTIFLUX GUI Development
• Network definition is made in Google SketchUp
• Airway branch definition is by:
– graphical template selection and
– Interactive user’s data input
44
Side-by-side comparison of MULTIFLUX, Ventsim
& Vuma vs. VnetPC/Climsim
• Base model of Garson nickel mine with aerodynamic
simulation in VnetPC and thermodynamic simulation in
Climsim.
• Verification methods have been validated in Matlab.
• Comparison of dry bulb and wet bulb predictions are the
meter of modeling performance.
45
MULTIFLUX model verification methods
46
MULTIFLUX model verification methods
47
MULTIFLUX Graphical User Interface
Google SketchUp Workspace
48
Ventsim model
49
Vuma model
50
Conclusions
• Without a tutor properly versed in each simulation
software, the probability of creating an accurate model is
spotty at best.
• Having reliable technical support that can guide the
student through the intricacies of the model configuration
is paramount when comparative simulations are
required.
• Until extreme resistances, either zero or (practically)
infinite, are resolved into realistic resistances even the
base case airflow model is suspect.
51
Development end MULTIFLUX sub-model
template
• Cooling capacity prediction and parametric studies are
being conducted to support the design or the
development of single-entry drifts
• A new set of data has been obtained from the Barrick
Gold strike Mine complex for model verification
• The goal of the study is to model and apply a
development-end template and determine the
performance of the proposed chiller in providing
workable environment at the face
52
Ventilation configuration for the Banshee development end
53
Geometry, specification & measurement locations for the
Banshee development end
54
Pressure distribution with three fan locations, p3.
Drift airflow direction
duct
Duct airflow direction
drift
Pressure distribution along drift and duct with 2.7kPa back pressure behind the bulkhead.
55
Dry bulb temperature distribution along drift and duct
duct
drift
Drift airflow direction
duct airflow direction
56
Conclusions
• Transient thermal-humidity simulation needs to be
configured to predict the true effect of the installed
chiller.
• 14% leakage between duct and drift has been
determined.
• MULTIFLUX is capable of simulating this multiple-aged
case with multiple transients.
• A net temperature decrease of 6 °C can be expected at
the face.
57