1
VENTILATION AND CLIMATE SIMULATION OF DEVELOPMENT ENDS IN METAL MINES
Davood Bahrami, University of Nevada, Reno, Reno, NV.
Pedram Rostami, University of Nevada, Reno, Reno, NV.
George Danko, University of Nevada, Reno, Reno, NV.
Abstract
It is important to study the mine ventilation systems in
order to better design and control the working environment
in deep underground mines. With increasing depth, heat,
and humidity, worker performance may be reduced and the
safety of the workers must take special attention.
The purpose of this paper is to apply a development-
end ventilation model to a real underground mining
scenario at the Lucky Friday Mine in Idaho, USA. Two
models and field measurements from the mine are used for
comparison, MULTIFLUX (MF) (Danko 2008) and Kduct
(Gao and Inoue, 2002).
The MF development-end model template has already
been benchmarked against the measurement data from two
UK coal mines in previous studies (Danko et al., 2010a;
Danko et al., 2010b). The present study is another test of
MF application in a metal mine.
The results of the study show a reasonable agreement
between the MF model and the measurements, provided
that the heat transport between the freshly mined ore and
the air is incorporated in the model.
Introduction
The number of mines suffering heat problems due to
the increasing depth of the working area is growing. It is
well known that high temperature and humidity in an
underground working area may result in loss of productivity
and impairment of workers. A properly controlled
environment and a well-implemented ventilation system
model must be maintained in underground mines.
Many studies have been made to control the climate
conditions in underground mines but most of them are
based on through airflow in a single airway. Only a few
models (Gao and Inoue, 2002; Danko et al., 2010a; Danko
et al., 2010b) are available for applications in development-
ends with local ventilation.
The purpose of this study is to model and simulate a
development-end scenario using mine input data and
measurements from the Lucky Friday Mine. Two mine
ventilation and climate simulation programs, MF and Kduct
are employed for comparison with mine data to simulate the
ventilation network and calculate the unknown parameters
such as temperature and humidity.
First, the MF program (Danko 2008), developed at the
University of Nevada, Reno, USA is used as it is pursued
for wide-spread mine ventilation and climate predictions in
underground mines. The MF model takes into account the
air flow field in the drift and the auxiliary air duct;
simultaneous heat and humidity transport from the drift
wall; heat and mass exchange between the air in the drift,
the ducts and freshly mined rock as well as the evaporation
of process water and/or condensation of vapor as governed
by the psychometric conditions. The MF software is a
qualified software (Danko, 2008), for ventilation and
climate studies for high level nuclear waste repositories.
MF has been used in mining applications to compare it to
CLIMSIM (CLIMSIM 1997), as well as other mine
ventilation applications for development-ends (Danko et al.,
2010a; Danko et al., 2010b).
Second, the Kduct (Gao and Inoue, 2002), is also used,
since it is specifically developed for development-end
applications by Gao and Inoue at the Kyushu University,
Japan. The Kduct model has similar capabilities to those of
MF, however, it does not include heat and moisture
transport from the transportation of the mined ore.
2
Model parameters and airway configuration
Input data for the simulation was received via personal
communication from the Lucky Friday Mine (Mousset,
2010). The dead-end development includes a 153m long
airway, 3.65m by 3.65m in cross section. A flexible duct
delivers fresh cooled air to the end of the drift. The air is
needed to clean out the dust from the production area by the
drill and blast operation, and to reduce the air temperature
for the miners. Figure 1 shows the schematic arrangements
of the development-end in this study. A single air duct is
used with a fan located 3m from the inlet to blow fresh air
to the face. The axial fan produces 11.8 (m3/s) airflow at
30% assumed power efficiency. The cooler is located 6m
from the inlet and has the capacity of 175.85KW (50 tonR)
of cooling power. The relative humidity of the air at the
inlet is calculated to be 100 %, based on wet-bulb and dry-
bulb temperatures.
Input Data
The input data used in the model configuration are
shown in Table 1. The nominal power ratings of 175kW
and 45kW for the cooler and the fan respectively, would
result in a colder air temperature entering the duct than that
of the drift. This would cause far too strong cooling effect
for the model to handle and to match the temperature at the
face and the exit. It was necessary to evaluate the
parameters manually after the cooler as the input for the air
duct.
Due to the fact that the efficiency of each unit is
unknown, the nominal values for the fan and the cooler
power cannot be used as the input values of the model.
Since no measurements were taken for the actual fan and
cooler power, the dry-bulb and wet-bulb temperatures after
the cooler were back-calculated manually, fitting the MF
model by trial and error to the measurements of the dry-
bulb and wet-bulb temperatures at the exit of the air duct.
The back-calculated dry-bulb and wet-bulb
temperatures after the cooler (i.e., the inlet value at the
beginning of the air duct) were 21.7 °C and 20.4 °C,
respectively.
No visible wetness was reported from the mine, but
judging from the measured values of wet-bulb at the inlet
being lower than the exit wet-bulb temperature, moisture
transport is expected and included in the model.
The Airflow, Thermal, and Humidity Model
The MF program is designed to be used in subsurface
openings such as a nuclear waste repository or an
underground mine with or without development-ends. The
model can be used for coupled, time-dependent thermal-
hydrologic and ventilation calculations. The software
allows for complex calculations for large-scale systems. MF
is composed of two main domains: (1) the geological rock
formation and (2) subsurface airway systems. The two main
domains are coupled iteratively in the MF program.
Table 1. Input parameters for the Kduct and MF model.
Airway
Length (m) 153
Grade (%) 16
Cross section (m2) 3.65x3.65
Surface are (m2) 13.4
Perimeter (m) 14.6
Inlet air Temperature (°C) 18
Relative Humidity (%) 100
Fan
Distance from the Entrance (m)
3
Flow(m3/s) 11.8
Power (kW) 44.74 (60 hp)
Cooler
Distance from the Entrance (m)
6
Flow(L/min) 284
Cooling Capacity (kW) 175 (50 tonR)
Duct Diameter (m) 1.07
Length (m) 132
Pressure Surface (kPa) 90.12
Section (kPa) 108.3
Rock
Virgin Rock Temperature(VTR) (°C)
50 (47.2*)
Thermal Conductivity (W/mK)
3.13
Density (kg/m3) 2670
Mining advance rate for material transport rate
Advance rate (m/day) 3.0**
Wet-bulb (WB)and Dry-bulb (DB) Temperature at the Face (measured)
DB (°C) 23.8
WB (°C) 21.11
Wet-bulb(WB) and Dry-bulb(DB) Temperature at the Entrance\Exit of duct (measured)
DB (°C) entrance 18.88
DB (°C) after fan and cooler
21.7***
WB (°C) entrance 18.88
WB (°C) after fan and cooler 20.4***
DB (°C) exit 22.7
WB (°C) exit 20.55
Wet-bulb(WB) and Dry-bulb(DB) Temperature at the exit (measured) ****
DB (°C) exit 29.4
WB (°C) exit 23.8
* Originally given as 47.2 °C, the VRT had to be modified, see discussion
section. **
Heat transport form the freshly mined ore to the air is included in the thermal
model. The material transport flow rate from the drift advance rate is 1 kg/s
per day ***
Back calculated temperatures, using the MF by trial and error. ****
These parameters were not explicitly needed for the modeling process;
however since the exit wet-bulb temperature was higher than that of the wet -
bulb at the inlet; moisture transport was expected and included in the model.
3
Figure 1. General schematic of the development-end with the airflow pattern
Figure 2.Discretization of rock mass domain around the airway in NUFT
-40 -30 -20 -10 0 10 20 30 40-40
-30
-20
-10
0
10
20
30
40
Ventilation
Raise Cooler
Exit
Fan
Bulk
Head
Model Domain
131m
3.6m
3.6m
Drill and Blast
Face
4
Figure 3.Heat and moisture fluxes from the strata to the interface elements of the drift.
In the rock mass domain, strata heat flow is modeled
with the NTCF (Numerical Transport Code
Functionalization) module (Danko, 2006). The NTCF
process uses a Porous Media Hydrothermal Code (PMHC)
to model the heat and moisture flow in the rock mass
around the airway. The PMHC model calculates the heat
and/or moisture flux for specific temperature and/or
humidity variations on any surface of the airway. NUFT
(Non-equilibrium, Unsaturated-saturated Flow and
Transport) (Nitao, 2000) is used as a PMHC in the present
paper. The rock mass model domain, shown in Figure 2, is
set up as a separate task. The relevant transport
connections in this study are shown in Figure 3. A
schematic illustration of the coupled processes in the cross-
section of a drift and on the rock-air interface is also shown.
In the drift air space, a numerical model is used in the
form of a lumped-parameter, Computational Fluid Dynamic
(CFD) solver for air, heat, and moisture transport. Heat and
moisture fluxes qh and qm are the input from NTCF, and
temperature and pressure are the output from CFD. The
heat and moisture fluxes are balanced at the common
surface temperature and partial vapor pressure at each drift
wall surface node and time instant t for the solution of the
time-dependent problem.
MF Model Definition
The first step in model preparation in MF is to discretize
the in-drift domain into a number of axial divisions and
define the elements and the transport processes in each
section between the elements. As shown in Figure 4,
discretization with the intervals of 1 meter spacing is
established in the airway and the air duct. Note that the
meshing is shown only at the two ends and left out in the
mid-section of the drift for clarity. The airflow affects the transport of heat and moisture in
two ways, first, by providing a direct means of transport
expressed in capacitive, and convection transport
connections in the CFD sub-models for heat and moisture
transport, second, by affecting the heat and mass transport
coefficients between the solid surfaces and moving fluid.
Heat and moisture transport connections are defined
between the nodes along the flow lines in the airway and
the duct, as well as between the nodes in the return flow
line and the solid surfaces. Further connections are
established between solid surface elements for modeling
heat radiation. As a result, the in-drift model domain has a
total of 1647 nodes for the air, the heat and the moisture
networks.
Air Node
Heat and moisture fluxqh, qm
Coupling
surface q
h (t) wall moisture flux
qm (t) wall heat flux
Wall Node
Tw (t) wall temperature
dependent p
w (t) wall partial vapor
pressure
Heat
convection
Heat
convection
Heat
convection
Moisture
convection
Duct thermal
radiation
qh (t) wall moisture flux
qm (t) wall heat flux
qm (t) wall heat flux q
h (t) wall moisture flux
Air Duct
Heat
convection
Mined Ore
5
Figure 4.Thermal, moisture and airflow connections in the airway.
The MF model input data conform to those given in
Table1. In addition, the following internal data were used.
Wetness factor on the drift wall in the MF: 85%.
Heat transport connection for the material transport
based on 3m advancement per day is 1.0 kg/s of ore
transport with enhanced surface exposure of 13m2 per
meter of drift.
Heat transport coefficient between the transported
material and the air in the drift: internally calculated,
equal to that on the drift wall.
Kduct Model Definition
The Kduct program is designed specifically for
development-end applications. Figure 5 shows the model
interface and the input parameters given in mixed units.
These values follow the input data in Table 1. The Kduct
model includes a fan and a cooler but it was impossible to
use the nominal power rating of these units as input and
have reasonable output results from the model.
Generally speaking, the data entry for the model should
use the actual power input for the fan and the fan’s
hydraulic and electric motor efficiencies in order to model
the temperature rise across it. Similarly, the
thermodynamic and heat/moisture transport within the
cooler should be correctly modeled in order to predict the
air temperate and humidity leaving the unit.
There is simply not enough number of parameters to
enter into the Kduct model for defining the processes in the
fan and the cooler. After some unsuccessful attempts to run
the Kduct model with meaningful results, the fan and the
cooler were left out of the model. The dry-bulb and the
wet-bulb temperatures at the duct inlet after the cooler were
used as explained in the Input Data section.
Results
The results from MF and Kduct are shown together in
Figures 6 and 7 for the dry-bulb and wet-bulb temperatures.
At the beginning of the air duct (inlet) for the MF model,
the dry-bulb temperature starts at 21.7 °C. The air heats up
in the duct, and the temperature reaches 22.8 °C at the duct
exit and 23.5°C at the face. Prediction for the temperature
of the returned air in the drift at the exit is 29.1°C.
The dry-bulb temperature for the Kduct at the duct inlet
point is also kept at 21.7 °C. The temperature increases to
22 °C at the end of the duct. At the face, the temperature is
22.5 °C, and at the drift exit point the temperature is 24.6
°C. The results of MF are in good agreement with mine
measurement data.
Face
Wall Node
Air Node in the
Drift
Air Node in the
Duct
1m
6
Figure 5. K-duct model input parameters.
Figure 7 summarizes the predictions for wet-bulb
temperatures. The MF simulation results for the wet-bulb
temperature is 20.4 °C at the inlet of the duct and 20.5 °C at
the exit of the air duct. Due to exposure to the hot face, the
temperature increases to 21.0 °C. The predicted temperature
at the drift exit is 23.5 °C.
The Kduct wet-bulb temperature prediction rises from
20.25°C at the duct inlet to 20.6°C at the exit of the duct.
Temperatures at the face and the drift exit are 20.6°C and
21.7°C, respectively.
Discussion
Since the actual fan and cooler power were not
available, the temperatures after the cooler had to be back-
calculated using the dry-bulb and wet-bulb temperatures at
the exit of the air duct. The dry-bulb and wet bulb
temperatures from this calculation had to be used as input to
the air duct in order to start the model calculations.
There is reasonable agreement between the predicted
wet-bulb and dry-bulb temperature values from MF and
those of the measurement data received from the mine. The
MF model includes thermal and moisture transport
processes from the transportation of the freshly mined ore
in the drift. These transport processes have been included in
the previous studies (Danko et al., 2010a; Danko et al.,
2010b) as a realistic transport assumption, and good
agreement was obtained between measurement and
simulation. The heat exchange from material transportation
process is not included in the Kduct model. For this reason,
i.e., missing thermal connections, the Kduct predictions are
neither in agreement with the measurement data nor with
the predicted values from the MF model.
7
Figure 6.Dry-bulb temperature predictions in the air duct and the drift.
Figure 7. Wet-bulb temperature predictions in the air duct and the drift.
0 20 40 60 80 100 120 140 16018
20
22
24
26
28
30
Distance, ( m )
Tem
pera
ture
, (
oC
)
MULTIFLUX
Kduct
measuement
0 20 40 60 80 100 120 140 16018
19
20
21
22
23
24
Distance, ( m )
Tem
pera
ture
, (
oC
)
MULTIFLUX
Kduct
measuement
Drift Exit
Drift
Face
Air Duct
Airway Inlet
Drift
Face
Air Duct
Duct Inlet, calibrated
Drift Exit
Airway Inlet
Duct Inlet, calibrated
8
The virgin rock temperature of 50 °C (used in both
models), is 2.8 °C more than what was originally received
from the mine. Liberty was taken to make this temperature
increase for better matching the models to measurement
data. We consider that uncertainty should be expected from
temperature measurements of about ±4 °C RMS error in an
operating mine, with temporal thermal variation, (UNR,
2010).
The Kduct model input parameters can be tuned to
obtain agreement with the measurements from the mine
only by using extreme input parameters such as 11W/m-K
for the rock mass thermal conductivity, a rather unrealistic
value for any rock type in an underground mine. For this
reason the simulation results with this high rock thermal
conductivity are not included in this paper.
Concluding Remarks
A development-end modeling exercise is presented to a
real underground mining scenario at the Lucky Friday
Mine in Idaho, USA. Two models, MF and Kduct, as
well as field measurements from the mine are used for
comparison.
The MF model incorporates the simulation of the air
flow field in the drift and the auxiliary air duct;
simultaneous heat and moisture transport from the drift
wall; heat and mass exchange between the air in the
drift, the ducts and the freshly mined ore; as well as the
evaporation of process water and/or condensation of
vapor as governed by the psychometric conditions.
The Kduct model has similar capabilities to those of
MF, however, it does not include heat and moisture
transport from the transportation of the mined ore. The
model cannot be matched with mine data without using
an extreme value for heat conductivity of the strata.
Excellent match was obtained by MF, if a model
element for thermal and moisture transport of the
freshly mined ore, being transported in the airway, is
included.
Acknowledgement
The research fund from NIOSH, USA, under grant
number 200-2009-30157 is gratefully acknowledged. The
permission of using NUFT from the Lawrence Livermore
National Laboratory is thankfully appreciated. We
thankfully acknowledge Dr. Pierre Mousset-Jones for
providing the measurements data from the Lucky Friday
Mine and personal communications with the mine.
References
1. Danko, G., (2006). “Functional or Operator
Representation of Numerical Heat and Mass Transport
Models.” ASME Journal of Heat Transfer, Vol.128,
pp.162-175.
2. Danko, G., (2008). “MULTIFLUX V5.0 software
Documentation Qualification Documents.” Software
Tracking Number; 1002-5.0-00, Software Management
Office, Berkeley National Laboratory.
3. Danko, G and Bahrami D., (2008). “Application of
MULIFLUX for Air, Heat and Moisture Flow
Simulations.” 12th
U.S/North America mine Ventilation
Symposium 2008, Reno, NV Jun 9-11, 2008, pp. 267-
274.
4. Danko, G., Bahrami, D. and Gunda, R., (2010a).
“Simultaneous Ventilation, Power and Cooling Supply
with Compressed Air.” Proceedings Extracting the
Science: A Century of Mining Research, (Ed. Jurgen
Brune), SME Annual Meeting and Exhibition, Phoenix,
AZ, 2010 pp. 463-477.
5. Danko, G., Bahrami, D. and Gunda, R. (2010b).
“Simulation of ventilation and climate conditions in
development-end applications.” Proceedings of the
13th U.S'/North American Mine Ventilation Congress
Symposium, 2010 Sudbury, Ontario, Canada.
6. Gao, K. Uchino & M. Inoue Fukuoka, Japan (2002).
“Modeling of thermal environment conditions in
developing roadway.” Earth Resources Engineering
Dept. Kyushu University.
7. Mousset-Jones P (2010). Personal communications
including those with mine personnel at the Lucky
Friday Mine.
8. Nitao, J. (2000). “NUFT, Flow and Transport code
V3.0s.” Software Configuration Management, Yucca
Mountain Project – STN: 10088-3.0S-00. Prepared at
the Lawrence Livermore National Laboratory.
9. UNR (University of Nevada, Reno), (2010). “Safety,
Health, and Ventilation Cost Optimization with
Simulation and Control.” Phase 1 report, prepared for
NIOSH under grant number 200-2009-30157.