6
During the ventilation survey, a smoke tube was
utilized to visualize the flow patterns in the study mine.
Figure 6 presents a representation of the airflow patterns
derived from the established CFD model, utilizing input
data acquired during the winter ventilation survey. During
this survey, airflow directions were determined at 33 sta-
tions (refer to Figure 1). Among these 33 stations, the
CFD model accurately predicted airflow directions at 24
locations. In five stations where measured air velocities
fell below 0.5 m/s, the CFD model estimated reverse air-
flow directions. In four stations, the CFD model showed
air circulations, preventing a direct comparison with field
measurements.
Figure 7 illustrates the correlation between the mass-
weighted average velocity magnitude as calculated by the
CFD model and the actual air velocity measured during
the second ventilation survey at 50 different locations. The
analysis revealed a lower R-square value of 0.57 in the sec-
ond ventilation survey. This decrease could be linked to the
fact that the mine was actively producing during the second
survey. During this period, haul trucks were observed enter-
ing through the intake-1 and exiting through the intake-2.
With the validation of the model completed, it is now ready
for assessing the effects of in-place stone stoppings layouts
on the efficiency of face ventilation and air recirculation at
crosscuts between exhaust and intake entries.
ASSESSMENT OF THE INFLUENCE OF
STONE STOPPINGS ON VENTILATION
EFFICIENCY
The primary aim of this research paper is to explore how
different arrangements of in-place stone stoppings impact
the efficiency of face ventilation and the air recirculation
at the crosscuts between exhaust and intake entries. Two
configurations for these in-place stone stoppings, referred
to as Layout-I and Layout-II, were assumed and conducted
simulations using the validated CFD models. Layout-I is
shown in Figure 8, featuring a shorter in-place stone stop-
ping, while Figure 9 illustrates Layout-II, which incorpo-
rates a longer in-place stone stopping.
The model setup closely aligns with the description
provided in the previous section, with a few exceptions
based on findings from the late spring ventilation survey:
Figure 5. The correlation between the CFD model’s average
velocity and the measured winter ventilation air velocity
Figure 6. CFD calculations of airflow patterns within the
study utilizing winter ventilation survey data as the input for
the CFD model
During the ventilation survey, a smoke tube was
utilized to visualize the flow patterns in the study mine.
Figure 6 presents a representation of the airflow patterns
derived from the established CFD model, utilizing input
data acquired during the winter ventilation survey. During
this survey, airflow directions were determined at 33 sta-
tions (refer to Figure 1). Among these 33 stations, the
CFD model accurately predicted airflow directions at 24
locations. In five stations where measured air velocities
fell below 0.5 m/s, the CFD model estimated reverse air-
flow directions. In four stations, the CFD model showed
air circulations, preventing a direct comparison with field
measurements.
Figure 7 illustrates the correlation between the mass-
weighted average velocity magnitude as calculated by the
CFD model and the actual air velocity measured during
the second ventilation survey at 50 different locations. The
analysis revealed a lower R-square value of 0.57 in the sec-
ond ventilation survey. This decrease could be linked to the
fact that the mine was actively producing during the second
survey. During this period, haul trucks were observed enter-
ing through the intake-1 and exiting through the intake-2.
With the validation of the model completed, it is now ready
for assessing the effects of in-place stone stoppings layouts
on the efficiency of face ventilation and air recirculation at
crosscuts between exhaust and intake entries.
ASSESSMENT OF THE INFLUENCE OF
STONE STOPPINGS ON VENTILATION
EFFICIENCY
The primary aim of this research paper is to explore how
different arrangements of in-place stone stoppings impact
the efficiency of face ventilation and the air recirculation
at the crosscuts between exhaust and intake entries. Two
configurations for these in-place stone stoppings, referred
to as Layout-I and Layout-II, were assumed and conducted
simulations using the validated CFD models. Layout-I is
shown in Figure 8, featuring a shorter in-place stone stop-
ping, while Figure 9 illustrates Layout-II, which incorpo-
rates a longer in-place stone stopping.
The model setup closely aligns with the description
provided in the previous section, with a few exceptions
based on findings from the late spring ventilation survey:
Figure 5. The correlation between the CFD model’s average
velocity and the measured winter ventilation air velocity
Figure 6. CFD calculations of airflow patterns within the
study utilizing winter ventilation survey data as the input for
the CFD model