Skip to main content
NCBI home page
ACS Omega logoLink to ACS Omega
. 2024 Apr 18;9(17):19320–19333. doi: 10.1021/acsomega.4c00433

Gas–Solid Flow Characteristics of Airflow and Dust Particles in Blasting Excavation of Underground Metal Mine Tunnels

Boxue Pang †,‡,*, Xianghui Ren †,‡, Shaoqin Wang †,‡, Guangliang Yan §, Jiyu Hou †,‡, Longhao Li †,‡, Liang Li †,‡, Xu Liu ∥,*
PMCID: PMC11064191  PMID: 38708228

Abstract

graphic file with name ao4c00433_0019.jpg

Effective dust removal has long been a challenge in the blasting mining of underground metal mine tunnels, and uncontrolled dust diffusion seriously endangers workers’ respiratory systems and the underground space safety environment. However, the vast majority of existing numerical studies on dust diffusion are focused on coal mine fully mechanized mining, which is different from metal mine blasting excavation in terms of stope structure and dust properties. Furthermore, the mechanism by which the forced and exhaust ventilation modes affect the diffusion characteristics of inhalable particles is unclear. In this work, gas–solid flow characteristics for dust diffusion in a typical metal mine blasting tunnel were numerically investigated based on the Euler–Lagrange method, where the blasting face instantly released 6.37 × 107 particles with 100 different sizes, ranging from 0.8 to 200 μm. The interphase forces between airflow and dust particles are comprehensively modeled, and the particle diffusion effect caused by fluid turbulence is described by a discrete random walk model. Detailed information for airflow turbulence and particle migration was revealed, and dust removal efficiencies for inhalable particulate matter (PM10) by forced, exhaust, and hybrid ventilation were analyzed. Numerical results predict a complex airflow pattern in the working roadway, including the jet-flow region, return airflow core region, airflow disorder region, and secondary flow region. Dust diffusion temporal characteristics can be divided into three stages, namely, the initial stage of dust generation, the efficient ventilation and dust removal stage, and the later stage of dust diffusion. Dust diffusion spatial characteristics indicate that under the Coanda wall attachment effect, the dust concentration exhibits nonuniform distribution in both vertical and horizontal directions of the return air roadway. The dust removal efficiency of hybrid ventilation on inhalable particles above respiratory height is better than that of forced ventilation, especially in the return air roadway. The additional exhaust air duct based on forced ventilation can discharge more inhalable particles from the tunnel.

1. Introduction

The progress of underground mining mechanization and the demand for large-scale high-intensity mining cause a sharp increase in total dust production during underground mine tunneling.1−5 Diffusion of high-concentration dust particles not only pollutes the underground working environment and reduces the production efficiency but also seriously endangers the respiratory system of workers and, in specific cases, even triggers dust explosions.6−11 In the past 10 years, the global incidence rate of pneumoconiosis has increased by 61.5%.12 Miners account for over 90% of occupational pneumoconiosis patients in China.13 Therefore, effective ventilation and dust removal are key technologies in tunneling. The dust diffusion characteristics are determined by the gas–solid two-phase flow system composed of airflow and a large amount of dust particles in underground spaces, which has received more attention from researchers in recent years.

Regarding the multiple size characteristics of dust particles, Zhang et al. adopted the Euler–Lagrangian method to investigate the distribution of dust particles with 10 different diameters below 200 μm in tunnels under forced ventilation. Their results indicate that the effect of airflow velocity on large dust particles is greater than that on small ones, and a reasonable reduction of airflow velocity is an effective way to control the suspended dust.14 Geng et al. numerically investigate settlement, circulation, and distribution of 50,000 dust particles within a size range of 2–200 μm in a hybrid ventilation system. They concluded that finer particles typically gather near the vent, while larger ones tend to settle to the exhaust side.15 Treating dust particles as a continuous phase, Wang et al. adopted the Euler–Euler method to study diffusion, sedimentation, and accumulation characteristics of dust with a single particle size (10 μm) under different dust production rates and proposed dust prevention methods under various ventilation modes.16 Mo et al. established a mathematical model for the operation of a vehicle-mounted dust collector in a fully mechanized mining face and analyzed the dust diffusion with 150 particle sizes within the range of 1–20 μm, obtaining the key technical parameters of the dust collector.17 Yu et al. established an airflow–dust coupling model by means of the computational fluid dynamics/discrete element method (CFD-DEM) method and analyzed the diffusion of 5000 dust particles with 5 different particle sizes, obtaining better dust control performance under single exhaust ventilation compared to single forced ventilation.18

Various underground ventilation and dust removal working conditions have also attracted the attention of researchers. Du et al. established an idealized rectangular coal mining face model with a mining height of up to 8.8 m and simulated the airflow and dust transport behavior within the supersized fully mechanized mining face.19 Song et al. constructed a fully mechanized top coal caving face model with full negative pressure-independent ventilation in a U-shaped working tunnel and simulated the two-phase diffusion of gas and inhalable dust particles.20 Gui et al. established a rectangular coal roadway model with an arch, focusing on the control effect of PM2.5 around the tunneling machine driver under the wind curtain-assisted ventilation system.21 Liu et al. established a tunnel boring machine (TBM) tunneling model with a circular cross section for subway tunnels, analyzed the dust transport under the opening and closing states of the main ventilation system, and summarized the principles of dust control in tunneling.22 Liu et al. established a 1:20 similarity scale spiral tunnel model to investigate the dust diffusion under different curvature radii and dust release amounts.23 Furthermore, Hu et al. used Monte Carlo and airflow–dust unidirectional coupling methods to study the dust transport in blasting excavation tunnels and revealed the temporal distribution characteristics of total and respiratory dust particles.24 For the blasting area of subway tunnels, Xie et al. analyzed the effects of the volume flow rate of forced air ducts and total mass of explosives on ventilation and dust removal time based on different upper limits of dust concentration.25

As mentioned above, the vast majority of numerical studies on dust diffusion are focused on coal mine fully mechanized mining faces, whose calculation domain is mostly rectangular or U-shaped, which is different from underground metal mining stopes.26 Second, metal mines are mainly excavated by blasting, where the blasting face instantly releases a large number of dust particles with rich sizes. Due to the uncertainty of random tracking in the Euler–Lagrange method, the dust particle size distribution is still discontinuous under limited particle number of the dust source. Therefore, releasing a sufficient number of particles from the blasting face is an effective way to obtain a stable particle size distribution field.27 However, in most existing research, both the total number of dust source particles and the number of particle sizes are insufficient. Due to the differences in tunnel structure, mining methods, and dust particle characteristics, the dust pollutant control parameters obtained based on coal mine fully mechanized mining tunnels cannot be directly applied to predict the dust diffusion in metal mine blasting tunnels.15,28

In view of the above-mentioned facts, this work adopts the discrete phase model to numerically investigate the dust diffusion characteristics in a typical underground metal mine blasting tunnel, where the working face instantly released 6.37 × 107 dust particles with 100 different sizes, ranging from 0.8 to 200 μm. The interphase forces between airflow and dust particles are comprehensively modeled, and the particle diffusion effect caused by fluid turbulence is described by the discrete random walk model. The spatiotemporal diffusion characteristics of airflow and dust particles have been revealed. The dust removal efficiencies for inhalable particulate matter (PM10) by forced, exhaust, and hybrid ventilation were analyzed.

2. Computational Fluid Dynamics Model for Airflow and Dust Particles

2.1. Mathematical Model for Airflow

The mass conservation equation for the airflow can be expressed as

2.1. 1

where subscript g represents the gas phase. ρ, t, and u are density, time, and velocity, respectively.

The momentum conservation equation for the airflow can be expressed as29

2.1. 2

where p is the airflow pressure and g is the gravity acceleration. Fi is the external body force from the interaction between airflow and dust particles.

τg is the airflow stress tensor, which can be expressed as

2.1. 3

where μg and μt are the laminar and turbulent viscosity of airflow, respectively.

The airflow turbulent viscosity μt is calculated as

2.1. 4

where Cμ = 0.09. k and εk are the turbulent kinetic energy and the dissipation rate from the k–εk two-equation turbulence model:30

2.1. 5
2.1. 6

where C1ε = 1.44 and C2ε = 1.92. σk = 1.0, and σε = 1.3, which are turbulent Prandtl constant of k and εk. Gk is the turbulent kinetic energy produced by the airflow velocity gradients.

2.2. Mathematical Model for Dust Particle Movement

In the Lagrangian coordinate system, the equilibrium equation for the force of dust particles is integrated to achieve the prediction of particle transport trajectories in the airflow field. The migration characteristics of dust particles in airflow can be described by Newton’s second law as follows:

2.2. 7

where subscript s represents the solid phase, us is the particle velocity, and ms is the particle mass.

Fgra and Fbuo are the gravity and buoyancy of the dust particle, respectively:

2.2. 8

where Vs is the volume of dust particles, ρs is the density of dust, and ds is the particle diameter.

∑Fgs is the combined force of the interaction between airflow and dust particles:

2.2. 9

where Fdr is the drag force, Fvm is the virtual mass force, Fp is the pressure gradient force, Fmag is the Magnus force, and Fsaf is the Saffman force.

The drag force plays a dominant role among the interaction forces between airflow and dust:

2.2. 10

where Cd is the drag coefficient for a single dust particle in the airflow:31

2.2. 11

where Res is the Reynolds number for particle:

2.2. 12

a1, a2, and a3 are coefficients applied to various ranges of Res:

2.2. 13

When the dust particles are accelerated relative to the airflow, they will be subjected to the additional virtual mass force:32

2.2. 14

where Cvm is the virtual mass coefficient and its default value is 0.5.

Due to the presence of pressure gradients in the airflow field, the movement of dust particles in the flow field is subjected to the pressure gradient force Fp:

2.2. 15

When there is a velocity gradient in the airflow field where the dust particles are located, the velocity difference between the fluid on both sides of the particles causes the Saffman lift force Fsaf:33,34

2.2. 16

where K is the Saffman constant coefficient and its typical value is 2.594, υ is the kinematic viscosity, and Dij is the deformation rate tensor:

2.2. 17

Due to dust particles rotation, the particles are subjected to the Magnus lift force Fmag perpendicular to the direction of airflow, whose direction points from the side with low fluid velocity to the side with high fluid velocity:35,36

2.2. 18

where ω is the relative fluid–particle angular velocity.

In addition to the interaction forces mentioned above, dust particle trajectories are significantly affected by airflow turbulence. In this work, the discrete random walk (DRW) model is applied to describe the particle diffusion effect caused by fluid turbulence.37

2.3. Geometric Model and Boundary Conditions for Dust Diffusion in the Ventilation Tunnel

The geometric model and dimensions of the ventilation tunnel, the air properties, and the dust source characteristics in the present work are derived from the Guizhou Shuiyindong gold mine in China.38Figure 1A illustrates the computational domain for the gas–solid flow of air and dust particles, which is a cross-shaped tunnel formed by a ventilation roadway and a working roadway. As shown, the ventilation tunnel is 50 m long, with a cross-sectional width of 2.5 m and a height of 3.0 m. One end of the working roadway is the blasting face, with a length of 12 m and a cross-sectional width and height of 2.6 m. At the other end of the working roadway is a 2.5 m long equipment room. As an auxiliary ventilation facility, an air duct with a diameter of 0.4 m is installed inside. As shown, the air duct is 1.58 m above the ground and 0.1 m from the side wall of the roadway. Its inlet is 5 m from the blasting face. To study the dust transport characteristics under different ventilation modes, the forced, exhaust, and hybrid ventilation systems are built on the basis of the present tunnel geometry, as illustrated in Figure 1B–D. As shown by the airflow direction represented by the blue arrow, in forced ventilation, the high-speed fresh air is pumped into the vicinity of the working face by the air duct, achieving the effect of ventilation and dust removal. In exhaust ventilation, the airflow in the opposite direction from the air duct exhibits a suction effect on dust particles. Hybrid ventilation is a combination of the above two, which sucks dust particles near the working face while being injected in high-speed fresh air.

Figure 1.

Figure 1

Open in a new tab

Geometric model of the simulated mining ventilation tunnel: (A) top and cross-sectional views, (B) forced ventilation, (C) exhaust ventilation, and (D) hybrid ventilation.

The quality and quantity of the grids are important factors that affect simulation accuracy and efficiency. The cross section of the simulated mining ventilation tunnel is meshed into quadrilateral grids, and the entire calculation domain throughout the tunnel is discretized into hexahedral structured grids using ICEM software. Furthermore, preliminary simulations are conducted to analyze grid size sensitivity. Three sets of grids with different sizes were constructed for the forced ventilation system, with quantities of 4,09,127, 2,55,224, and 1,03,776, respectively. The simulated airflow velocity at a height of 1.5 m along the axis of the return air roadway at the three grid sizes is illustrated in Figure 2. Starting from the inlet side of the tunnel (Z = 50 m) along the axial direction, the airflow velocity gradually increases. Near the working roadway (Z = 20 m), the airflow velocity rapidly increases to its maximum value, which is due to the supplementation of the airflow rate from the forced air duct. From the working roadway to the outlet, the airflow velocity gradually decreases. As shown, the trend of simulation results based on three sets of grids is similar. The difference in airflow velocity along the tunnel axial direction based on medium and fine grids is very small. However, the simulation results based on coarse grids show significant deviations from the above two in the range from the working roadway to the outlet (Z = 0–20 m).

Figure 2.

Figure 2

Open in a new tab

Simulated airflow velocity at a height of 1.5 m along the axis of the return air roadway at different grid sizes.

Figure 3 shows the mesh quality distribution for the medium grids of the ventilation tunnel computational domain. The modeling effect of the hexahedral structural mesh is evaluated by calculating three indicators (determinant, maximum orthogonality, and maximum skewness) and taking the minimum value as the mesh quality.39 The mesh quality ranges from 0 to 1, where 1 indicates the best mesh quality, and 0 indicates the worst mesh quality. The statistical results indicate that the worst grid quality is 0.365, and the best grid quality is 1.0. The proportion of grids with quality ranging from 0.95 to 1.0 is 56.113%, while the proportion of grids with quality ranging from 0.365 to 0.4 is only 0.003%. Therefore, the medium grids were determined to perform accurate and efficient simulations.

Figure 3.

Figure 3

Open in a new tab

Mesh quality distribution for the ventilation tunnel computational domain.

Numerical simulations for gas–solid flow of airflow and dust particles during underground metal mine tunnel blasting are performed based on Euler–Lagrange method incorporating the discrete phase model in the CFD code ANSYS-FLUENT.40 The summarized boundary conditions used in the present simulations are listed in Table 1. At the inlet of the ventilation roadway, fresh air flows into the roadway at a velocity of 2.0 m/s. At the inlet of the forced air duct, the direction of airflow points toward the blasting face, and the inlet velocity is 13.3 m/s. However, the direction of airflow at the exhaust air duct is opposite, and the discharge velocity is 16 m/s.

Table 1. Summarized Simulation Parameters.

object property value unit
ventilation tunnel size of ventilation roadway 2.5 × 3 × 50 m
  size of working roadway 2.6 × 2.6 × 17 m
  diameter of the air duct 0.4 m
  height of the air duct 1.58 m
airflow air density 1.225 kg/m3
  air viscosity 1.7894 × 10–5 kg/(m·s)
  inlet velocity at the ventilation roadway 2.0 m/s
  inlet velocity at the forced air duct 13.3 m/s
  inlet velocity at the exhaust air duct –16.0 m/s
dust particles dust material calcium oxide  
  dust injection velocity 10 m/s
  dust density 3320 kg/m3
  dust total generating rate 8 × 10–3 kg/s
  dust injection time 1 s
  dust diameter distribution Rosin–Rammler  
  dust minimum diameter 8 × 10–7 m
  dust maximum diameter 2 × 10–4 m
  dust mean diameter 7 × 10–5 m
Open in a new tab

During the blasting process, a large number of dust particles are generated instantaneously. All dust particles are released from the blasting face with a total generation rate of 8 × 10–3 kg/s, and the initial injection velocity is set to 10 m/s. According to the setting, the dust particles will complete the injection within 1 s. Diameters of the dust particles follow a Rosin–Rammler distribution, with a maximum diameter of 2 × 10–4 m, a minimum diameter of 8 × 10–7 m, and a mean diameter of 7 × 10–5 m, which is a typical particle size range for dust in deep metal mining.14,41 As a result, 6.37 × 107 dust particles with 100 different sizes are generated. The exit of the tunnel is set as an atmospheric pressure outlet boundary condition for airflow and escape boundary conditions for particles.

3. Results and Discussion

3.1. Model Validation

Effective numerical methods can compensate for the shortcomings of field measurements and provide more detailed flow field information for complex operating conditions. However, the accuracy of the numerical models needs to be verified through field measurements. The local airflow velocity inside the tunnel is the key flow field information that affects dust diffusion. Comparisons between simulated airflow velocity and on-site measurements of the Shuiyindong gold mine in China38 at different locations are illustrated in Figure 4. The inlet airflow velocities at the windward side of the roadway and at the forced air duct are 1.5 and 17.0 m/s, respectively. The working roadway with a forced air duct is located 20 m away from the ventilation roadway outlet. It can be seen that the airflow velocity significantly increases after the forced airflow position. The simulated area average airflow velocity is quite consistent with the on-site measurements.38 Therefore, the proposed model in the present work was confirmed to be a reliable method for simulating the ventilation flow field in metal mine tunnels.

Figure 4.

Figure 4

Open in a new tab

Comparisons between simulations and on-site measurements at different locations.

3.2. Airflow Diffusion Characteristics

3.2.1. Airflow Velocity Distribution

The airflow pattern is the dominant factor in the dust diffusion characteristics in the tunnels. Figure 5 shows the velocity distribution contour and three-dimensional (3D) streamlines of airflow in the forced ventilation tunnel. Overall, the fresh air enters uniformly from the upwind side at a velocity of 2.0 m/s and flows toward the downwind side. The forced air duct injects fresh air at a high velocity of 13.3 m/s into the working roadway for dust removal. As a result, all contaminated air flows out from the downwind side.

Figure 5.

Figure 5

Open in a new tab

Velocity magnitude contour and 3D streamlines of airflow in the ventilation tunnel.

In the upwind region (Z = 20–50 m), before the air duct jet from the working roadway enters, the airflow velocity distribution is relatively uniform, and the streamlines are almost parallel. After the airflow reaches the downwind region, the airflow velocity distribution becomes uneven. From the Z = 5 and 15 m cross section contours, the airflow velocity is higher on the side far from the working roadway than on the side adjacent to the working roadway due to the X-positive component of the high-velocity airflow from the working roadway.

In the working roadway, the airflow pattern is much more complex. The high-velocity airflow is injected from the forced air duct suspended in the upper right corner of the roadway, forming a jet-flow region. After the high-velocity jet flow impacts the blasting face, the airflow direction is reversed. During this process, the kinetic energy is lost, resulting in a decrease in the airflow velocity. Under the combined action of the diversion in the blind headway limited space and the negative pressure generated by the high-velocity jet flow from the air duct, the airflow direction has undergone multiple reversals, and a large number of eddies are formed in the working tunnel. As the distance from the blasting face increases, the airflow disorder phenomenon weakens, and the relatively stable airflow enters the return air tunnel.

The axial transport of dust particles released from the blasting face in the working roadway is dominated by the airflow X-velocity. Figure 6 shows the X-velocity distribution and 3D streamlines of airflow in the working roadway. The first thing to note is the velocity direction represented by the legend. The blue in the legend represents the maximum velocity in the negative X direction, facing the blasting face. However, the red in the legend represents the maximum value in the positive X direction, which is away from the blasting face. The blue dashed line in the cross sections of X = 2 and 4 m shows the jet-flow region, which is located between the air duct and the blasting face. In this region, high-velocity airflow impacts the blasting face. The closer the distance to the blasting face, the larger the jet area. The red dashed line in each cross section shows the return airflow core region, which is located near the working roadway ground. In this area, the high-velocity air flows from the blasting face to the return air roadway. As the distance from the blasting face increases, the area of the return airflow core region decreases, and the airflow distribution becomes more uniform. The pink dashed line in the cross section of X = 2 and 4 m shows the airflow disorder region, which is mainly located on the tunnel wall side opposite the air duct. The airflow direction in this region is different from the main flow; it moves toward the blasting face instead of moving toward the positive X direction. When the reverse dust-laden airflow diffuses to a larger area, it will mix with fresh air, pollute the intake area, and affect the dust removal efficiency. Furthermore, when the airflow is subjected to lateral pressure along the boundary and undergoes displacement parallel to the boundary, a secondary flow superimposed on the main airflow is formed. As a result of the centrifugal force field and the shear stress gradient, the airflow showed opposite tangential velocities within the cross section at X = 2 m, as indicated by the black rotating arrows, which is the secondary flow phenomenon.

Figure 6.

Figure 6

Open in a new tab

X-velocity distribution and 3D streamlines of airflow in the working roadway.

1.5 m is usually the height of the human mouth and nose, which is the breathing zone of workers, and the dust concentration in this area is closely related to their health and safety.42,43Figure 7 illustrates the X-velocity of airflow along the axis of the working roadway at the breathing height (Y = 1.5 m). Along the central axis (Line O) and right axis (Line R) of the working roadway, the airflow velocity near the blasting face is in the negative X direction, while the airflow velocity away from the blasting face is in the positive X direction. Especially on the air duct side (Line R), the jet velocity toward the working face is very high, and it sharply decreases and changes direction behind the air duct. On the left axis of the working roadway (Line L), the airflow velocity in the X direction has undergone multiple directional changes, and the airflow disorder area is within X = 2–6 m.

Figure 7.

Figure 7

Open in a new tab

Airflow X-velocity along the axis of the working roadway at the breathing height.

3.2.2. Airflow Turbulence Distribution

Airflow turbulence kinetic energy and its dissipation rate are shown in Figure 8, which are important physical quantities that describe velocity pulsation and its energy dissipation. Turbulent kinetic energy refers to the kinetic energy of turbulent motion in a fluid. Turbulent dissipation rate refers to the rate at which the kinetic energy of turbulent motion is converted into internal energy due to viscous dissipation in the fluid. An increase in turbulent kinetic energy means that the turbulent motion of the fluid is more vigorous. However, an increase in the turbulent dissipation rate indicates an increase in the amount of turbulent heat transfer and an increase in energy losses. In the region between the air duct and the blasting face, the turbulence kinetic energy and its dissipation rate are relatively high. On the one hand, at the jet outlet, there is a large velocity gradient, and the restricted jet flow can fully develop. On the other hand, the jet flow is dominated by inertial forces, and the original airflow inside the tunnel is dominated by viscous forces. Under the interaction of the two, shear, mixing, and momentum exchange occur between the airflow, resulting in strong turbulence pulsations. Meanwhile, because of the friction between the airflow and the tunnel wall, as well as the impact with the blasting face, some turbulent energy is dissipated into internal energy, leading to a high turbulent dissipation rate. In addition, high turbulent kinetic energy and dissipation rates also appear in the return airflow core region near the ground, which is caused by airflow disorder and ground friction.

Figure 8.

Figure 8

Open in a new tab

Turbulence kinetic energy and its dissipation rate of airflow in the ventilation tunnel.

Area average turbulence kinetic energy and its dissipation rate of airflow along the working roadway are illustrated in Figure 9. The turbulent kinetic energy decreases along the positive X direction from the blasting face. Especially within the 1 m area near the blasting face, the velocity pulsation of the airflow sharply weakens. However, for the turbulent dissipation rate, its decrease along the working roadway is not monotonic. At a distance of about 3 m from the blasting face, there exists a maximum value of turbulent dissipation rate, which also corresponds to the airflow disorder region.

Figure 9.

Figure 9

Open in a new tab

Area average turbulence kinetic energy and its dissipation rate of airflow along the working roadway.

3.3. Dust Particles Diffusion Characteristics

3.3.1. Temporal Distribution of Dust Particles

The mass concentration distribution and diffusion time of dust in tunnels are important standards for evaluating the air quality of underground space environments. Figure 10A–C shows the dust temporal distribution characteristics in the tunnel during the initial stage of blasting dust production. In this simulation, 6.37 × 107 dust particles with 100 different diameters are initially released during the working face blasting. About 2 s after blasting, the front edge of the high-concentration dust field has rapidly spread to the central position in the X direction of the working roadway. Due to the jet-flow field from the air duct in the upper part of the tunnel, some dust particles are pressed into the lower space. At T = 6 s, the dust particles had already spread and filled the entire working roadway space. Affected by jet flow, the dust concentration near the blasting face has significantly decreased, while in the return airflow core region, it is relatively high. At T = 10 s, a portion of the dust particles enter the return air roadway. Under the airflow driving force within the return air roadway, dust particles diffuse in the negative Z direction. Simulation results indicate that before 10 s, the dust concentration in most of the working roadway space exceeded 20 mg/m3.

Figure 10.

Figure 10

Open in a new tab

Temporal distribution of dust particles: (A) T = 2 s, (B) T = 6 s, (C) T = 10 s, (D) T = 100 s, (E) T = 150 s, and (F) T = 200 s.

Figure 10D–F shows the temporal and spatial distribution characteristics of dust particles within the tunnel after 100 s of forced ventilation. It can be seen that there are still a large amount of dust particles suspended and dispersed in the working roadway and the downwind side of the return air roadway. In the working roadway, dusts spread the entire space. However, in the return air roadway, under the Coanda wall attachment effect, a large number of dust particles diffuse toward the tunnel exit, adhering to the right wall. Furthermore, a portion of dust particles settle to the tunnel ground, forming a dense dust sedimentary area. At T = 150 s, dust particle concentration within the ventilation tunnel is significantly reduced, and in most locations, it has decreased to below 0.5 mg/m3. At T = 200 s, the dust mass concentration further decreases, and the dust removal effect of forced ventilation is significant.

In order to more intuitively describe the temporal characteristics of dust diffusion, Figure 11 illustrates the variation of the volume average mass concentration of dust in the entire ventilation tunnel over time. As the simulation conditions were set, the generation and release of dust particles at the moment of blasting were completed within 1 s. Point A marks the completion of the release of dust from the blasting face, and the dust mass concentration in the tunnel skyrockets. Afterward, the dusts diffuse throughout the entire ventilation tunnel, but their average volume concentration remains at 1.8 × 10–5 kg/m3. Until point B, which is 16.4 s, the dusts diffuse to the exit of the return air tunnel at this time, and the volume average dust mass concentration of the entire tunnel begins to decrease. After about 100 s of forced ventilation, as illustrated in point C, the dust mass concentration has reached a lower level, but its decrease over time is limited, and dust particles continue to disperse in the tunnel space. We can divide the temporal characteristics of dust diffusion in the tunnel into three stages, namely, the initial stage of dust generation (stage I), the efficient ventilation and dust removal stage (stage II), and the later stage of dust diffusion (stage III).

Figure 11.

Figure 11

Open in a new tab

Variation of the volume average mass concentration of dust in the entire ventilation tunnel over time.

3.3.2. Spatial Distribution of Dust Particles

In underground mining ventilation and dust removal engineering, the primary concern is the dust concentration at the workers’ breathing height, that is, at the height of their mouth and nose, which is closely related to safety and health. Second, dust concentration distribution at different distances from the blasting face is also crucial for the selection of safe working locations. Figure 12 shows dust mass concentration distribution at the breathing height and cross sections of the tunnel after 60 s of forced ventilation. Overall, the dust particles released from the blasting face are distributed throughout the entire working roadway space. After entering the return air tunnel, most of the dust particles are transported along the downwind side tunnel (Z = 5, 15 m), and they are rarely distributed in the upwind side (Z = 25, 35, 45 m). In the X-cross sections of the working roadway (X = 2, 4, 6, 8, 10 m), the dust concentration along the vertical direction shows a distribution trend of high in the lower part and low in the upper part, which is due to the gravitational sedimentation of particles. However, in the Z-cross sections of the return air tunnel (Z = 5, 15 m), the dust concentration exhibits nonuniform distribution characteristics along both X and Y directions. Under the combined action of gravity settlement and Coanda wall attachment effect, more red areas are shown on the contour in the corner between the ground and the right wall of the downwind region, where a large amount of dust is accumulated.

Figure 12.

Figure 12

Open in a new tab

Dust mass concentration distribution at the breathing height and cross sections of the tunnel: (A) spatial distribution view and (B) top view.

The variation of the area average mass concentration of dust in the X-cross sections (X = 2, 4, 6, 8, 10 m) of the working roadway over time is illustrated in Figure 13. Overall, the dust mass concentration shows a trend of first increasing and then decreasing. In the early stage of blasting dust production, the dust mass concentration at various positions in the working roadway rapidly increases to its maximum value within a few seconds (T = 0–5 s). The dust particles generated from the working face diffuse along the positive X direction under the action of the airflow returning from the forced air duct jet. Therefore, the closer the distance to the blasting face, the earlier the dust concentration reaches its maximum value. Moreover, at the axial positions from X = 2 to 10 m, the maximum dust concentration first decreases and then increases. The reason is that a portion of the dust particles are deposited and then suspended and diffused again. For the same reason, during the middle stage of dust removal (T = 15–30 s), fluctuations in dust concentration occurred at various axial locations of the working roadway. In the middle and later stages of dust removal (T = 30–200 s), under the action of forced ventilation, the dust concentration decreases in an oscillatory manner, and this process lasts for a long time. Moreover, the farther away from the working face, the higher the average dust concentration. The reason is that the dust removal effect is mainly dominated by the airflow in the positive X direction, which is generated by the airflow returning from the working face.

Figure 13.

Figure 13

Open in a new tab

Variation of the area average mass concentration of dust in the X-cross sections of the working roadway over time.

3.4. Effects of Forced, Exhaust, and Hybrid Ventilation Modes

3.4.1. Velocity of Dust Particles and Airflow under Three Ventilation Modes

In this work, the dust particles’ diffusion characteristics under three ventilation modes were investigated, namely, forced ventilation, exhaust ventilation, and hybrid ventilation. As mentioned above, after blasting to produce dust and ventilation for 100 s, the reduction rate of dust concentration is limited and the dust removal process needs to last for a long time. This process is a dust removal stage that requires special attention. In this section, the dust diffusion characteristics under different ventilation modes were analyzed based on the transient results of ventilation and dust removal for 150 s. Figure 14 illustrates the distribution of dust velocity in different ventilation modes. In forced ventilation, the particle velocity is relatively high at the air duct jet area and at the tunnel ground near the blasting face. The velocity of dust particles decreases at the exit of the working roadway and increases after entering the return air roadway. In the tunnel with only an exhaust air duct, the dust particles’ diffusion rate is slow. After 150 s of exhaust ventilation, most of the dust particles have not yet entered the return air roadway. In hybrid ventilation, that is, in the tunnel with both forced and exhaust air ducts, the particle velocity within the region between the blasting face and the air duct is higher, and the suspended dust particles in the return air roadway are reduced.

Figure 14.

Figure 14

Open in a new tab

Dust particle velocity magnitude under different ventilation modes: (A) forced ventilation, (B) exhaust ventilation, and (C) hybrid ventilation.

Figure 15A shows the airflow X-velocity along the working roadway at breathing height (Y = 1.5 m) under different ventilation modes. As shown, the axial velocity is lower in the exhaust ventilation tunnel than that in the forced and hybrid ventilation tunnels. In the working roadways of forced and hybrid ventilations, the airflow X-velocity changes from negative to positive. Moreover, under the combined effect of the forced and exhaust air ducts, the transition position of the airflow X-velocity direction in the hybrid ventilation is closer to the blasting face.

Figure 15.

Figure 15

Open in a new tab

Airflow velocity distribution at the breathing height along the axis of the working roadway under different ventilation modes: (A) X-velocity and (B) velocity magnitude.

Figure 15B shows the airflow velocity magnitude along the working roadway at the breathing height (Y = 1.5 m). Overall, among the three ventilation modes, due to the jet and suction effects of the air duct, the airflow velocity magnitude increases sharply near the blasting face and then fluctuates significantly along the axial direction. The velocity magnitude in forced and hybrid ventilation is greater than that in exhaust ventilation. In forced ventilation, the velocity magnitude is relatively high in the area between the air duct and the blasting face. At a distance of more than 6 m from the working face, the airflow velocity magnitude decreases. In the exhaust ventilation, due to the reverse suction, the velocity magnitude suddenly increases at Z = 5 m and remains at a lower level in other axial positions. For hybrid ventilation, the velocity magnitude fluctuates significantly multiple times in the working roadway, and its amplitude is higher than that in forced ventilation.

3.4.2. Spatial Distribution of Dust with Various Particle Sizes

In the simulation of this work, the working face released more than 6 × 107 dust particles with 100 different sizes ranging from 0.8 to 200 μm at the moment of blasting. Dust particles with diameter less than 10 μm, namely, inhalable particulate matter (PM10), pose a serious threat to the respiratory system of workers and should be given special attention in ventilation and dust removal. Figure 16 shows the spatial distribution characteristics of dust with various particle sizes in the tunnel under different ventilation modes at T = 150 s. Inhalable particles (PM10) are uniformly suspended in the tunnel space. For dusts with the particle size of 10–80 μm, part of them diffuses in a suspended flow state, while the other part settles to the ground of the tunnel. For dust particles ranging in size from 80 to 200 μm, the vast majority of them have settled to the tunnel ground.

Figure 16.

Figure 16

Open in a new tab

Spatial distribution characteristics of dust with various particle sizes in the tunnel under different ventilation modes at T = 150 s: (A) forced ventilation, (B) exhaust ventilation, and (C) hybrid ventilation.

As shown in Figure 16, in the tunnel with only an exhaust air duct, the dust removal efficiency is poor, and a majority of dust particles are still suspended and dispersed in the working roadway. In the tunnel with a forced air duct, the dust removal efficiency has been improved, but there is still a large amount of dust with particle sizes ranging from 0 to 80 μm suspended and diffused in the working and return air roadways. For the hybrid ventilation with both forced and exhaust air ducts, compared to forced ventilation, the concentration of dust particles with a size of 0–10 μm decreases in both the working and return air roadways, while the concentration of dust particles with a size of 10–80 μm decreases only in the return air roadway.

3.4.3. Inhalable Particles (PM10) in the Respiratory Zone

We define the space above a height of 1.5 m in the tunnel as a suspension zone and believe that dust particles in this space have the opportunity to come into contact with the mouth and nose of workers. Figure 17 shows the number and proportion distribution characteristics of dust with various particle sizes in the suspended zone of the tunnel under different ventilation modes. It can be seen that there are no particles with a diameter of over 80 μm in the suspended zone based on the three ventilation modes. In forced ventilation, the number and proportion of inhalable particles (PM10) suspended in the space above a height of 1.5 m is higher than that in hybrid ventilation. Whereas, in hybrid ventilation, the number and proportion of particles with the size of 10–40 μm is high. However, in the tunnel with only an exhaust air duct, the number of dust particles with a diameter of less than 40 μm far exceeds the other two ventilation modes mentioned above.

Figure 17.

Figure 17

Open in a new tab

Number and proportion distribution characteristics of dust with various particle sizes in the suspended zone of the tunnel under different ventilation modes.

Figure 18 shows the mass concentration of inhalable dust particles (PM10) in the suspended zone along the working roadway and the return air roadway under different ventilation modes. In the working tunnel, we divided it into 24 sections along the X direction, with a spacing of 0.5 m. In the downwind zone of the return airway, we divided it into 20 sections along the Z direction, with a spacing of 1.0 m. Then, the concentration of inhalable particulate matter (PM10) in each suspended zone of the interval was statistically analyzed. In the working tunnel with only an exhaust air duct, the concentration of inhalable particles (PM10) in the suspended zone is much higher than that in forced and hybrid ventilation. Under the action of the jet flow from the forced air duct, the concentration of inhalable particulate matter significantly decreases. The hybrid ventilation exhibits a more stable dust removal effect for PM10. Only in the jet-flow zone (Z = 0–5 m), the concentration of residual inhalable particles in the forced ventilation is lower than that of the hybrid ventilation.

Figure 18.

Figure 18

Open in a new tab

Mass concentration of inhalable particles (PM10) in the suspended zone along working and return air roadways under different ventilation modes: (A) working roadway and (B) return air roadway.

Through the entire return air roadway of the forced ventilation, the concentration of residual inhalable particles in the suspended zone is much higher than that in the hybrid ventilation. For the exhaust ventilation, there is no PM10 in the return air roadway because, after 150 s of exhaust ventilation, the vast majority of dust is still suspended in the working tunnel. Only an exhaust air duct can effectively remove dust. Summarily, the dust removal efficiency for inhalable particulate matter in the suspended zone is that hybrid ventilation is better than forced ventilation. The additional exhaust air duct based on forced ventilation can discharge more inhalable particles from the tunnel.

4. Conclusions

The spatiotemporal distribution characteristics of dust diffusion in a typical underground metal mine blasting tunnel were numerically investigated using the computational fluid dynamics method. The gas–solid flow of airflow and dust particles in tunnels is simulated based on a discrete phase model, which has been confirmed to be a reliable method for simulating the ventilation flow field in comparison with on-site measurements. Detailed information for airflow and 6.37 × 107 dust particles in the tunnel are analyzed, including airflow velocity, turbulence, dust spatiotemporal distribution, and inhalable particles (PM10) removal efficiency. Furthermore, the effects of forced, exhaust, and hybrid ventilation modes on dust diffusion characteristics are studied and discussed.

  • Due to the jet flow from the air duct and the diversion by the single end tunnel, the airflow direction has undergone multiple reversals, and a large number of eddies are formed in the working tunnel. The complex airflow pattern appears in the working roadway, including the jet-flow region, the return airflow core region, and the airflow disorder region. Moreover, tangential velocities of airflow in two opposite directions, namely, secondary flow, occur approximately 2 m from the blasting face.

  • Strong turbulence pulsation and energy dissipation in the jet-flow region are caused by shear, mixing, and momentum exchange between the airflow, and those in the return airflow core region are caused by airflow disorder and ground friction.

  • The temporal characteristics of dust diffusion in the tunnel can be divided into three stages, namely, the initial stage of dust generation, the efficient ventilation and dust removal stage, and the later stage of dust diffusion. The dust concentration decreases in an oscillatory manner during the ventilation, the reason for which is that a portion of the dust particles are deposited and then suspended and diffused again.

  • For the spatial characteristics of dust diffusion, due to the suspension of inhalable particles (PM10) and gravity settlement of large particles (80–200 μm), the dust concentration in the vertical direction of the tunnel is higher at the bottom and lower at the top. However, under the action of the Coanda wall attachment effect, the dust concentration exhibits nonuniform distribution characteristics in both X and Y directions of the return air roadway.

  • In the tunnel with only an exhaust air duct, the dust removal efficiency is poor due to the low airflow velocity. In hybrid ventilation with both forced and exhaust air ducts, the airflow velocity fluctuates significantly multiple times along the working roadway, and its amplitude is higher than that of forced ventilation.

  • The dust removal efficiency of hybrid ventilation on inhalable particles (PM10) above respiratory height is better than that of forced ventilation, especially in the return air roadway. However, for particle sizes ranging from 10 to 40 μm, the dust removal of forced ventilation is more effective. The additional exhaust air duct based on forced ventilation can discharge more inhalable particles from the tunnel.

Acknowledgments

This work was supported by the National Natural Science Foundation of China [grant numbers 12202098 and 22203039] and the National Key R&D Program of China [grant number 2023YFC2907205].

Glossary

Nomenclature

Cd

drag coefficient

Cvm

virtual mass coefficient

Dij

deformation rate tensor

ds

particle diameter

Fbuo

buoyant force

Fdr

drag force

Fgra

gravity force

Fmag

Magnus force

Fp

pressure gradient force

Fsaf

Saffman force

Fvm

virtual mass force

g

acceleration of gravity

K

Saffman constant coefficient

k

turbulence kinetic energy

ms

particle mass of dust

p

airflow pressure

Res

Reynolds number for particle

ug

gas velocity

us

particle velocity

Vs

volume of dust particle

εk

turbulent dissipation rate

ρg

airflow density

ρs

dust density

ω

relative fluid–particle angular velocity

μg

airflow molecular viscosity

μt

airflow turbulent viscosity

υ

kinematic viscosity

τg

airflow stress

Glossary

Subscripts

g

gas phase

s

solid phase

The authors declare no competing financial interest.

References

  1. Zheng L.; Liu Z. Q.; Li D. W.; Wang H. T.; Zhang Q. T. Micromechanism analysis of surfactant wetting of coal based on 13C NMR experiments. ACS Omega 2021, 6 (2), 1378–1390. 10.1021/acsomega.0c05005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Zhang L. C.; Zhou G.; Ma Y.; Jing B.; Sun B.; Han F. W.; He M.; Chen X. Numerical analysis on spatial distribution for concentration and particle size of particulate pollutants in dust environment at fully mechanized coal mining face. Powder Technol. 2021, 383, 143–158. 10.1016/j.powtec.2021.01.039. [DOI] [Google Scholar]
  3. Wang Y. P.; Jiang Z. G.; Zhang F.; Lu Y.; Bao Y. W. Study on dust diffusion characteristics of continuous dust sources and spray dust control technology in fully mechanized working face. Powder Technol. 2022, 396, 718–730. 10.1016/j.powtec.2021.11.025. [DOI] [Google Scholar]
  4. Hao T. X.; Wang L.; Wang Z. H.; Li F.; Jiang W.; Jiang S. Research on Dust Migration and Dust Deposition Rules of Breathing Zone in Fully Mechanized Mining Face. ACS Omega 2023, 8 (42), 39143–39153. 10.1021/acsomega.3c04251. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Kumar A. R.; Schafrik S.; Novak T. Multi-phase computer modeling and laboratory study of dust capture by an inertial Vortecone scrubber. Int. J. Min. Sci. Technol. 2020, 30 (3), 287–291. 10.1016/j.ijmst.2020.03.014. [DOI] [Google Scholar]
  6. Su X. B.; Ding R.; Zhuang X. G. Characteristics of dust in coal mines in central North China and its research significance. ACS Omega 2020, 5 (16), 9233–9250. 10.1021/acsomega.0c00078. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Toraño J.; Torno S.; Menéndez M.; Gent M. Auxiliary ventilation in mining roadways driven with roadheaders: Validated CFD modelling of dust behavior. Tunneling Underground Space Technol. 2011, 26 (1), 201–210. 10.1016/j.tust.2010.07.005. [DOI] [Google Scholar]
  8. Saki S. A.; Brune J. F.; Khan M. U. Optimization of gob ventilation boreholes design in longwall mining. Int. J. Min. Sci. Technol. 2020, 30 (6), 811–817. 10.1016/j.ijmst.2020.08.005. [DOI] [Google Scholar]
  9. Paluchamy B.; Mishra D. P.; Panigrahi D. C. Airborne respirable dust in fully mechanised underground metalliferous mines-Generation, health impacts and control measures for Cleaner production. J. Cleaner Prod. 2021, 296, 126524 10.1016/j.jclepro.2021.126524. [DOI] [Google Scholar]
  10. Liu T. Q.; Zhao X.; Tian W. Y.; Jia R. H.; Wang N.; Cai Z. X.; Wu X. C. Experimental research on the suppression effect of different types of inert dust on micron-sized lignite dust explosion pressure in a confined space. ACS Omega 2022, 7 (39), 35069–35076. 10.1021/acsomega.2c03952. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Xiu Z. H.; Cai P.; Chen D. W.; Nie W. Numerical simulation of dust control technology for longwall working face with convective air curtain. Environ. Sci. Pollut. Res. 2023, 30 (45), 101829–101840. 10.1007/s11356-023-29563-w. [DOI] [PubMed] [Google Scholar]
  12. Huang X. Z.; Liu W.; Yao Y. X.; Wang D. M.; Sun Y.; Chen W. H. 30-Year Trends in the Disease Burden, Incidence, and Prevention of Pneumoconiosis. China CDC Wkly. 2023, 5 (38), 856–860. 10.46234/ccdcw2023.163. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Cai P.; Nie W.; Chen D. W.; Yang S. B.; Liu Z. Q. Effect of air flowrate on pollutant dispersion pattern of coal dust particles at fully mechanized mining face based on numerical simulation. Fuel 2019, 239, 623–635. 10.1016/j.fuel.2018.11.030. [DOI] [Google Scholar]
  14. Zhang W.; Xue S.; Tu Q. Y.; Shi G. F.; Zhu Y. F. Study on the distribution characteristics of dust with different particle sizes under forced ventilation in a heading face. Powder Technol. 2022, 406, 117504 10.1016/j.powtec.2022.117504. [DOI] [Google Scholar]
  15. Geng F.; Luo G.; Zhou F. B.; Zhao P. T.; Ma L.; Chai H. L.; Zhang T. T. Numerical investigation of dust dispersion in a coal roadway with hybrid ventilation system. Powder Technol. 2017, 313, 260–271. 10.1016/j.powtec.2017.03.021. [DOI] [Google Scholar]
  16. Wang Y. C.; Luo G.; Geng F.; Li Y. B.; Li Y. L. Numerical study on dust movement and dust distribution for hybrid ventilation system in a laneway of coal mine. J. Loss Prev. Process Ind. 2015, 36, 146–157. 10.1016/j.jlp.2015.06.003. [DOI] [Google Scholar]
  17. Mo J. M.; Yang J. L.; Ma W.; Chen F.; Zhang S. J. Numerical simulation and field experiment study on onboard dust removal technology based on airflow-dust pollution dispersion characteristics. Environ. Sci. Pollut. Res. 2020, 27, 1721–1733. 10.1007/s11356-019-06847-8. [DOI] [PubMed] [Google Scholar]
  18. Yu H. M.; Cheng W. M.; Xie Y.; Peng H. T. Micro-scale pollution mechanism of dust diffusion in a blasting driving face based on CFD-DEM coupled model. Environ. Sci. Pollut. Res. 2018, 25, 21768–21788. 10.1007/s11356-018-1992-4. [DOI] [PubMed] [Google Scholar]
  19. Du T.; Nie W.; Chen D. W.; Xiu Z. H.; Yang B.; Liu Q.; Guo L. D. CFD modeling of coal dust migration in an 8.8-meter-high fully mechanized mining face. Energy 2020, 212, 118616 10.1016/j.energy.2020.118616. [DOI] [Google Scholar]
  20. Song S. Z.; Zhou G.; Duan J. J.; Zhang L. C.; Gao D. H.; Sun B. Numerical simulation investigation on optimal dust-exhausting airflow volume in fully mechanized caving face of high-gas coal mine. Process Saf. Environ. Prot. 2021, 146, 853–866. 10.1016/j.psep.2020.11.045. [DOI] [Google Scholar]
  21. Gui C. G.; Geng F.; Tang J. H.; Niu H. W.; Zhou F. B.; Liu C.; Hu S. D.; Teng H. X. Gas-solid two-phase flow in an underground mine with an optimized air-curtain system: A numerical study. Process Saf. Environ. Prot. 2020, 140, 137–150. 10.1016/j.psep.2020.04.028. [DOI] [Google Scholar]
  22. Liu Q.; Cheng W. M.; Liu L. S.; Hua Y.; Guo L. D.; Nie W. Research on the control law of dust in the main ventilation system in excavated tunnels for Cleaner production. Build. Environ. 2021, 205, 108282 10.1016/j.buildenv.2021.108282. [DOI] [Google Scholar]
  23. Liu R.; Jiang D. Y.; Chen J.; Ren S.; Fan J. Y.; He Y. Blasting dust diffuse characteristics of spiral tunnel and dust distribution model: similar experiment and numerical modeling. Environ. Sci. Pollut. Res. 2023, 30 (18), 52340–52357. 10.1007/s11356-023-25422-w. [DOI] [PubMed] [Google Scholar]
  24. Hu S. Y.; Feng G. R.; Ren X. Y.; Xu G.; Chang P.; Wang Z.; Zhang Y. T.; Li Z.; Gao Q. Numerical study of gas-solid two-phase flow in a coal roadway after blasting. Adv. Powder Technol. 2016, 27 (4), 1607–1617. 10.1016/j.apt.2016.05.024. [DOI] [Google Scholar]
  25. Xie Z. W.; Xiao Y. M.; Jiang C. X.; Ren Z. L.; Li X. Q.; Yu K. C. Numerical study on fine dust pollution characteristics under various ventilation time in metro tunnel after blasting. Build. Environ. 2021, 204, 108111 10.1016/j.buildenv.2021.108111. [DOI] [Google Scholar]
  26. Sa Z. Y.; Li F.; Qin B.; Pan X. H. Numerical simulation study of dust concentration distribution regularity in cavern stope. Saf. Sci. 2012, 50 (4), 857–860. 10.1016/j.ssci.2011.08.019. [DOI] [Google Scholar]
  27. Wang Z. W.; Ren T. Investigation of airflow and respirable dust flow behaviour above an underground bin. Powder Technol. 2013, 250, 103–114. 10.1016/j.powtec.2013.08.045. [DOI] [Google Scholar]
  28. Azam S.; Mishra D. P. Effects of particle size, dust concentration and dust-dispersion-air pressure on rock dust inertant requirement for coal dust explosion suppression in underground coal mines. Process Saf. Environ. 2019, 126, 35–43. 10.1016/j.psep.2019.03.030. [DOI] [Google Scholar]
  29. Batchelor G. K.An Introduction to Fluid Dynamics; Cambridge University Press: Cambridge, 1967. [Google Scholar]
  30. Launder B. E.; Spalding D. B.. Lectures in Mathematical Models of Turbulence; Academic Press: London, 1972. [Google Scholar]
  31. Morsi S. A.; Alexander A. J. An investigation of particle trajectories in two-phase flow systems. J. Fluid Mech. 1972, 55 (2), 193–208. 10.1017/S0022112072001806. [DOI] [Google Scholar]
  32. Drew D. A.; Lahey D. A.. Analytical Modeling of Multiphase Flow. In Particulate Two-phase Flows; Roco M. C., Ed.; Butterworth-Heinemann: Oxford, 1993. [Google Scholar]
  33. Saffman P. G. The lift on a small sphere in a slow shear flow. J. Fluid Mech. 1965, 22 (2), 385–400. 10.1017/S0022112065000824. [DOI] [Google Scholar]
  34. Li A.; Ahmadi G. Dispersion and deposition of spherical particles from point sources in a turbulent channel flow. Aerosol Sci. Technol. 1992, 16 (4), 209–226. 10.1080/02786829208959550. [DOI] [Google Scholar]
  35. Rubinow S. I.; Keller J. B. The transverse force on a spinning sphere moving in a viscous fluid. J. Fluid Mech. 1961, 11 (3), 447–459. 10.1017/S0022112061000640. [DOI] [Google Scholar]
  36. Crowe C.; Sommerfeld M. S.; Tsuji Y.. Multiphase Flows with Droplets and Particles; CRC Press: Boca Raton, 1998; pp 67–88. [Google Scholar]
  37. Gosman A. D.; Loannides E. Aspects of computer simulation of liquid-fueled combustors. J. Energy 1983, 7 (6), 482–490. 10.2514/3.62687. [DOI] [Google Scholar]
  38. Hu H. Y.; Zhang Z. Q.; Li B. L.; Zhan S. L.; Huang Y. X.; Lv Q. Y.; Hu Z. H.; Long Y. A numerical simulation of dust pollution law under traditional electric rake operation: A case study of Shuiyindong gold mine. Process Saf. Environ. 2023, 174, 253–266. 10.1016/j.psep.2023.03.070. [DOI] [Google Scholar]
  39. ICEM . ANSYS ICEM CFD Help Manual. ANSYS, Inc. Release 2021 R1, Southpointe, 2600 ANSYS Drive, Canonsburg, PA 15317, 2021. (January 2021). [Google Scholar]
  40. FLUENT . ANSYS Fluent Theory Guide. ANSYS, Inc. Release 2021 R1, Southpointe, 2600 ANSYS Drive, Canonsburg, PA 15317, 2021. (January 2021). [Google Scholar]
  41. Geng F.; Gui C. G.; Teng H. X.; Tang J. H.; Niu H. W.; Zhou F. B.; Liu C.; Hu S. D.; Li S. H. Dispersion characteristics of dust pollutant in a typical coal roadway under an auxiliary ventilation system. J. Cleaner Prod. 2020, 275, 126524 10.1016/j.jclepro.2020.122889. [DOI] [Google Scholar]
  42. Liu N.; Chen K.; Deng E.; Yang W. C.; Wang Y. W. Study on dust suppression performance of a new spray device during drilling and blasting construction in the metro tunnel. Tunneling Underground Space Technol. 2023, 133, 104975 10.1016/j.tust.2022.104975. [DOI] [Google Scholar]
  43. Zhou G.; Feng B.; Yin W. J.; Wang J. Y. Numerical simulations on airflow-dust diffusion rules with the use of coal cutter dust removal fans and related engineering applications in a fully-mechanized coal mining face. Powder Technol. 2018, 339, 354–367. 10.1016/j.powtec.2018.07.078. [DOI] [Google Scholar]

Articles from ACS Omega are provided here courtesy of American Chemical Society

RESOURCES