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Distributions of airflow in four rectangular section roadways with different supporting methods in underground coal mines
Tunnelling and Underground Space Technology 46 (2015) 85–93
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Tunnelling and Underground Space Technology journal homepage: www.elsevier.com/locate/tust
Distributions of airflow in four rectangular section roadways with different supporting methods in underground coal mines Yonghao Luo a,⇑, Yangsheng Zhao a, Yi Wang b, Mingbo Chi a, Haibo Tang a, Shaoqing Wang a a b
Mining Technology Institute, Taiyuan University of Technology, Taiyuan, Shanxi Province 030024, China College of Mining Engineering, Taiyuan University of Technology, Taiyuan, Shanxi Province 030024, China
a r t i c l e
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Article history: Received 1 April 2014 Received in revised form 18 October 2014 Accepted 19 November 2014
Keywords: Coal mine Rectangular section roadway Distribution of airflow Supporting method
a b s t r a c t A study has been carried out in four rectangular section roadways with different supporting methods in Yuwu Coal Company (a longwall mine), by measurements of airflow velocities in cross-section of the roadways. The asymmetrical distributions of airflow in each roadway section was obtained. The paper analyzes the low airflow velocity region of roadways through the drawing of the distributions of airflow in each roadway section. The supporting methods influence the low airflow velocity region around the roof and wall of roadways. It is shown that the low airflow velocity region increase with surface roughness of the roof and wall. The high airflow velocity region was located around the floor of the roadway with rough roof and wall. However, in the roadways with smooth roof and wall the high airflow velocity region was located around the center of section. The risk assessment should be carried out in the low airflow velocity region in the roadway with rough roof and wall. To ensure the safety of coal mining, higher volume of air intake or more smooth roof and wall of the roadways should be achieved in a dangerous zone. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction The mine’s ventilation system should provide miners with sufficient fresh air and ensure a safe and productive environment. In order to prevent explosion of methane and gas poisoning, the distributions of airflow need to be analyze. The airflow could carry off the toxic gases, CO and NO2, but the concentration would be high in the low airflow velocity region. The air quantity and average air velocity are the parameters measured in roadways and the range of average air velocity is regulated. However, the regulation of the distributions of airflow in roadways has not found. A number of studies have been carried out on underground mine air flow behaviors. Herdeen and Sullivan (1993) were among the first who introduced Computational Fluid Dynamics (CFDs) to investigate airflow ventilation in mines; however, their model was not validated against experimental data. Then there were many researches of ventilation by means of 3D, computational methods taking into account time and validating these models by measurement programmes. Uchino and Inoue (1997) developed CFD model for auxiliary ventilation and validated the model against blowing ventilation
⇑ Corresponding author. Tel.: +86 13546350343. E-mail address: [email protected] (Y. Luo). http://dx.doi.org/10.1016/j.tust.2014.11.005 0886-7798/Ó 2014 Elsevier Ltd. All rights reserved.
data. Moloney and Lowndes (1999) drew a comparison of measured underground air velocities and air flows simulated by CFDs. Suglo and Frimpong (2001) used empirical methods to assess the efficiencies of auxiliary ventilation systems. Toraño et al. (2002) created a program for calculating ventilation in tunneling works based on an explicit method. Wala et al. (2003) validated their CFD model for longwall ventilation with lab scale data for methane concentration. Parra et al. (2005) given a numerical and experimental analysis of different ventilation systems in deep mines. A CFDs study on ventilation flow paths in longwall gobs has been conducted by Yuan et al. (2006). Hargreaves and Lowndes (2007) used CFD to model the underground mine air flow behavior and ventilation airflow patterns. Onder and Cevik (2008) developed a predictive model of the volume flow rate reaching the end of a leaky ventilation duct for a simple auxiliary ventilation system using multiple regression analysis. Wang et al. (2009) proposed a 3D unsteady quasi-single phase models to optimize the ventilation time with different tunneling lengths and analyzed the distributions of airflow, CO and dust in the diversion tunnel. The prediction by the present model for airflow in a diversion tunnel is confirmed by the experimental values reported by Nakayama (1998). Methane emissions both in longwall mining and in dead-end roadways vary considerably according to the type of coal and the work carried out at the face (Karacan, 2008).
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Fig. 1. Velocity distribution (m/s) in main ventilation roadway of N1102 (bolting with wire mesh).
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(A) Layout of the analytic paths in the crosssection of main ventilation roadway of N1102.
(D) Evolution of airflow velocities in direction c according to the distance from the boundary.
(B) Evolution of airflow velocities in direction a according to the distance from the boundary.
(E) Evolution of airflow velocities in direction d according to the distance from the boundary.
(C) Evolution of airflow velocities in direction b according to the distance from the boundary.
(F) Evolution of airflow velocities in direction e according to the distance from the boundary.
Fig. 2. Analysis diagram of main ventilation roadway of N1102.
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Fig. 3. Velocity distribution (m/s) in Northwest air-return rise roadway (bolting and shotcreting).
Toraño et al. (2009) conducted studies in a roadway excavated in a coalbed of a deep underground coal mine located in Northern Spain (Hullera Vasco Leonesa SA), by both airflow velocity and methane concentration measurements and taken airflow velocity and methane concentration measurements in 5 points of 6 crosssections at 0, 3, 6, 12, 24 and 60 m respectively from the face. Liu et al. (2009) developed 3D multiphase flow model for longwall mining; the distribution of air with and without vapor were compared. Kun et al. (2010) adopted a 3-D transient single phase model and analyzed the influence of branch tunnels on main underground powerhouse construction ventilation. Toraño et al. (2011) presented a study of dust behavior in two auxiliary ventilations systems by Computational Fluid Dynamics (CFDs) models, taking into account the influence of time. Wang et al. (2011) evaluated the effectiveness of air curtain for dust control in long wall shearer using CFD model. Se et al. (2012) used CFD to investigate the effect of an active fan group on the airflow structure and temperature distribution in a tunnel with varied fire sources. Gao et al. (2012) used Large Eddy Simulation to study the dispersion of fire-induced smoke in a subway station and the influence of natural and mechanical ventilation was investigated. Torno et al. (2013) carried out a study in a coal heading, excavated by drilling and blasting in a deep underground mine located in Northern Spain (Hullera Vasco Leonesa SA), by measurements of blasting gases, CO and NO2, in three cross-sections of the heading located at 20, 30, and 40 m from the heading face. Xu et al. (2013) described a simulation of tracer gas distribution in a simplified laboratory experimental mine with the ventilation controls in various states and taken tracer gas measurements in laboratory experimental apparatus to validate the numerical model. However, numerical simulations are not as reliable and reproducible as their theoretical and computational basis would suggest. They often give differing results owing to the complexity of approximations and the number of parameters used (Gygi, 2013). The previous computational methods and measurement programmes were only within one region’s distributions of airflow and studies about different roadway’s airflow distribution with different supporting methods in underground coal mines are rare.
This study aims to investigate airflow distribution in different rectangular section roadways with different supporting methods in underground coal mines. The airflow distributions in four rectangular section roadways using different supporting methods, bolting with wire mesh, bolting and shotcreting, I-steel, bolting and shotcreting with smoothing, were measured. The low airflow velocity region of roadways were studied in quantitative analysis. A new measuring system on airflow velocity was used in this study. This method made more measure points in one section and investigated more roadways compared with other methods such as Wang et al. (2009), Toraño et al. (2009) and Torno et al. (2013). Some of the most useful measurements and discussions about the low airflow velocity region in the roadway are reported here. 2. Underground airflow measurements Yuwu Coal Company located in the province of Shanxi in the North of China, is an underground coal mine with five shafts connected between them. The annual coal production is 8 million tons and the proved exploitable coal reserves at the end of 2013 are 679 million tons. Stratigraphically, the coal basin is divided into 5 well-defined formations. The whole group is about 1200 m thick, formed about 500 million years ago. Permian System formation shows the best economic prospects and it provides the totality of the present coal production. No.3 coalbed in Stratigraphy of Shan-tung in formation of Permian System, varies in thickness from 5.00 to 7.25 m. The only mining technique is used longwall retreat. The aim of this research has been investigating the low airflow velocity region of rectangular section roadways using different supporting methods. Therefore the boundary layer and the turbulence not have been carefully researched. In this study, the source of air comes from North ventilation shaft and its exit is in North air-return shaft. A good repeatability could be obtained because the airflow in each measured roadways is stable. The airflow velocity measuring system cannot lead to explosion and could be used in underground coal mine with methane and coal dust. This measuring system could measure airflow velocity within 0.30–10.00 m/s and the error affected less than 0.10 m/s.
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(A) Layout of the analytic paths in the crosssection of Northwest air-return rise roadway.
(B) Evolution of airflow velocities in direction a according to the distance from the boundary.
(C) Evolution of airflow velocities in direction b according to the distance from the boundary.
(D) Evolution of airflow velocities in direction c according to the distance from the boundary.
(E) Evolution of airflow velocities in direction d according to the distance from the boundary.
(F) Evolution of airflow velocities in direction e according to the distance from the boundary.
Fig. 4. Analysis diagram of Northwest air-return rise roadway.
The cross-section of roadway was divided equally into 100 same small rectangular sections. The airflow velocity was measured in the center of each small rectangular section. The duration of the experimental investigation is 3 h in each cross-section. If there was a obstacle in the point, then the measurement would be canceled. The detailed arrangement of measure point could be seen in the following section.
3. Results and discussion 3.1. Experimental measurements in four rectangular section roadways Fig. 1 shows the airflow velocity distribution (m/s) in main ventilation roadway of N1102 (bolting with wire mesh). The cross-section of the roadway with its length of 4.7 m and its high of 3.2 m is a rectangular section at 317 m from the entrance of airflow. The
main ventilation roadway of N1102 with a total length of 1174 m in the west of the mine area was used the supporting method of bolting with wire mesh and cables was used in the roof. There are some physical objects in the roadway: the gas drainage duct, overhead monorail and electric cables. The detailed descriptions of the physical objects are shown in Fig. 1. Average degree and height of concave–convex boundaries can be 150–300 mm in this roadway. The high airflow velocity region was located around the floor of the roadway section and the two sides were generally symmetrical. The average value of airflow velocity crossing the roadway cross-section was 2.46 m/s. Fig. 2(A) depicts the layout of the analytic paths (a, b, c, d and e) in the cross-section of main ventilation roadway of N1102. It can be seen that some regions with velocities lower than other regions, are produced at the boundary. These lower airflow velocity regions may be dangerous since gases and dust accumulate in them
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Fig. 5. Velocity distribution (m/s) in No.2 northeast ventilation and conveyor connection roadway (I-steel).
(Toraño et al., 2011). Dave et al. (2013) calculated the boundary layer thickness based on the location where the mean streamwise velocity is 99% of the freestream velocity. In this paper, the low airflow velocity region means that the value of airflow velocity is lower than 80% of the highest velocity in the path region. The risk increases with the scope of low airflow velocity region. The airflow velocities were rising in direction a according to the distance from the boundary. When the value of airflow velocity reached 80% (2.51 m/s) of the highest velocity in the path a region, the distance reached 61% (1.306 m) of the total distance (Fig. 2(B)). The airflow velocities were rising at first, while reached the extreme point became lower, then were rising again in direction b according to the distance from the boundary. When the value of airflow velocity reached 80% (2.50 m/s) of the highest velocity in the path b region, the distance reached 46% (1.735 m) of the total distance (Fig. 2(C)). The airflow velocities were rising in direction c according to the distance from the boundary. When the value of airflow velocity reached 80% (2.54 m/s) of the highest velocity in the path c region, the distance reached 47% (1.778 m) of the total distance (Fig. 2(D)). The airflow velocities were rising rapidly, then slow down, in direction d according to the distance from the boundary. When the value of airflow velocity reached 80% (2.50 m/s) of the highest velocity in the path d region, the distance reached 15% (0.217 m) of the total distance (Fig. 2(E)). The airflow velocities were rising rapidly at first, while reached the extreme point became lower, in direction e according to the distance from the boundary. When the value of airflow velocity reached 80% (2.70 m/s) of the highest velocity in the path e region, the distance reached 13% (0.182 m) of the total distance (Fig. 2(F)). Fig. 3 shows the airflow velocity distribution (m/s) in Northwest air-return rise roadway (bolting and shotcreting). The crosssection of the roadway with its length of 4.8 m and its high of 3.4 m is a rectangular section at 241 m from the entrance of airflow. The Northwest air-return rise roadway with a total length
of 3768 m in the northwest of the mine area was used the supporting method of bolting and shotcreting. There are some physical objects in the roadway: the gas drainage duct, electric cables. The detailed descriptions of the physical objects are shown in Fig. 3. Average degree and height of concave–convex boundaries can be 100–200 mm in this roadway. The high airflow velocity region was located around the floor of the roadway section and the two sides were generally symmetrical in this roadway. The average value of airflow velocity crossing the roadway cross-section was 1.80 m/s. Fig. 4(A) depicts the layout of the analytic paths (a, b, c, d and e) in the cross-section of Northwest air-return rise roadway. The airflow velocities were rising rapidly, then slow down, in direction a according to the distance from the boundary. When the value of airflow velocity reached 80% (1.89 m/s) of the highest velocity in the path a region, the distance reached 25% (0.543 m) of the total distance (Fig. 4(B)). The airflow velocities were rising rapidly at first, then slow down, then were rising again in direction b according to the distance from the boundary. When the value of airflow velocity reached 80% (1.66 m/s) of the highest velocity in the path b region, the distance reached 67% (1.817 m) of the total distance (Fig. 4(C)). The airflow velocities were rising rapidly at first, then slow down and rising, then dropping, in direction c according to the distance from the boundary. When the value of airflow velocity reached 80% (1.99 m/s) of the highest velocity in the path c region, the distance reached 36% (0.963 m) of the total distance (Fig. 4(D)). The airflow velocities were rising rapidly, then slow down, in direction d according to the distance from the boundary. When the value of airflow velocity reached 80% (1.66 m/s) of the highest velocity in the path d region, the distance reached 58% (0.880 m) of the total distance (Fig. 4(E)). The airflow velocities were rising rapidly at first, then fluctuating, in direction e according to the distance from the boundary. When the value of airflow velocity reached 80% (1.91 m/s) of the
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(A) Layout of the analytic paths in the crosssection of No.2 northeast ventilation and conveyor connection roadway.
(D) Evolution of airflow velocities in direction c according to the distance from the boundary.
(B) Evolution of airflow velocities in direction a according to the distance from the boundary.
(E) Evolution of airflow velocities in direction d according to the distance from the boundary.
(C) Evolution of airflow velocities in direction b according to the distance from the boundary.
(F) Evolution of airflow velocities in direction e according to the distance from the boundary.
Fig. 6. Analysis diagram of No.2 northeast ventilation and conveyor connection roadway.
highest velocity in the path e region, the distance reached 6% (0.127 m) of the total distance (Fig. 4(F)). Fig. 5 shows the airflow velocity distribution (m/s) in No.2 northeast ventilation and conveyor connection roadway (I-steel). The cross-section of the roadway with its topline of 3.79 m, baseline of 4.16 m, and its high of 3.82 m is a trapezoid section at 87 m from the entrance of airflow. To compare with other rectangular section roadways, this roadway was analyzed as a rectangular section roadway. The No.2 northeast ventilation and conveyor connection roadway with a total length of 126 m in the northwest of the mine area was used the supporting method of I-steel with an interval of 0.84 m. There are some electric cables in the roadway. The detailed descriptions of the electric cables are shown in Fig. 5.
The high airflow velocity region was located around the roof of the roadway section and the two sides were generally symmetrical in this roadway. The average value of airflow velocity crossing the roadway cross-section was 1.58 m/s. Fig. 6(A) depicts the layout of the analytic paths (a, b, c, d and e) in the cross-section of No.2 northeast ventilation and conveyor connection roadway. The airflow velocities were rising rapidly, then fluctuating, in direction a according to the distance from the boundary. When the value of airflow velocity reached 80% (1.71 m/s) of the highest velocity in the path a region, the distance reached 26% (0.493 m) of the total distance (Fig. 6(B)). The airflow velocities were rising rapidly at first, then slow down, in direction b according to the distance from the boundary.
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Fig. 7. Velocity distribution (m/s) in Air measuring station (bolting and shotcreting with smoothing).
When the value of airflow velocity reached 80% (1.64 m/s) of the highest velocity in the path b region, the distance reached 45% (1.238 m) of the total distance (Fig. 6(C)). The airflow velocities were rising rapidly at first, then dropping slowly, then rising, in direction c according to the distance from the boundary. When the value of airflow velocity reached 80% (1.61 m/ s) of the highest velocity in the path c region, the distance reached 58% (1.092 m) of the total distance (Fig. 6(D)). The airflow velocities were rising rapidly, then dropping, then rising slowly, in direction d according to the distance from the boundary. When the value of airflow velocity reached 80% (1.86 m/s) of the highest velocity in the path d region, the distance reached 23% (0.387 m) of the total distance (Fig. 6(E)). The airflow velocities were rising rapidly at first, then slow down, in direction e according to the distance from the boundary. When the value of airflow velocity reached 80% (1.61 m/s) of the highest velocity in the path e region, the distance reached 53% (0.908 m) of the total distance (Fig. 6(F)). Fig. 7 shows the airflow velocity distribution (m/s) in Air measuring station (bolting and shotcreting with smoothing). The crosssection of the roadway with its length of 4.0 m and its high of 3.0 m is a rectangular section at 92 m from the entrance of airflow. The Air measuring station with a total length of 178 m in the west of the mine area was used the supporting method of bolting and shotcreting with smoothing. There is a gas drainage duct in the roadway. The detailed descriptions of the gas drainage duct are shown in Fig. 7. Average degree and height of concave–convex boundaries can be 1–10 mm in this roadway. The high airflow velocity region was located around the center of the roadway section and the two sides were generally symmetrical in this roadway. The average value of airflow velocity crossing the roadway cross-section was 2.02 m/s. Fig. 8(A) depicts the layout of the analytic paths (a, b, c, d and e) in the cross-section of Air measuring station. The airflow velocities were rising rapidly, then slow down, in direction a according to the distance from the boundary. When the value of airflow velocity reached 80% (2.08 m/s) of the highest velocity in the path a region, the distance reached 17% (0.303 m) of the total distance (Fig. 8(B)).
The airflow velocities were rising rapidly at first, then slow down, in direction b according to the distance from the boundary. When the value of airflow velocity reached 80% (2.02 m/s) of the highest velocity in the path b region, the distance reached 41% (0.919 m) of the total distance (Fig. 8(C)). The airflow velocities were rising rapidly at first, then steady, in direction c according to the distance from the boundary. When the value of airflow velocity reached 80% (2.03 m/s) of the highest velocity in the path c region, the distance reached 28% (0.636 m) of the total distance (Fig. 8(D)). The airflow velocities were rising rapidly, then slow down, then rising, in direction d according to the distance from the boundary. When the value of airflow velocity reached 80% (2.02 m/s) of the highest velocity in the path d region, the distance reached 16% (0.217 m) of the total distance (Fig. 8(E)). The airflow velocities were rising rapidly at first, then slow down, in direction e according to the distance from the boundary. When the value of airflow velocity reached 80% (2.14 m/s) of the highest velocity in the path e region, the distance reached 30% (0.406 m) of the total distance (Fig. 8(F)). 3.2. Analysis and discussion Airflow velocity measurements, in 100 points of the crosssections, were taken using the same methods. And the airflow velocity in different parts of the cross-section were measured in the same way. Therefore, the measure results could give an objective distribution of airflow velocity in the cross-section. By comparing the distribution of airflow velocity in Figs. 1, 3, 5 and 7, it can be observed that the high airflow velocity region was located around the floor of the roadway with rough roof and wall, but in the roadways with smooth roof and wall was located around the center of section. Because of the surface roughness of floors in four different roadways was similarity, the surface roughness of wall and roof is the most important factor for this phenomenon. The results show that the supporting methods affect the distributions of airflow velocity through the surface roughness of wall and roof. Table 1 shows the percentages of the low airflow velocity distance in total distance when the value of airflow velocity reached
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(A) Layout of the analytic paths in the crosssection of Air measuring station.
(D) Evolution of airflow velocities in direction c according to the distance from the boundary.
(B) Evolution of airflow velocities in direction a according to the distance from the boundary.
(E) Evolution of airflow velocities in direction d according to the distance from the boundary.
(C) Evolution of airflow velocities in direction b according to the distance from the boundary.
(F) Evolution of airflow velocities in direction e according to the distance from the boundary.
Fig. 8. Analysis diagram of Air measuring station.
Table 1 Percentages of the low velocity distance in total distance of different paths. Supporting methods
Average velocity (m/s)
Path a (%)
Path b (%)
Path c (%)
Path d (%)
Path e (%)
Bolting with wire mesh Bolting and shotcreting I-steel Bolting and shotcreting with smoothing
2.46 1.80 1.58 2.02
61 25 26 17
46 67 45 41
47 36 58 28
15 58 23 16
13 6 53 30
80% of the highest velocity in the paths a, b, c, d and e regions. It can be seen in Figs. 2(A), 4(A), 6(A) and 8(A) that paths a, b, c, d and e reflect the influence of wall, wall and roof, wall and floor, roof and floor, respectively, on the distribution of airflow. The influence of floor could be reflected in paths c and e. The surface roughness of floors in four different roadways was similarity, but there was a difference in the percentages of the low velocity distance in total distance. It is due to the higher value of average airflow velocity could lead to boundary layer becoming thinner.
The influence of roof and wall could be reflected in paths a, b, c and d. The percentages of the low velocity distance in total distance increase with surface roughness in these paths. It can be seen in Table 1 that the percentage in path a in the roadway with bolting with wire mesh supporting method is highest, though it has the highest value of average airflow velocity. This indicated that the surface roughness has more important influence on the distribution of airflow velocity than average airflow velocity in this study.
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The dimension of the rectangular section roadway could also influence the distribution of airflow velocity. To eliminate the influence of the dimension, the sections which we studied generally have the same dimensions. However, it is very difficult to find four rectangular section roadways with the same dimensions and different supporting methods in underground coal mines. Therefore, CFD models and laboratory studies should be developed to solve the problem in the future. 4. Conclusions To know the behavior of ventilation airflow in the roadways is very important for the safety of workers in underground mines and other underground works. Studies on the needs of distributions of airflow in rectangular section roadways with different supporting methods in underground coal mines by conventional methods are necessary. Both smoothing and average velocity could influence the distribution of airflow. The supporting methods influence the low airflow velocity region around the roof and wall of roadways. It is shown that the low airflow velocity region increase with surface roughness of the roof and wall. Increasing the value of average airflow velocity could lead to low airflow velocity region decreasing. The high airflow velocity region was located around the floor of the roadway with rough roof and wall. However, in the roadways with smooth roof and wall the high airflow velocity region was located around the center of section. The risk assessment should be carried out in the low airflow velocity region in the roadway with rough roof and wall. To ensure the safety of coal mining, higher volume of air intake or more smooth roof and wall of the roadways should be achieved in a dangerous zone. Acknowledgments This work was financed by the National Natural Science Foundation of China (No. 51104105). We would like to thank Yuwu Coal Company (China) for the access to their underground mines and for technical supporting this study. References Dave, N., Azih, C., Yaras, M.I., 2013. A DNS study on the effects of convex streamwise curvature on coherent structures in a temporally-developing turbulent boundary layer with supercritical water. Int. J. Heat Fluid Flow 44, 635–643. Gao, R., Li, A., Hao, X., Lei, W., Deng, B., 2012. Prediction of the spread of smoke in a huge transit terminal subway station under six different fire scenarios. Tunn. Undergr. Space Technol. 31, 128–138.
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Gygi, F., 2013. Sharing data in materials science. Nature 503, 464. Hargreaves, D.M., Lowndes, I.S., 2007. The computational modeling of the ventilation flows within a rapid development drivage. Tunn. Undergr. Space Technol. 22 (2), 150–160. Herdeen, J., Sullivan, P. 1993. The application of CFD for evaluation of dust suppression and auxiliary ventilation systems used with continuous miners. In: Proceeding of the 6th US Mine Ventilation Symposium, SME, Littleton, pp. 293– 297. Karacan, C.O., 2008. Modelling and prediction of ventilation methane emissions of U.S. longwall mines using supervised artificial neural networks. Int. J. Coal Geol. 73, 371–387. Kun, H., Wang, X.L., Zhou, Z.Y., Zhou, S.S., 2010. Influence of branch tunnels on CO diffusion simulation of main underground powerhouse construction ventilation. In: 2010 3rd International Conference on Biomedical Engineering and Informatics, pp. 2654–2657. Liu, G., Gao, F., Ji, M.L., Xing, G., 2009. Investigation of the ventilation simulation model in mine based on multiphase flow. Procedia Earth Planet. Sci. 1, 491–496. Moloney, K.W., Lowndes, I.S., 1999. Comparison of measured underground air velocities and air flows simulated by computational fluid dynamics. Trans. Inst. Min. Metall. (Sec. A: Min. Ind.) 108, 105–114. Nakayama, 1998. In-situ measurement and simulation bu CFD of methane gas distribution at a heading faces. Shinsen-to-Sozai 114 (11), 769–775. Onder, M., Cevik, E., 2008. Statistical model for the volume rate reaching the end of ventilation duct. Tunn. Undergr. Space Technol. 23, 179–184. Parra, M.T., Villafruela, J.M., Castro, F., Méndez, C., 2005. Numerical and experimental analysis of different ventilation systems in deep mines. Build. Environ. 41, 87–93. Se, C.M.K., Lee, E.W.M., Lai, A.C.K., 2012. Impact of location of jet fan on airflow structure in tunnel fire. Tunn. Undergr. Space Technol. 27 (1), 30–40. Suglo, R.S., Frimpong, S., 2001. Assessment of the efficiencies of auxiliary ventilation systems using empirical methods. Can. Inst. Min. Metall. Bull., 67–71 (September). Toraño, J., Rodríguez, R., Cuesta, A., Diego, I., 2002. A computer program for calculating ventilation in tunneling works based on an explicit method. Tunn. Undergr. Space Technol. 17 (3), 227–236. Toraño, J., Torno, S., Menendez, M., Gent, M.R., Velasco, J., 2009. Models of methane behavior in auxiliary ventilation of underground coal mining. Int. J. Coal Geol. 80, 35–43. Toraño, J., Torno, S., Menendez, M., Gent, M., 2011. Auxiliary ventilation in mining roadways driven with roadheaders: validated CFD modelling of dust behavior. Tunn. Undergr. Space Technol. 26, 201–210. Torno, S., Toraño, J., Ulecia, M., Allende, C., 2013. Conventional and numerical models of blasting gas behavior in auxiliary ventilation of mining headings. Tunn. Undergr. Space Technol. 34, 73–81. Uchino, K., Inoue, M., 1997. Auxiliary ventilation at a heading of a face by a fan. In: Proceeding of the 6th US Mine Ventilation Symposium, SME, Littleton, pp. 493– 496. Wala, A., Jacob, J., Brown, J., Huang, G., 2003. New approaches to mine-face ventilation. Min. Eng. 55 (3), 25–30. Wang, X.L., Liu, X.P., Sun, Y.F., An, J., Zhang, J., Chen, H.C., 2009. Construction schedule simulation of a diversion tunnel based on the optimized ventilation time. J. Hazard. Mater. 165, 933–943. Wang, P., Feng, T., Liu, R., 2011. Numerical simulation of dust distribution at a fully mechanized face under the isolation effect of an air curtain. Min. Sci. Technol. (China) 21, 65–69. Xu, G., Luxbacher, K.D., Ragab, S., Schafrik, S., 2013. Tunn. Undergr. Space Technol. 33, 1–11. Yuan, L., Smith, A.C., Brune, J.F., 2006. Computational fluid dynamics study on ventilation flow paths in longwall gobs. In: 11th US/North American Mine Ventilation Symposium, State College, PA, pp. 591–598.
Contents lists available at ScienceDirect
Tunnelling and Underground Space Technology journal homepage: www.elsevier.com/locate/tust
Distributions of airflow in four rectangular section roadways with different supporting methods in underground coal mines Yonghao Luo a,⇑, Yangsheng Zhao a, Yi Wang b, Mingbo Chi a, Haibo Tang a, Shaoqing Wang a a b
Mining Technology Institute, Taiyuan University of Technology, Taiyuan, Shanxi Province 030024, China College of Mining Engineering, Taiyuan University of Technology, Taiyuan, Shanxi Province 030024, China
a r t i c l e
i n f o
Article history: Received 1 April 2014 Received in revised form 18 October 2014 Accepted 19 November 2014
Keywords: Coal mine Rectangular section roadway Distribution of airflow Supporting method
a b s t r a c t A study has been carried out in four rectangular section roadways with different supporting methods in Yuwu Coal Company (a longwall mine), by measurements of airflow velocities in cross-section of the roadways. The asymmetrical distributions of airflow in each roadway section was obtained. The paper analyzes the low airflow velocity region of roadways through the drawing of the distributions of airflow in each roadway section. The supporting methods influence the low airflow velocity region around the roof and wall of roadways. It is shown that the low airflow velocity region increase with surface roughness of the roof and wall. The high airflow velocity region was located around the floor of the roadway with rough roof and wall. However, in the roadways with smooth roof and wall the high airflow velocity region was located around the center of section. The risk assessment should be carried out in the low airflow velocity region in the roadway with rough roof and wall. To ensure the safety of coal mining, higher volume of air intake or more smooth roof and wall of the roadways should be achieved in a dangerous zone. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction The mine’s ventilation system should provide miners with sufficient fresh air and ensure a safe and productive environment. In order to prevent explosion of methane and gas poisoning, the distributions of airflow need to be analyze. The airflow could carry off the toxic gases, CO and NO2, but the concentration would be high in the low airflow velocity region. The air quantity and average air velocity are the parameters measured in roadways and the range of average air velocity is regulated. However, the regulation of the distributions of airflow in roadways has not found. A number of studies have been carried out on underground mine air flow behaviors. Herdeen and Sullivan (1993) were among the first who introduced Computational Fluid Dynamics (CFDs) to investigate airflow ventilation in mines; however, their model was not validated against experimental data. Then there were many researches of ventilation by means of 3D, computational methods taking into account time and validating these models by measurement programmes. Uchino and Inoue (1997) developed CFD model for auxiliary ventilation and validated the model against blowing ventilation
⇑ Corresponding author. Tel.: +86 13546350343. E-mail address: [email protected] (Y. Luo). http://dx.doi.org/10.1016/j.tust.2014.11.005 0886-7798/Ó 2014 Elsevier Ltd. All rights reserved.
data. Moloney and Lowndes (1999) drew a comparison of measured underground air velocities and air flows simulated by CFDs. Suglo and Frimpong (2001) used empirical methods to assess the efficiencies of auxiliary ventilation systems. Toraño et al. (2002) created a program for calculating ventilation in tunneling works based on an explicit method. Wala et al. (2003) validated their CFD model for longwall ventilation with lab scale data for methane concentration. Parra et al. (2005) given a numerical and experimental analysis of different ventilation systems in deep mines. A CFDs study on ventilation flow paths in longwall gobs has been conducted by Yuan et al. (2006). Hargreaves and Lowndes (2007) used CFD to model the underground mine air flow behavior and ventilation airflow patterns. Onder and Cevik (2008) developed a predictive model of the volume flow rate reaching the end of a leaky ventilation duct for a simple auxiliary ventilation system using multiple regression analysis. Wang et al. (2009) proposed a 3D unsteady quasi-single phase models to optimize the ventilation time with different tunneling lengths and analyzed the distributions of airflow, CO and dust in the diversion tunnel. The prediction by the present model for airflow in a diversion tunnel is confirmed by the experimental values reported by Nakayama (1998). Methane emissions both in longwall mining and in dead-end roadways vary considerably according to the type of coal and the work carried out at the face (Karacan, 2008).
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Fig. 1. Velocity distribution (m/s) in main ventilation roadway of N1102 (bolting with wire mesh).
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(A) Layout of the analytic paths in the crosssection of main ventilation roadway of N1102.
(D) Evolution of airflow velocities in direction c according to the distance from the boundary.
(B) Evolution of airflow velocities in direction a according to the distance from the boundary.
(E) Evolution of airflow velocities in direction d according to the distance from the boundary.
(C) Evolution of airflow velocities in direction b according to the distance from the boundary.
(F) Evolution of airflow velocities in direction e according to the distance from the boundary.
Fig. 2. Analysis diagram of main ventilation roadway of N1102.
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Fig. 3. Velocity distribution (m/s) in Northwest air-return rise roadway (bolting and shotcreting).
Toraño et al. (2009) conducted studies in a roadway excavated in a coalbed of a deep underground coal mine located in Northern Spain (Hullera Vasco Leonesa SA), by both airflow velocity and methane concentration measurements and taken airflow velocity and methane concentration measurements in 5 points of 6 crosssections at 0, 3, 6, 12, 24 and 60 m respectively from the face. Liu et al. (2009) developed 3D multiphase flow model for longwall mining; the distribution of air with and without vapor were compared. Kun et al. (2010) adopted a 3-D transient single phase model and analyzed the influence of branch tunnels on main underground powerhouse construction ventilation. Toraño et al. (2011) presented a study of dust behavior in two auxiliary ventilations systems by Computational Fluid Dynamics (CFDs) models, taking into account the influence of time. Wang et al. (2011) evaluated the effectiveness of air curtain for dust control in long wall shearer using CFD model. Se et al. (2012) used CFD to investigate the effect of an active fan group on the airflow structure and temperature distribution in a tunnel with varied fire sources. Gao et al. (2012) used Large Eddy Simulation to study the dispersion of fire-induced smoke in a subway station and the influence of natural and mechanical ventilation was investigated. Torno et al. (2013) carried out a study in a coal heading, excavated by drilling and blasting in a deep underground mine located in Northern Spain (Hullera Vasco Leonesa SA), by measurements of blasting gases, CO and NO2, in three cross-sections of the heading located at 20, 30, and 40 m from the heading face. Xu et al. (2013) described a simulation of tracer gas distribution in a simplified laboratory experimental mine with the ventilation controls in various states and taken tracer gas measurements in laboratory experimental apparatus to validate the numerical model. However, numerical simulations are not as reliable and reproducible as their theoretical and computational basis would suggest. They often give differing results owing to the complexity of approximations and the number of parameters used (Gygi, 2013). The previous computational methods and measurement programmes were only within one region’s distributions of airflow and studies about different roadway’s airflow distribution with different supporting methods in underground coal mines are rare.
This study aims to investigate airflow distribution in different rectangular section roadways with different supporting methods in underground coal mines. The airflow distributions in four rectangular section roadways using different supporting methods, bolting with wire mesh, bolting and shotcreting, I-steel, bolting and shotcreting with smoothing, were measured. The low airflow velocity region of roadways were studied in quantitative analysis. A new measuring system on airflow velocity was used in this study. This method made more measure points in one section and investigated more roadways compared with other methods such as Wang et al. (2009), Toraño et al. (2009) and Torno et al. (2013). Some of the most useful measurements and discussions about the low airflow velocity region in the roadway are reported here. 2. Underground airflow measurements Yuwu Coal Company located in the province of Shanxi in the North of China, is an underground coal mine with five shafts connected between them. The annual coal production is 8 million tons and the proved exploitable coal reserves at the end of 2013 are 679 million tons. Stratigraphically, the coal basin is divided into 5 well-defined formations. The whole group is about 1200 m thick, formed about 500 million years ago. Permian System formation shows the best economic prospects and it provides the totality of the present coal production. No.3 coalbed in Stratigraphy of Shan-tung in formation of Permian System, varies in thickness from 5.00 to 7.25 m. The only mining technique is used longwall retreat. The aim of this research has been investigating the low airflow velocity region of rectangular section roadways using different supporting methods. Therefore the boundary layer and the turbulence not have been carefully researched. In this study, the source of air comes from North ventilation shaft and its exit is in North air-return shaft. A good repeatability could be obtained because the airflow in each measured roadways is stable. The airflow velocity measuring system cannot lead to explosion and could be used in underground coal mine with methane and coal dust. This measuring system could measure airflow velocity within 0.30–10.00 m/s and the error affected less than 0.10 m/s.
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(A) Layout of the analytic paths in the crosssection of Northwest air-return rise roadway.
(B) Evolution of airflow velocities in direction a according to the distance from the boundary.
(C) Evolution of airflow velocities in direction b according to the distance from the boundary.
(D) Evolution of airflow velocities in direction c according to the distance from the boundary.
(E) Evolution of airflow velocities in direction d according to the distance from the boundary.
(F) Evolution of airflow velocities in direction e according to the distance from the boundary.
Fig. 4. Analysis diagram of Northwest air-return rise roadway.
The cross-section of roadway was divided equally into 100 same small rectangular sections. The airflow velocity was measured in the center of each small rectangular section. The duration of the experimental investigation is 3 h in each cross-section. If there was a obstacle in the point, then the measurement would be canceled. The detailed arrangement of measure point could be seen in the following section.
3. Results and discussion 3.1. Experimental measurements in four rectangular section roadways Fig. 1 shows the airflow velocity distribution (m/s) in main ventilation roadway of N1102 (bolting with wire mesh). The cross-section of the roadway with its length of 4.7 m and its high of 3.2 m is a rectangular section at 317 m from the entrance of airflow. The
main ventilation roadway of N1102 with a total length of 1174 m in the west of the mine area was used the supporting method of bolting with wire mesh and cables was used in the roof. There are some physical objects in the roadway: the gas drainage duct, overhead monorail and electric cables. The detailed descriptions of the physical objects are shown in Fig. 1. Average degree and height of concave–convex boundaries can be 150–300 mm in this roadway. The high airflow velocity region was located around the floor of the roadway section and the two sides were generally symmetrical. The average value of airflow velocity crossing the roadway cross-section was 2.46 m/s. Fig. 2(A) depicts the layout of the analytic paths (a, b, c, d and e) in the cross-section of main ventilation roadway of N1102. It can be seen that some regions with velocities lower than other regions, are produced at the boundary. These lower airflow velocity regions may be dangerous since gases and dust accumulate in them
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Fig. 5. Velocity distribution (m/s) in No.2 northeast ventilation and conveyor connection roadway (I-steel).
(Toraño et al., 2011). Dave et al. (2013) calculated the boundary layer thickness based on the location where the mean streamwise velocity is 99% of the freestream velocity. In this paper, the low airflow velocity region means that the value of airflow velocity is lower than 80% of the highest velocity in the path region. The risk increases with the scope of low airflow velocity region. The airflow velocities were rising in direction a according to the distance from the boundary. When the value of airflow velocity reached 80% (2.51 m/s) of the highest velocity in the path a region, the distance reached 61% (1.306 m) of the total distance (Fig. 2(B)). The airflow velocities were rising at first, while reached the extreme point became lower, then were rising again in direction b according to the distance from the boundary. When the value of airflow velocity reached 80% (2.50 m/s) of the highest velocity in the path b region, the distance reached 46% (1.735 m) of the total distance (Fig. 2(C)). The airflow velocities were rising in direction c according to the distance from the boundary. When the value of airflow velocity reached 80% (2.54 m/s) of the highest velocity in the path c region, the distance reached 47% (1.778 m) of the total distance (Fig. 2(D)). The airflow velocities were rising rapidly, then slow down, in direction d according to the distance from the boundary. When the value of airflow velocity reached 80% (2.50 m/s) of the highest velocity in the path d region, the distance reached 15% (0.217 m) of the total distance (Fig. 2(E)). The airflow velocities were rising rapidly at first, while reached the extreme point became lower, in direction e according to the distance from the boundary. When the value of airflow velocity reached 80% (2.70 m/s) of the highest velocity in the path e region, the distance reached 13% (0.182 m) of the total distance (Fig. 2(F)). Fig. 3 shows the airflow velocity distribution (m/s) in Northwest air-return rise roadway (bolting and shotcreting). The crosssection of the roadway with its length of 4.8 m and its high of 3.4 m is a rectangular section at 241 m from the entrance of airflow. The Northwest air-return rise roadway with a total length
of 3768 m in the northwest of the mine area was used the supporting method of bolting and shotcreting. There are some physical objects in the roadway: the gas drainage duct, electric cables. The detailed descriptions of the physical objects are shown in Fig. 3. Average degree and height of concave–convex boundaries can be 100–200 mm in this roadway. The high airflow velocity region was located around the floor of the roadway section and the two sides were generally symmetrical in this roadway. The average value of airflow velocity crossing the roadway cross-section was 1.80 m/s. Fig. 4(A) depicts the layout of the analytic paths (a, b, c, d and e) in the cross-section of Northwest air-return rise roadway. The airflow velocities were rising rapidly, then slow down, in direction a according to the distance from the boundary. When the value of airflow velocity reached 80% (1.89 m/s) of the highest velocity in the path a region, the distance reached 25% (0.543 m) of the total distance (Fig. 4(B)). The airflow velocities were rising rapidly at first, then slow down, then were rising again in direction b according to the distance from the boundary. When the value of airflow velocity reached 80% (1.66 m/s) of the highest velocity in the path b region, the distance reached 67% (1.817 m) of the total distance (Fig. 4(C)). The airflow velocities were rising rapidly at first, then slow down and rising, then dropping, in direction c according to the distance from the boundary. When the value of airflow velocity reached 80% (1.99 m/s) of the highest velocity in the path c region, the distance reached 36% (0.963 m) of the total distance (Fig. 4(D)). The airflow velocities were rising rapidly, then slow down, in direction d according to the distance from the boundary. When the value of airflow velocity reached 80% (1.66 m/s) of the highest velocity in the path d region, the distance reached 58% (0.880 m) of the total distance (Fig. 4(E)). The airflow velocities were rising rapidly at first, then fluctuating, in direction e according to the distance from the boundary. When the value of airflow velocity reached 80% (1.91 m/s) of the
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(A) Layout of the analytic paths in the crosssection of No.2 northeast ventilation and conveyor connection roadway.
(D) Evolution of airflow velocities in direction c according to the distance from the boundary.
(B) Evolution of airflow velocities in direction a according to the distance from the boundary.
(E) Evolution of airflow velocities in direction d according to the distance from the boundary.
(C) Evolution of airflow velocities in direction b according to the distance from the boundary.
(F) Evolution of airflow velocities in direction e according to the distance from the boundary.
Fig. 6. Analysis diagram of No.2 northeast ventilation and conveyor connection roadway.
highest velocity in the path e region, the distance reached 6% (0.127 m) of the total distance (Fig. 4(F)). Fig. 5 shows the airflow velocity distribution (m/s) in No.2 northeast ventilation and conveyor connection roadway (I-steel). The cross-section of the roadway with its topline of 3.79 m, baseline of 4.16 m, and its high of 3.82 m is a trapezoid section at 87 m from the entrance of airflow. To compare with other rectangular section roadways, this roadway was analyzed as a rectangular section roadway. The No.2 northeast ventilation and conveyor connection roadway with a total length of 126 m in the northwest of the mine area was used the supporting method of I-steel with an interval of 0.84 m. There are some electric cables in the roadway. The detailed descriptions of the electric cables are shown in Fig. 5.
The high airflow velocity region was located around the roof of the roadway section and the two sides were generally symmetrical in this roadway. The average value of airflow velocity crossing the roadway cross-section was 1.58 m/s. Fig. 6(A) depicts the layout of the analytic paths (a, b, c, d and e) in the cross-section of No.2 northeast ventilation and conveyor connection roadway. The airflow velocities were rising rapidly, then fluctuating, in direction a according to the distance from the boundary. When the value of airflow velocity reached 80% (1.71 m/s) of the highest velocity in the path a region, the distance reached 26% (0.493 m) of the total distance (Fig. 6(B)). The airflow velocities were rising rapidly at first, then slow down, in direction b according to the distance from the boundary.
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Fig. 7. Velocity distribution (m/s) in Air measuring station (bolting and shotcreting with smoothing).
When the value of airflow velocity reached 80% (1.64 m/s) of the highest velocity in the path b region, the distance reached 45% (1.238 m) of the total distance (Fig. 6(C)). The airflow velocities were rising rapidly at first, then dropping slowly, then rising, in direction c according to the distance from the boundary. When the value of airflow velocity reached 80% (1.61 m/ s) of the highest velocity in the path c region, the distance reached 58% (1.092 m) of the total distance (Fig. 6(D)). The airflow velocities were rising rapidly, then dropping, then rising slowly, in direction d according to the distance from the boundary. When the value of airflow velocity reached 80% (1.86 m/s) of the highest velocity in the path d region, the distance reached 23% (0.387 m) of the total distance (Fig. 6(E)). The airflow velocities were rising rapidly at first, then slow down, in direction e according to the distance from the boundary. When the value of airflow velocity reached 80% (1.61 m/s) of the highest velocity in the path e region, the distance reached 53% (0.908 m) of the total distance (Fig. 6(F)). Fig. 7 shows the airflow velocity distribution (m/s) in Air measuring station (bolting and shotcreting with smoothing). The crosssection of the roadway with its length of 4.0 m and its high of 3.0 m is a rectangular section at 92 m from the entrance of airflow. The Air measuring station with a total length of 178 m in the west of the mine area was used the supporting method of bolting and shotcreting with smoothing. There is a gas drainage duct in the roadway. The detailed descriptions of the gas drainage duct are shown in Fig. 7. Average degree and height of concave–convex boundaries can be 1–10 mm in this roadway. The high airflow velocity region was located around the center of the roadway section and the two sides were generally symmetrical in this roadway. The average value of airflow velocity crossing the roadway cross-section was 2.02 m/s. Fig. 8(A) depicts the layout of the analytic paths (a, b, c, d and e) in the cross-section of Air measuring station. The airflow velocities were rising rapidly, then slow down, in direction a according to the distance from the boundary. When the value of airflow velocity reached 80% (2.08 m/s) of the highest velocity in the path a region, the distance reached 17% (0.303 m) of the total distance (Fig. 8(B)).
The airflow velocities were rising rapidly at first, then slow down, in direction b according to the distance from the boundary. When the value of airflow velocity reached 80% (2.02 m/s) of the highest velocity in the path b region, the distance reached 41% (0.919 m) of the total distance (Fig. 8(C)). The airflow velocities were rising rapidly at first, then steady, in direction c according to the distance from the boundary. When the value of airflow velocity reached 80% (2.03 m/s) of the highest velocity in the path c region, the distance reached 28% (0.636 m) of the total distance (Fig. 8(D)). The airflow velocities were rising rapidly, then slow down, then rising, in direction d according to the distance from the boundary. When the value of airflow velocity reached 80% (2.02 m/s) of the highest velocity in the path d region, the distance reached 16% (0.217 m) of the total distance (Fig. 8(E)). The airflow velocities were rising rapidly at first, then slow down, in direction e according to the distance from the boundary. When the value of airflow velocity reached 80% (2.14 m/s) of the highest velocity in the path e region, the distance reached 30% (0.406 m) of the total distance (Fig. 8(F)). 3.2. Analysis and discussion Airflow velocity measurements, in 100 points of the crosssections, were taken using the same methods. And the airflow velocity in different parts of the cross-section were measured in the same way. Therefore, the measure results could give an objective distribution of airflow velocity in the cross-section. By comparing the distribution of airflow velocity in Figs. 1, 3, 5 and 7, it can be observed that the high airflow velocity region was located around the floor of the roadway with rough roof and wall, but in the roadways with smooth roof and wall was located around the center of section. Because of the surface roughness of floors in four different roadways was similarity, the surface roughness of wall and roof is the most important factor for this phenomenon. The results show that the supporting methods affect the distributions of airflow velocity through the surface roughness of wall and roof. Table 1 shows the percentages of the low airflow velocity distance in total distance when the value of airflow velocity reached
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(A) Layout of the analytic paths in the crosssection of Air measuring station.
(D) Evolution of airflow velocities in direction c according to the distance from the boundary.
(B) Evolution of airflow velocities in direction a according to the distance from the boundary.
(E) Evolution of airflow velocities in direction d according to the distance from the boundary.
(C) Evolution of airflow velocities in direction b according to the distance from the boundary.
(F) Evolution of airflow velocities in direction e according to the distance from the boundary.
Fig. 8. Analysis diagram of Air measuring station.
Table 1 Percentages of the low velocity distance in total distance of different paths. Supporting methods
Average velocity (m/s)
Path a (%)
Path b (%)
Path c (%)
Path d (%)
Path e (%)
Bolting with wire mesh Bolting and shotcreting I-steel Bolting and shotcreting with smoothing
2.46 1.80 1.58 2.02
61 25 26 17
46 67 45 41
47 36 58 28
15 58 23 16
13 6 53 30
80% of the highest velocity in the paths a, b, c, d and e regions. It can be seen in Figs. 2(A), 4(A), 6(A) and 8(A) that paths a, b, c, d and e reflect the influence of wall, wall and roof, wall and floor, roof and floor, respectively, on the distribution of airflow. The influence of floor could be reflected in paths c and e. The surface roughness of floors in four different roadways was similarity, but there was a difference in the percentages of the low velocity distance in total distance. It is due to the higher value of average airflow velocity could lead to boundary layer becoming thinner.
The influence of roof and wall could be reflected in paths a, b, c and d. The percentages of the low velocity distance in total distance increase with surface roughness in these paths. It can be seen in Table 1 that the percentage in path a in the roadway with bolting with wire mesh supporting method is highest, though it has the highest value of average airflow velocity. This indicated that the surface roughness has more important influence on the distribution of airflow velocity than average airflow velocity in this study.
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The dimension of the rectangular section roadway could also influence the distribution of airflow velocity. To eliminate the influence of the dimension, the sections which we studied generally have the same dimensions. However, it is very difficult to find four rectangular section roadways with the same dimensions and different supporting methods in underground coal mines. Therefore, CFD models and laboratory studies should be developed to solve the problem in the future. 4. Conclusions To know the behavior of ventilation airflow in the roadways is very important for the safety of workers in underground mines and other underground works. Studies on the needs of distributions of airflow in rectangular section roadways with different supporting methods in underground coal mines by conventional methods are necessary. Both smoothing and average velocity could influence the distribution of airflow. The supporting methods influence the low airflow velocity region around the roof and wall of roadways. It is shown that the low airflow velocity region increase with surface roughness of the roof and wall. Increasing the value of average airflow velocity could lead to low airflow velocity region decreasing. The high airflow velocity region was located around the floor of the roadway with rough roof and wall. However, in the roadways with smooth roof and wall the high airflow velocity region was located around the center of section. The risk assessment should be carried out in the low airflow velocity region in the roadway with rough roof and wall. To ensure the safety of coal mining, higher volume of air intake or more smooth roof and wall of the roadways should be achieved in a dangerous zone. Acknowledgments This work was financed by the National Natural Science Foundation of China (No. 51104105). We would like to thank Yuwu Coal Company (China) for the access to their underground mines and for technical supporting this study. References Dave, N., Azih, C., Yaras, M.I., 2013. A DNS study on the effects of convex streamwise curvature on coherent structures in a temporally-developing turbulent boundary layer with supercritical water. Int. J. Heat Fluid Flow 44, 635–643. Gao, R., Li, A., Hao, X., Lei, W., Deng, B., 2012. Prediction of the spread of smoke in a huge transit terminal subway station under six different fire scenarios. Tunn. Undergr. Space Technol. 31, 128–138.
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Gygi, F., 2013. Sharing data in materials science. Nature 503, 464. Hargreaves, D.M., Lowndes, I.S., 2007. The computational modeling of the ventilation flows within a rapid development drivage. Tunn. Undergr. Space Technol. 22 (2), 150–160. Herdeen, J., Sullivan, P. 1993. The application of CFD for evaluation of dust suppression and auxiliary ventilation systems used with continuous miners. In: Proceeding of the 6th US Mine Ventilation Symposium, SME, Littleton, pp. 293– 297. Karacan, C.O., 2008. Modelling and prediction of ventilation methane emissions of U.S. longwall mines using supervised artificial neural networks. Int. J. Coal Geol. 73, 371–387. Kun, H., Wang, X.L., Zhou, Z.Y., Zhou, S.S., 2010. Influence of branch tunnels on CO diffusion simulation of main underground powerhouse construction ventilation. In: 2010 3rd International Conference on Biomedical Engineering and Informatics, pp. 2654–2657. Liu, G., Gao, F., Ji, M.L., Xing, G., 2009. Investigation of the ventilation simulation model in mine based on multiphase flow. Procedia Earth Planet. Sci. 1, 491–496. Moloney, K.W., Lowndes, I.S., 1999. Comparison of measured underground air velocities and air flows simulated by computational fluid dynamics. Trans. Inst. Min. Metall. (Sec. A: Min. Ind.) 108, 105–114. Nakayama, 1998. In-situ measurement and simulation bu CFD of methane gas distribution at a heading faces. Shinsen-to-Sozai 114 (11), 769–775. Onder, M., Cevik, E., 2008. Statistical model for the volume rate reaching the end of ventilation duct. Tunn. Undergr. Space Technol. 23, 179–184. Parra, M.T., Villafruela, J.M., Castro, F., Méndez, C., 2005. Numerical and experimental analysis of different ventilation systems in deep mines. Build. Environ. 41, 87–93. Se, C.M.K., Lee, E.W.M., Lai, A.C.K., 2012. Impact of location of jet fan on airflow structure in tunnel fire. Tunn. Undergr. Space Technol. 27 (1), 30–40. Suglo, R.S., Frimpong, S., 2001. Assessment of the efficiencies of auxiliary ventilation systems using empirical methods. Can. Inst. Min. Metall. Bull., 67–71 (September). Toraño, J., Rodríguez, R., Cuesta, A., Diego, I., 2002. A computer program for calculating ventilation in tunneling works based on an explicit method. Tunn. Undergr. Space Technol. 17 (3), 227–236. Toraño, J., Torno, S., Menendez, M., Gent, M.R., Velasco, J., 2009. Models of methane behavior in auxiliary ventilation of underground coal mining. Int. J. Coal Geol. 80, 35–43. Toraño, J., Torno, S., Menendez, M., Gent, M., 2011. Auxiliary ventilation in mining roadways driven with roadheaders: validated CFD modelling of dust behavior. Tunn. Undergr. Space Technol. 26, 201–210. Torno, S., Toraño, J., Ulecia, M., Allende, C., 2013. Conventional and numerical models of blasting gas behavior in auxiliary ventilation of mining headings. Tunn. Undergr. Space Technol. 34, 73–81. Uchino, K., Inoue, M., 1997. Auxiliary ventilation at a heading of a face by a fan. In: Proceeding of the 6th US Mine Ventilation Symposium, SME, Littleton, pp. 493– 496. Wala, A., Jacob, J., Brown, J., Huang, G., 2003. New approaches to mine-face ventilation. Min. Eng. 55 (3), 25–30. Wang, X.L., Liu, X.P., Sun, Y.F., An, J., Zhang, J., Chen, H.C., 2009. Construction schedule simulation of a diversion tunnel based on the optimized ventilation time. J. Hazard. Mater. 165, 933–943. Wang, P., Feng, T., Liu, R., 2011. Numerical simulation of dust distribution at a fully mechanized face under the isolation effect of an air curtain. Min. Sci. Technol. (China) 21, 65–69. Xu, G., Luxbacher, K.D., Ragab, S., Schafrik, S., 2013. Tunn. Undergr. Space Technol. 33, 1–11. Yuan, L., Smith, A.C., Brune, J.F., 2006. Computational fluid dynamics study on ventilation flow paths in longwall gobs. In: 11th US/North American Mine Ventilation Symposium, State College, PA, pp. 591–598.