Open AccessArticle

Influence of Long Pressure and Short Suction Ventilation Parameters on Air Flow Field and Dust Migration in Driving Face

Yuannan Zheng

^1,2,*

Bo Ren

¹ and

Guofeng Yu

State Key Laboratory for Safe Mining of Deep Coal Resources and Environment Protection, Huainan 232000, China

Joint National–Local Engineering Research Centre for Safe and Precise Coal Mining, Huainan 232001, China

Author to whom correspondence should be addressed.

Sustainability 2024, 16(17), 7786; https://doi.org/10.3390/su16177786

Submission received: 12 August 2024 / Revised: 28 August 2024 / Accepted: 4 September 2024 / Published: 6 September 2024

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Abstract

A combination of similar tests and numerical simulation was used to study the distribution of the air flow field and the dust field in the driving face under the conditions of long pressure and short suction ventilation. The results show that the air flow field is divided into return, jet, and vortex zones. When the distance (L) is 1.6 m, the wind speed (V_a) is 8 m/s, and the ratio of pumped air volume to pressure air volume (Q) is 0.8, the total and exhaled dust concentration (T_d, R_d, T_p, and R_p) at the driver’s and pedestrian’s position were the lowest. According to the grey correlation analysis, the importance of factors affecting T_d and T_p is ranked as L > V_a > Q, R_d is ranked as V_a > L > Q, and R_p is as follows: V_a > Q > L. The increase in V_a and the decrease in L have a significant effect on the expulsion of exhaled dust.

Keywords:

driving face; numerical simulation; long pressure; short pumping; wind field; dust transport

1. Introduction

In the mining field, dust control has not yet achieved a holistic and comprehensive improvement [1]. The high concentration of dust in coal mines not only seriously threatens the safety of mine production, but also induces lung, cardiovascular, and brain diseases in coal mine employees, causing great harm to their physical and mental health [2,3]. As one of the main dust-producing areas in coal mines, the driving face has a serious dust pollution situation along the roadway, which can be solved by combining various dust-removal control methods [4].

Common coal dust treatment methods mainly include coal seam water dust reduction [5,6,7], spray dust reduction [8,9,10], ventilation dust removal, etc. [11,12,13]. Ventilation dust removal is one of the more effective methods at present [14,15]. Domestic and foreign scholars have carried out a lot of research on ventilation dust removal. HUA et al. [16] explored the influence of the position of an air extraction pipe and the amount of air extraction on the generation and dust control effect of the air curtain under the ventilation model of long pressure and short suction. When the pressure extraction pipe is located on the left and right sides of the driving roadway, respectively, and under the combined action of exhaust air and pressure air, the direction of air flow is directed towards the working face to effectively control the dust in the air curtain. NIE et al. [17] concluded through orthogonal numerical simulation that among the four ventilation parameters of pressure and exhaust outlet position and pressure and exhaust air volume, pressure and exhaust air volume was the most significant factor affecting the diffusion of dust in high and low concentrations. Geng et al. [18] established a numerical model based on the Euler–Lagrange method to solve the movement and trajectory of dispersed dust, respectively, and found that the dust distribution is very uneven. Mishra [19] used CFD software ANSYS-Fluent 14.0 to conduct a three-dimensional numerical simulation in combination with actual mines, and studied the influence of different ventilation parameters on dust diffusion. BOSIKOV I.I. [20], using statistical dynamics, the correlation function of random variables, set theory, basic laws of mine aerodynamics, graph theory, and discrete mathematics, analyzed and estimated the aerodynamic parameters of coal mine air distribution control systems.

To sum up, most scholars mainly establish a full-scale model by numerical simulation based on the actual driving face so as to explore the space–time evolution law of the total suspended particulates along the roadway. However, there are few reports on the influence of multiple ventilation parameter disturbance on respirable dust. Because respirable dust has small particles and relatively small contents, it is difficult to accurately measure its mass concentration and spatial distribution by experimental methods [21,22]. There are many problems in the numerical simulation of the actual working face, such as low computational efficiency and difficulties in finding out the law of the dust field. As a kind of mixed ventilation, long pressure short pump ventilation has been gradually popularized in the low-gas driving face roadway due to its better dust-control effect compared with pressurized ventilation [23,24]. However, the dust-removal effect of long pressure and short pumping ventilation is different under different parameters. It is necessary to explore the influence of different ventilation parameters on the air flow field and dust field along the roadway, and to obtain the best ventilation parameters or the influence of ventilation parameters on the dust field along the roadway, which can help to adjust the ventilation system or change the layout of the roadway.

Therefore, this paper takes the Hongliulin Mine 25212 excavation face as the research object, and sets up a long pressure short suction ventilation dust removal test platform according to the ratio of 1:2, and uses a numerical simulation method to verify the effectiveness of the platform. After that, the experimental platform was modeled. The effects of multiple ventilation parameters (L, V_a, Q) on the air flow and dust fields were investigated. A grey correlation analysis was used to analyze the importance of each ventilation parameter in influencing the total and exhaled dust of drivers and pedestrians.

2. Model and Method

2.1. Model

2.1.1. Experiment Platform

Due to the large size of the excavation roadway, it is difficult to establish a 1:1 experimental model. In order to ensure the feasibility of the experiment, the similarity criterion is adopted to scale the original size and establish a similar experimental model of the excavation roadway for analysis. In order to achieve the same physical phenomenon and mechanical similarity between the similar experimental model and the field situation, it is necessary to ensure not only the geometric similarity of the model, but also the similar movement and dynamics of the fluid, and at the same time to meet the same initial conditions and boundary conditions of the fluid movement in the two environments [16]. The similarity criterion is the basis of establishing the similarity model. In order to meet the requirement of the similarity model in the similarity experiment, the similarity criterion number of the air flow and solid particles along the roadway are derived, respectively, according to the similarity theorem [25].

(1): Equation of motion of gas

It is assumed that the gas flow is incompressible when the dust migrates in the driving roadway under the influence of wind speed. The three-dimensional steady-state incompressible Navier–Stokes equation is used to describe it, and the gas motion equation can be written as follows [26]:

ρ_{g} \frac{d V_{g}}{d t} = F + P + μ Δ V_{g}

(1)

where

ρ_{g}

is the gas density, kg/m³;

V_{g}

is the velocity vector of the gas, m/s;

t

is the movement time of the gas, s;

F

is the mass force vector of a gas per unit volume, N/m³;

P

is the pressure vector of the gas, Pa;

μ

is the viscosity coefficient of the gas, N·s/m²; and

Δ

is the Laplace operator.

(2): Motion equation

The force analysis of a single particle shows that the particle size is small, and the main forces affecting the dust movement are gravity, buoyancy, and aerodynamic resistance when the forces of smaller magnitudes are ignored. When external forces are ignored, the motion equation of spherical dust particles is as follows [27]:

\frac{π}{6} {d_{p}}^{3} \{ρ_{p} \frac{d V_{p}}{d t} - (ρ_{p} - ρ_{g}) g\} = \frac{π}{8} C_{p} {d_{p}}^{2} ρ_{g} (V_{g} - V_{p}) |V_{g} - V_{p}|

(2)

where

d_{p}

is the diameter of the dust particle, m;

ρ_{p}

is the density of the dust particles, kg/m³;

V_{p}

is the velocity vector of the dust particles, m/s;

C_{p}

is the resistance coefficient, which represents the nature and magnitude of the resistance;

g

is the acceleration of gravity, m/s²; and

V_{g}

is the velocity vector of the gas, m/s.

There are 10 dimensional physical quantities in Formula (1) and Formula (2), such as

ρ_{g}

ρ_{p}

V_{p}

V_{g}

d_{p}

g

μ

l

t

P

. The basic physical dimensions are length [L], mass [M], and time [T]. Therefore, according to the theorem of dimensional analysis in similar processes, 7 different similar criterion numbers such as the Stokes criterion number

S_{t k}

, homogeneity criterion number

H_{o}

, Froude criterion number

F_{r}

, Euler criterion number

E_{u}

, Reynolds criterion number

R_{e}

, density criterion number

ρ_{p} / ρ_{g}

, and motion criterion number

|V_{g} - V_{p}| / V_{g}

can be derived, among which is the following:

S_{t k} = \frac{d_{p}^{2} (V_{g} - V_{p})}{l μ}

(3)

R_{e} = \frac{l ρ_{g} V_{g}}{μ}

(4)

The Equations (1) and (2) describe the motion of the dust-bearing air flow. The unique flow can be determined only when single-valued conditions are given, which include geometric conditions (expressed by the number of similarity criteria

ζ_{1}

), physical conditions, and boundary conditions. Because of the above criterion number, the Euler criterion number

E_{u}

is a non-qualitative criterion, and the size of the dust particles can be expressed by the particle Reynolds criterion number, that is,

R e_{p} = d_{p} r_{g} (V_{g} - V_{p}) / m

. Therefore, there are 8 independent similarity criteria in the whole gas–solid two-phase flow, namely

S_{t k}

H_{o}

F_{r}

R_{e}

ρ_{p} / ρ_{g}

|V_{g} - V_{p}| / V_{g}

R e_{p}

, and

ζ_{1}

(number of geometric similarity criteria). In order to carry out the model test, it is almost impossible for the prototype and the model to meet the above similarity criteria at the same time, so it is necessary to adopt the method of approximate model research, which is essentially to grasp the decisive factors and ignore the secondary factors [28,29]. According to the actual situation of the similar model test of the excavation roadway, the following approximate modeling method is adopted in this paper. In general, the dust used in the model test is the same as the actual dust, so the density of the gas–solid two-phase flow

ρ_{p} / ρ_{g}

can be satisfied by nature. When the flow field of the prototype

H_{o}

and the model is in a stable state during the test, the time uniformity criterion number

|V_{g} - V_{p}| / V_{g}

is not considered. The motion criterion number

F_{r}

represents the ratio of dust particle velocity to gas velocity, which can be approximated to 1 in the prototype and model. The Froude criterion number

F_{r}

represents the ratio of inertial force to gravity, and because the particles are small, the criterion number is not taken into account. Therefore, after the above simplification, the similarity criterion number of gas–solid two-phase flow in the prototype and model is obtained as

S_{t k}

R e_{p}

R_{e}

, and

ζ_{1}

. In addition, in order to make the model test closer to the actual situation, it is necessary to ensure that the dust production location, direction, concentration, and particle diameter distribution of the model and the prototype are similar. The Stokes number and the particle Reynolds number of the model and prototype are equal, and the similarity ratio of the wind speed of the model roadway to that of the prototype roadway can be obtained from Formula (3) as follows:

V_{m} = \frac{l_{y}}{l_{m}} \cdot {(\frac{ρ_{y}}{ρ_{m}})}^{2} \cdot \frac{μ_{m}}{μ_{y}} \cdot V_{y}

(5)

where

V_{y}

and

V_{m}

are, respectively, the wind speed in the prototype and model, m/s;

l_{y}

and

l_{m}

are the prototype and model lengths, respectively, m;

ρ_{y}

and

ρ_{m}

are, respectively, the gas density in the prototype and model, kg/m³; and

μ_{y}

and

μ_{m}

are the aerodynamic viscosity coefficients in the prototype and model, N·s/m², respectively.

The following can be obtained from Formula (4):

\frac{R e_{m}}{R e_{y}} = \frac{l_{m}}{l_{y}} \cdot \frac{ρ_{m}}{ρ_{y}} \cdot \frac{μ_{y}}{μ_{m}} \cdot \frac{l_{y}}{l_{m}} \cdot {(\frac{ρ_{y}}{ρ_{m}})}^{2} \cdot \frac{μ_{m}}{μ_{y}} = \frac{ρ_{y}}{ρ_{m}}

(6)

It can be seen from Equation (6) that the ratio of the fluid Reynolds number between the model and the prototype is equal to the inverse ratio of the air flow density, and the density difference between the mine air and the surface air is small. Therefore, the fluid Reynolds number of the model and the prototype can be basically equal under the conditions of meeting the Stokes criterion and the particle Reynolds number criterion. At the same time, the fluid Reynolds number must meet R_e > 2300, so that the fluid is located in the second self-mode region, to ensure that its dynamics are similar, and thus to ensure that the movement of the fluid is similar [30].

According to the above geometric relationship, the relevant parameters can be determined as follows: it is considered that the air density in the tunnel prototype is equal to the air density in the model, and the air density at 20 °C is taken as

ρ_{y} = ρ_{m} = 1.225 kg / m^{3}

. The prototype aerodynamic viscosity coefficient of the roadway is equal to the model aerodynamic viscosity coefficient,

μ_{y} = μ_{m} = 1.79 \times 10^{- 5} N \cdot s / m^{2}

. The geometric dimension ratio is

l_{m} / l_{y} = 0.5

, the geometric length measurement takes the equivalent diameter of the cross-section

D_{m} = 1 m

, and the wind speed in the prototype roadway is usually 0.25~4 m/s [31].

By substituting within Formula (5), we can deduce the following:

V_{m} = \frac{2}{1} \times 1^{2} \times V_{y} = 2 \times (0.25 \sim 4) m / s

(7)

By substituting Formula (6), we can obtain

R e_{y} = R e_{m} = \frac{1 \times 1.225 \times (0.25 \sim 4)}{1.79 \times 10^{- 5}} = (1.71 \sim 27.37) \times 10^{4}

(8)

Since Re is greater than 2300, the fluid flow in the region is completely turbulent, satisfying similar test conditions. However, according to Nicolas’s experiment, as long as the dynamic similarity is satisfied, the fluid motion similarity is also satisfied in the roadway region [32]. Therefore, the simulated wind speed does not need to be twice as high as the actual wind speed, but only needs to follow the geometric similarity criteria for model design.

According to the modeled similarity criterion number and Hongliulin 25212’s comprehensive excavation face, a test platform with long pressure and short suction ventilation is designed according to the actual model ratio of 2:1. The section height is 2 m, the width is 2 m, and the length is 9 m. A similar roadway model is shown in Figure 1. The front end of the generator is installed with a tower-shaped dust-generation head, whose driving surface is parallel to the roadway face, the height of the control driving surface is 1.3 m, and the distances between the center point of the driving surface and the walls on both sides are equal.

2.1.2. Construction of CFD Model

(1): The establishment of geometric models

The numerical simulation geometric model was established. The model size was 2 m × 2 m × 9 m. The three surface intersection points of pressure side, head, and floor are taken as the origin. The X-axis points from the driving face to the end of the roadway, the Y-axis points from the floor to the roof, and the Z-axis direction points from the pressure side to the exhaust side. Since the model roadway is built in accordance with the ratio of 1:2, Y = 0.75 m. The driving surface is a square with a side length of 0.25 m and an area of 0.0625 m², as shown in Table 1.

(2): Grid independence verification

In order to ensure the consistency of the numerical simulation results on different grids, the dependence of the numerical simulation results on the grid was evaluated. ICEM software was used to create three different numbers of coarse (2496490), medium (4321668), and fine (8701201) grids in the model fluid domain, and the mesh mass was greater than 0.3 in all instances. The numerical calculation of continuous and discrete phases was carried out under the condition that the air speed of the tuyere was 8 m/s, the ratio of pumping air volume was 0.6, and the distance from the blower to the driving surface was 1.6 m. The pressure side (X: 1–7 m, Y: 0.75 m, Z: 0.35 m) and the central region (X: 1–7 m, Y: 0.75 m, Z: 1 m) were extracted at the moment of air flow stability. The size of the air flow at the height of the breathing zone on the extraction side (X: 1–7 m, Y: 0.75 m, Z: 1.65 m) is shown in Figure 2. The wind speed of the three grids increases first, then fluctuates, and finally decreases slowly. The calculated results of the medium grid and the fine grid are similar; only the coarse grid has a relatively large difference in wind speed. This indicates that although the number and quality of the grids divided by the three schemes are different, grid independence has been achieved. Considering the accuracy of the calculation results and the finiteness of the computing resources, the authors chose the medium number of meshes to divide the following meshes. At this time, the mesh shape is tetrahedron, the maximum mesh mass is 0.99, the minimum mesh mass is 0.28, and the average mass is 0.875.

(3): Parameter settings

According to the actual situation of the 25212 driving face, the model boundary and parameters are set as shown in Table 2.

In order to prove the validity of the numerical model, experimental verification is needed. Within a 1–7 m distance from the head of the exhaust side, every 0.5 m is a measuring point, and the wind speed is measured after the ventilation is turned on for a period of time. Starting from 1 m from the front of the exhaust side, one dust sampler is arranged every 1 m, with a total of 6 sets. The dust-generating rate of the dust generator is set at 2000 mg/s, and the concentration is measured after the dust is completely diffused inside the platform. The result is shown in Figure 3. In general, the peak position of wind speed and dust concentration is equally reflected in the experiment and numerical simulation. Compared with the experimental results, the maximum error of the wind speed measurement point is 7.01%, with an average error of 4.25%, and the maximum error of the dust concentration measurement point is 12.66%, with an average error of 6.72%. Considering that the internal flow field will be disturbed when the experimenter enters the platform, the error is considered to be within a reasonable range, and the numerical model can be used for further study.

2.2. Simulation Parameter

There are many influencing factors on the air flow field and dust field along the roadway under the condition of long pressure and short suction ventilation, among which the most important are the L, V_a, and Q. These influencing factors are collectively called the mixed ventilation parameters [33].

In this paper, based on fluent numerical simulation technology, the effect of long pressure suction mixing ventilation parameters on the air flow field and dust field is investigated. First of all, the V_a is 8 m/s, the Q is 0.6, and the L is set as 0.8 m, 1.2 m, 1.6 m, 2.0 m, 2.4 m, 2.8 m, and 3.2 m. Then, the L is 1.6 m, the Q is 0.6, and the V_a is set as 4 m/s, 6 m/s, 10 m/s, 12 m/s, 14 m/s, and 16 m/s. In long pressure and short suction ventilation dust removal, the compressed air volume is generally greater than the extracted air volume. Therefore, the V_a is 8 m/s, the L is set to 1.6 m, and Q is set to 0.2, 0.3, 0.4, 0.5, 0.7, and 0.8. A total of 19 groups of simulation tests were carried out in this paper, and the specific simulation scheme is shown in Table 3.

3. Results

3.1. Influence of Mixed Ventilation Parameters on Air Flow Field of Roadway

Dust generated in the excavation process is carried by air flow and distributed along the entire roadway. Reasonable air flow field design can effectively prevent dust accumulation.

3.1.1. Influence of L on Air Flow Field of Roadway

When the air speed of the air outlet of the pressure duct is 8 m/s, its ratio with the pumping air volume is 0.6, and L is 0.8 m, 1.2 m, 1.6 m, 2 m, 2.4 m, 2.8 m, and 3.2 m, respectively. According to Figure 4, the air flow field under the condition of long pressure and short suction ventilation is divided into return, jet, and vortex zones. The jet area is the air flow area blown by the air outlet of the duct to the driving surface. Due to the influence of the single-ended roadway, a backflow area soon appears. At the same time, there is a vortex area in the middle of the roadway where more dust gathers [34]. With the increase in L, the vortex region is more disordered [35].

With the central axis of the roadway as a symmetrical line, axis 1 is arranged, and axis 2 and axis 3 are arranged 0.65 m away from both sides of the central axis, denoted as the pressure side and extraction side, respectively. The height of the measuring point is the height of the human breathing zone. Considering that the roadway is built in accordance with 1:2, the height of the measuring point is set at 0.75 m from the ground. Wind speed and dust mass concentration were measured on three axes. The changes in the wind speed along the three axes of the roadway when L changes is shown in Figure 5. For the wind speed on the side line of the pressure wind, when the L is 1.6–3.2 m, the wind velocity within 5.5 m is larger, while the wind velocity outside 5.5 m is smaller. At 0.8–1.2 m, the speed in the middle region is smaller, and the speed at both ends is larger. When the distance is 0.8 m and 1.2 m, the change law of wind speed on the central axis is close; when the distance is 1.6–2.4 m, the change law of wind speed is similar; and when the distance is greater than 2.8 m, the change law of wind speed is similar. For the wind speed on the extraction side line, under the four working conditions within 2.0–3.2 m, the variation law is similar, and the wind speed increases first and then decreases and tends to be stable. Under the three operating conditions within 0.8–1.6 m, the change law of wind speed is similar, and the wind speed decreases and climbs sharply within 2–3 m. In general, the further the L, the more the wind speed attenuation of the jet, resulting in a lower wind speed of the return flow. This is due to the role of friction and resistance; the wind flow will suffer a certain energy loss in the process of long-distance transmission. The closer the outlet is to the driving surface, the better the outlet can deliver fresh air to the driving surface, providing a more uniform air flow field, and the distribution of air flow across the driving surface may be more uniform. If the distance between the outlet is far, the air flow may be affected by other obstacles during the transmission process, resulting in a more complex air flow path, which may produce rotation, backflow, or other non-ideal wind flow conditions, which may lead to uneven wind speed distribution, and may lead to low wind speed near the excavation surface, which is not conducive to dust dilution [36,37].

3.1.2. Influence of Wind Speed at the Outlet of Pressure Duct on Air Flow Field in Roadway

The air flow field when the L is 1.6 m, the Q is 0.6, and the V_a is 4 m/s, 6 m/s, 8 m/s, 12 m/s, 14 m/s, and 16 m/s, respectively, is shown in Figure 6. Generally speaking, the velocity changes in the same area of the roadway are close under different wind speeds. When the wind speed at the outlet of the pressure duct is low, the air flow cannot fully cover each area of the roadway, resulting in uneven wind speed distribution. A moderate outlet wind speed of the pressure duct can provide a better distribution of the air flow field. The air flow can cover all areas of the roadway more evenly, effectively remove dust, and provide a good ventilation environment [38].

The changes in the wind speed of different pressure tuyeres on roadway wind speed along the road are shown in Figure 7. From the roadway head to the tail end, the influence of the wind speed of different pressure tuyeres on the change in wind speed along the road is generally consistent, and the wind speed shows a trend of decreasing first, increasing, and then decreasing to a steady state. The variation in wind speed on different axes is different, mainly in the position and amplitude of wind speed reduction. For the wind speed on the pressure side line, the wind speed decreases at about 1.2 m from the head, while the wind speed is low at about 1.5 m on the center line, and the wind speed reaches its minimum at 2.7 m on the extraction side. The cause may be the formation of many eddies along the roadway, and this area is at the center of the eddy. Moderate wind speed helps to maintain air mobility, reduce accumulation and deposition, and improve ventilation. When the V_a is high, the air flow may produce a large amount of turbulence and resistance, resulting in uneven wind speed distribution [39].

3.1.3. The Influence of Suction Gas Ratio on Air Flow Field in Roadway

The air flow field when the V_a is 8 m/s, the L is set to 1.6m, and the Q is 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, and 0.8, respectively, is shown in Figure 8. When the ratio of pumping air volume is different, the change in roadway wind speed along the road is shown in Figure 9. The wind speed along the three axes of the pressure side, the central axis, and the extraction side shows great differences. For the compressed wind side, when the compressed air ratio is very small, the wind speed is larger within 3.7 m of the roadway head, and then decreases continuously. When the suction air volume ratio is greater than 0.5, the air volume at the tail end of the roadway is significantly higher than that at the roadway head position. The possible causes are that the L is longer than the distance from the exhaust duct to the head. When the suction gas ratio is very low, that is, the suction air volume is small or the pressure air volume is large, this may lead to lower negative pressure along the roadway. In addition, the low ventilation ratio may also lead to uneven wind speed distribution, and the wind speed would be low in some areas, affecting the ventilation effect and working environment. The proper negative pressure and wind speed can be maintained along the roadway by the reasonable allocation of the suction–gas ratio. A moderate ventilation ratio can effectively remove dust, keeping the air along the roadway fresh [40].

3.2. Influence of Mixed Ventilation Parameters on Dust Field of Roadway

Dust generated in the excavation process is carried by air flow and distributed along the entire roadway. Reasonable air flow field design can effectively prevent dust accumulation [41].

3.2.1. Influence of L on Dust Field of Roadway

The distribution of particulate matter at different horizontal distances is shown in Figure 10. In general, the further the pressure duct is from the dust source, the more large-particulate dust in the area. By observing the mapping of particles on the XY plane, it is found that with the increase in the horizontal distance from the pressure tuyere to the driving surface, large-particle dust accumulates more and the diffusion distance along the road is longer. The projection of particles on the XZ plane is analyzed. As the L increases, the large-particle accumulation area gradually migrates from the pressure side to the extraction side.

The concentration of total dust and exhaled dust on the three axes when the L changes is shown in Figure 11. When L is small, the concentration of exhaled dust on the return air side may be higher. This is because a smaller L will lead to lower wind speeds and a weak exhaust effect, and coal dust and particulate matter are more likely to deposit and accumulate on the return air side. When the distance between air ducts is longer, the concentration of exhaled dust on the return air side is usually reduced. The larger assembly provides more adequate ventilation time and distance, so that coal dust and particulate matter have more opportunities to be extracted away, reducing their deposition on the return air side. When L is large, the total dust concentration may be relatively low due to the better ventilation effect and the reduction in exhaled dust concentration. Regardless of the length of the air duct distance, the dust concentration on the pressure side is usually low. This is because the wind speed on the pressure side is higher, which can effectively bring coal dust and particulate matter out of the roadway and reduce their accumulation on the pressure side [42].

In this paper, the 2.5–3.5 m range of the compressed air side is defined as the driver’s position, and the 5–7 m range of the exhaust air side is defined as the pedestrian’s position. By extracting the dust concentration data of the compressed air side and the exhaust air side and taking its average value, the influence of the L on the total dust and exhumed dust mass concentration at the driver and pedestrian positions is obtained, as shown in Table 4.

As can be seen from Table 4, when L = 1.6 m, the total dust concentration of drivers and pedestrians is 69.44 mg/m³ and 52.55 mg/m³, and the exhumed dust concentration is 21.34 mg/m³ and 16.69 mg/m³, respectively, the average concentration is the lowest. Therefore, when the V_a is 10 m/s and the Q is 0.6, the dust removal effect is ideal when the L is 1.6 m.

3.2.2. Influence of Wind Speed at the Outlet of Pressure Duct on Dust Field in Roadway

The distribution of particulate matter under different pressure wind speeds is shown in Figure 12. In general, with the increase in pressure wind speed, large-particle dust increases in the region, and the large-particle dust located on the pressure wind side spreads further (inside the blue dashed line in the figure). When the wind speed is 4 m/s, it is difficult for the air flow to lift the large-particle dust, resulting in the area being dominated by small particle size dust, with only a very small amount of medium particle size dust located at the front end of the exhaust side. With the increase in V_a, the medium-sized particles have enough kinetic energy to kick up, and medium-sized particles gradually begin to appear in the middle and back part of this region.

Total dust and exhaled dust concentrations on the three axes under different pressure wind speeds are shown in Figure 13. When the pressure wind speed increases, the exhaled dust concentration on the return air side usually decreases. Higher pressure wind speeds can strengthen the ventilation effect, effectively bring coal dust and particulate matter to the exhaust end, and reduce its deposition and accumulation on the return air side. At low pressure wind speeds, the concentration of exhaled dust may be higher. This is because the lower pressure wind speed may not effectively carry coal dust and particulate matter to the suction end, causing them to accumulate and deposit on the pressure side. Under high pressure wind speeds, the total dust concentration may be relatively low due to the better ventilation and exhaust effect. However, high pressure wind speed may also lead to turbulence and the dust removal of suspended particles, thereby increasing the total dust concentration [43].

The influence of wind speed at the outlet of different pressure ducts on total dust and exhaled dust mass concentration at the driver’s and pedestrian’s position is shown in Table 5. As can be seen from Table 5, when V_a = 14 m/s, the total dust concentration of drivers and pedestrians is 51.7358 mg/m³ and 28.1204 mg/m³, and the exhumed dust concentration is 16.4067 mg/m³ and 11.7284 mg/m³, respectively. At this time, the average concentration is the lowest. Therefore, the dust removal effect is ideal when the L is 1.6 m, the Q is 0.6, and the V_a is 14 m/s.

3.2.3. Influence of Suction Gas Ratio on Dust Field in Roadway

The distribution of particulate matter under different pumping air ratios is shown in Figure 14. On the whole, due to the increase in pumping air volume, the amount of dust in this region gradually decreases, the dust in the region shifts to the pumping side as a whole, and the wake of the triangle area concentrated by large-sized particles shifts to the pumping side. When the pumping pressure ratio is 0.2, large particles gather in the middle of the region, and they disappear completely when the pumping pressure ratio is increased to 0.5. At the same time, when the pumping ratio is increased to 0.4, the large-particle dust on the pressurized air side will diffuse along the way. However, with the continuous increase in the pumping ratio, the large-particle dust on the pressurized air side will diffuse to the entire pressurized air side at the pumping ratio of 0.5 and will shrink, and the particle size will increase with the increase in the pumping ratio.

The influence of different pumping air ratios on total dust and exhaled dust concentration on the three axes is shown in Figure 15. When the pumping pressure ratio is low, that is, when the pumping air volume is small or the pressurized air volume is large, the exhaled dust concentration on the return air side may be higher. Due to the lack of exhaust air volume, coal dust and particulate matter easily accumulate and deposit on the return air side, resulting in an increase in the concentration of exhaust dust. When the pumping pressure ratio is high, the exhaled dust concentration on the return air side is usually reduced. A higher pumping ratio means a stronger pumping capacity, which can effectively remove coal dust and particles on the return air side, reducing their accumulation and deposition on the return air side. Regardless of the pumping ratio, the concentration of exhaled dust on the suction side is usually lower. This is because the wind speed on the compressed air side is higher, which can effectively discharge coal dust and particulate matter from the roadway and reduce their accumulation on the compressed air side. Total dust concentration change can be summarized as follows: at a high pumping pressure ratio, the total dust concentration is usually relatively low due to the better ventilation and exhaust effect and the reduction in the dust concentration [44].

The influence of different pumping ratios on total dust and exhaled dust mass concentration of drivers and pedestrians is shown in Table 6. As can be seen from Table 6, when Q = 0.8, the total dust concentration of the drivers and pedestrians is 24.09 mg/m³ and 23.98 mg/m³, and the exhaled dust concentration is 13.94 mg/m³ and 9.15 mg/m³, respectively. The dust removal effect is ideal when the L is 1.6 m and the Q is 0.8. Through the overall comparison with the previous working conditions, it is found that the average concentration of total dust and exhumed dust at the driver and pedestrian under this working condition is the lowest, so the best working condition can be determined as when L is 1.6 m, V_a is 8 m/s, and Q is 0.8.

3.3. Grey Correlation Analysis

In order to optimize the parameters of roadway ventilation and dust removal, a grey correlation analysis was used to analyze the influence of the L, the V_a, and the Q on the total dust and dust concentration at the position of drivers and pedestrians along the roadway. The grey correlation analysis method is used to determine the degree of correlation and influence among the factors by comparing the main characteristics of the system and the development trend of the main influencing factors [40]. The resulting numerical simulation parameters are shown in Table 7. X0, X01, X02, and X03 are the total dust concentration at the driver’s position, the total dust concentration at the pedestrian’s position, the respirable dust concentration at the driver’s position, and the respirable dust concentration at the pedestrian’s position, respectively, and are the reference sequences. X1, X2, and X3 are the L, the V_a, and the Q, respectively.

Taking the total dust concentration at the driver’s position as an example, the analysis steps are as follows:

(1): Initial calculation of sequence: establish matrix

$X = (X_{0}, X_{1}, X_{2}, X_{3}) = (\begin{matrix} X_{0} (1) & X_{1} (1) & X_{2} (1) & X_{3} (1) \\ X_{0} (2) & X_{1} (2) & X_{2} (2) & X_{3} (2) \\ ⋮ & ⋮ & ⋮ & ⋮ \\ X_{0} (19) & X_{1} (19) & X_{2} (19) & X_{3} (19) \end{matrix})$
(2): Dimensionless sequence: each dimension represents a different meaning, so processing needs to be dimensionless. Using the range method to process each sequence, a dimensionless matrix is obtained: $X^{'} = (X_{0}^{'}, X_{1}^{'}, X_{2}^{'}, X_{3}^{'})$ , k = 1, 2, … 19.
(3): Sequence difference calculation: calculate the absolute difference in the corresponding elements of each comparison sequence and reference sequence one by one, that is, $|X_{0}^{'} (k) - X_{i}^{'} (k)|$ , and obtain the sequence difference matrix $Δ_{i} = (Δ_{1} (k), Δ_{2} (k), Δ_{3} (k))$ , k = 1, 2, … 19.
(4): Calculation of sequence two-stage difference: the maximum value of the sequence difference is $M = \max_{i} \max_{i} Δ_{i} (k)$ , and the minimum value of the sequence difference is $M = \min_{i} \min_{i} Δ_{i} (k)$ .
(5): Calculation of correlation degree coefficient: the grey correlation coefficient matrix $R_{i} = (ζ_{1} (k), ζ_{2} (k), ζ_{3} (k))$ is obtained from $ζ_{i} (k) = \frac{m + η M}{Δ_{i} (k) + η M}$ , where $η$ is the resolution coefficient and 0.5 is taken.
(6): Grey correlation calculation: the grey correlation calculation formula is $ζ_{i} = \frac{1}{19} \sum_{k = 1}^{19} ζ_{i} (k)$ , i = 1, 2, 3; k = 1, 2, … 19. By substituting the data, the correlation degree of total dust concentration at the driver’s position is ${\bar{R}}_{i} = (ζ_{1}, ζ_{2}, ζ_{3}) = (0.5966, 0.5928, 0.5815)$ .

Similarly, the correlation degree of dust concentration at the driver’s position is (0.6519, 0.6526, 0.6455), the correlation degree of total dust concentration at the pedestrian’s position is (0.6725, 0.6683, 0.6503), and the correlation degree of dust concentration at the pedestrian’s position is (0.6534, 0.6770, 0.6631), as shown in Figure 16. The greater the grey correlation degree

ζ_{i}

, the greater the influence on the dust concentration at this location, and vice versa. According to the analysis of grey correlation results, it can be seen that the influencing factors on the total dust concentration at the position of drivers and pedestrians are of the same importance, and the order is L > V_a > Q, that is, the main influencing factors on the total dust concentration at the position of drivers and pedestrians are the L, followed by the V_a, and finally the Q. The order of importance of influencing factors on the dust concentration of the driver’s position is as follows: V_a > L > Q, that is, the main influencing factor on the dust concentration of the driver’s position is V_a, followed by the L, and finally the Q. The order of importance of influencing factors on the dust concentration at the pedestrian position is as follows: V_a > Q > L, that is, the main influencing factor on the dust concentration at the pedestrian position is the V_a, followed by the Q, and finally the L. Because respirable dust has a greater harmful effect on the human body, in order to reduce the respirable dust, we can first consider improving the V_a, that is, increasing the Q, and at the same time, we can appropriately shorten the L to speed up the dust discharge.

4. Discussion

In this paper, dust removal by ventilation with long pressure and short suction is studied in detail. The air flow field under the condition of long pressure and short suction ventilation is divided into return, vortex, and jet zones, which is consistent with the reference [45]. It can be measured in the vortex zone that the dust removal device can be added to reduce the dust concentration. In order to effectively remove fine dust, spray dusting should be carried out when the dust concentration is high. In addition, this study can provide theoretical guidance for the determination of parameters such as the optimal L, V_a, and Q. The study in this paper still has certain limitations due to the obstacles of equipment and space in the actual roadway, and the numerical simulation results may be different from the actual situation in the field. Numerical simulations often require building models based on assumptions and simplifications that may not be completely consistent with the actual situation. The formation of the three areas requires a certain amount of time, and the optimal opening time of the air duct needs to be further studied.

5. Conclusions

A combination of similar tests and numerical simulation was used to study the distribution of the air flow field and the dust field in the driving face under the condition of long pressure and short suction ventilation. The main conclusions are as follows:

(1): The air flow field under the condition of long pressure and short suction ventilation is divided into return, vortex, and jet zones. The longer the L, the more the wind speed of the jet decreases, resulting in a lower wind speed of the reflux. The position and size of the vortex formed along the roadway are different under different mixed ventilation parameters.
(2): When the distance from the vent to the driving surface of the pressure duct is 1.6 m, the wind speed V_a at the outlet of the pressure duct is 8 m/s, and the extraction ratio Q is 0.8, the total dust concentration at the driver and pedestrian is 24.09 mg/m³ and 23.98 mg/m³, respectively. The exhaled dust concentrations were 13.94 mg/m³ and 9.15 mg/m³, respectively. Although the best air flow control scheme under the long pressure and short suction ventilation mode has been determined, the dust concentration at the driver’s position along the driving roadway exceeds the 10 mg/m³ prescribed by the regulations, and other auxiliary dust removal measures such as spray dust removal and chemical dust removal should be taken at the same time.
(3): Through grey correlation analysis, it is found that the factors affecting the total dust concentration at the location of drivers and pedestrians are of the same importance, and the order is L > V_a > Q. The order of importance of influencing factors on the concentration of dust at the driver’s position is V_a > L > Q.; and the order of importance of influencing factors on the dust concentration at the pedestrian’s position is V_a > Q > L. Increasing the air supply volume and shortening the L have a significant effect on accelerating dust discharge.

Author Contributions

Conceptualization, Y.Z.; methodology, B.R.; software, Y.Z.; validation, Y.Z.; formal analysis, Y.Z.; data curation, Y.Z.; writing—original draft preparation, Y.Z.; writing—review and editing, G.Y.; visualization, Y.Z.; funding acquisition, B.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China, grant number 52104179, and the Independent Research fund of the Joint National–Local Engineering Research Centre for Safe and Precise Coal Mining (Anhui University of Science and Technology), grant number EC2022014.

Data Availability Statement

The data is unavailable due to privacy or ethical restrictions.

Conflicts of Interest

The authors declare no conflicts of interest.

Nomenclature

Abbreviation	Explanation
L	Distance from the vent to the driving surface of the pressure duct, m
V_a	Wind speed at the outlet of the pressure duct, m/s
Q	Ratio of pumped air volume to pressurized air volume
T_d	Driver’s position total dust concentration, mg/m³
T_p	Pedestrian’s position total dust concentration, mg/m³
R_d	Driver’s position exhaled dust concentration, mg/m³
R_p	Pedestrian’s position exhaled dust concentration, mg/m³
$S_{t k}$	Stokes criterion number
$H_{o}$	Homogeneity criterion number
$F_{r}$	Froude criterion number
$E_{u}$	Euler criterion number
$R_{e}$	Reynolds criterion number

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Figure 1. Long pressure short suction ventilation dust removal experimental platform.

Figure 2. Variation in wind speed.

Figure 3. Verification of wind speed and dust concentration along the roadway. (a) Wind velocity. (b) Dust concentration.

Figure 4. Effect of L on the wind flow field.

Figure 5. Changes in roadway wind speed along different distances from the air outlet of the pressure duct to the driving surface. (a) Pressure side. (b) Central axis. (c) Extraction side.

Figure 6. Air flow field along the roadway at different pressure tuyere wind speeds.

Figure 7. Changes in roadway wind speed along different pressure tuyere wind speeds. (a) Pressure side. (b) Central axis. (c) Extraction side.

Figure 8. Conditions of air flow field in roadway under different ratios of pumping pressure and air volume.

Figure 9. Changes in roadway wind speed along the road with different pumping air volume ratios. (a) Pressure side. (b) Central axis. (c) Extraction side.

Figure 10. Effect of L on particulate matter distribution.

Figure 11. Influence of L on dust distribution along the roadway. (a) Total dust concentration on the pressure side. (b) Total dust concentration at the central axis. (c) Total dust concentration on the exhaust side. (d) Respirable dust concentration on the pressure side. (e) Respirable dust concentration at the central axis. (f) Respirable dust concentration on the exhaust side.

Figure 12. Distribution of particulate matter under different pressure wind speeds.

Figure 13. Influence of V_a on dust distribution along the roadway. (a) Total dust concentration on the pressure side. (b) Total dust concentration at the central axis. (c) Total dust concentration on the exhaust side. (d) Respirable dust concentration on the pressure side. (e) Respirable dust concentration at the central axis. (f) Respirable dust concentration on the exhaust side.

Figure 14. Distribution of particulate matter under different pumping air volume ratios.

Figure 15. Influence of Q on dust distribution along the roadway. (a) Total dust concentration on the pressure side (b) Total dust concentration at the central axis (c) Total dust concentration on the exhaust side (d) Respirable dust concentration on the pressure side (e) Respirable dust concentration at the central axis (f) Respirable dust concentration on the exhaust side.

Figure 16. Correlation degree of each influencing factor.

Table 1. Geometrical parameters used in the present model.

Properties	Value (m)
X	9
Y	2
Z	2
Pressure duct diameter	0.4
Exhaust duct diameter	0.3
Distance from supply vent to face	0.8–3.2 (Mobile)
Distance from exhaust vent to face	0.8 (Stationary)
Dust-generating surface area	0.25 × 0.25

Table 2. Parameter settings.

Name	Parameters	Value
General	Type	Pressure-based
Air	Density	1.225 kg/m³
Air	Viscosity	1.79 × 10⁻⁵ kg/(m·s)
Solution	Method	SIMPLEC
Solution	Total time	160 s
Discrete phase	Injection type	Surface
	Material	Coal-hv
	Diameter distribution	Rosin–Rammler
	Min. Diameter	4.05 × 10⁻⁷ m
	Max. Diameter	9.81 × 10⁻⁵ m
	Mean Diameter	1.38 × 10⁻⁵ m
	Spread Parameter	0.855
	Number of Diameters	20
	Drag Law	Spherical

Table 3. Simulation scheme.

Number	L	V_a	Q
1	0.8	8	0.6
2	1.2	8	0.6
3	1.6	8	0.6
4	2.0	8	0.6
5	2.4	8	0.6
6	2.8	8	0.6
7	3.2	8	0.6
8	1.6	4	0.6
9	1.6	6	0.6
10	1.6	10	0.6
11	1.6	12	0.6
12	1.6	14	0.6
13	1.6	16	0.6
14	1.6	8	0.2
15	1.6	8	0.3
16	1.6	8	0.4
17	1.6	8	0.5
18	1.6	8	0.7
19	1.6	8	0.8

Table 4. Total dust and exhaled dust concentration of driver and pedestrian at different L values.

L (m)	0.8	1.2	1.6	2	2.4	2.8	3.2
Td (mg/m³)	89.94	233.87	69.44	102.39	45.34	69.91	49.53
Tp (mg/m³)	67.95	61.482	52.55	144.96	148.72	79.09	76.33
Rd (mg/m³)	39.07	44.27	21.34	29.32	10.98	20.02	10.43
Rp (mg/m³)	32.70	31.95	16.69	51.24	72.51	30.79	33.62

Table 5. Total dust and exhaled dust concentrations at different V_a for drivers and pedestrians.

V_a (m/s)	4	6	8	10	12	14	16
Td (mg/m³)	212.41	96.57	69.44	56.08	76.04	51.73	60.54
Tp (mg/m³)	87.81	59.61	52.55	49.27	33.87	28.12	34.69
Rd (mg/m³)	66.87	24.31	21.34	20.58	29.34	16.40	31.48
Rp (mg/m³)	54.36	18.54	16.69	22.90	7.45	11.72	16.24

Table 6. Total dust and exhaled dust concentration of drivers and pedestrians at different Q values.

Q	0.2	0.3	0.4	0.5	0.6	0.7	0.8
Td (mg/m³)	202.47	180.00	174.07	158.40	69.44	36.32	24.09
Tp (mg/m³)	134.35	124.89	120.59	78.69	52.55	65.25	23.98
Rd (mg/m³)	48.81	49.40	52.05	47.66	21.34	20.38	13.94
Rp (mg/m³)	72.89	46.86	49.16	35.69	16.69	40.21	9.15

Table 7. Data of main influencing factors on dust concentration.

Number	L (X₁)	V_a (X₂)	Q (X₃)	T_d (X₀)	T_p (X₀₁)	R_d (X₀₂)	R_p (X₀₃)
1	0.8	8	0.6	89.94	67.95	39.07	32.70
2	1.2	8	0.6	233.87	61.48	44.27	31.95
3	1.6	8	0.6	69.44	52.55	21.34	16.69
4	2	8	0.6	102.39	144.96	29.32	51.24
5	2.4	8	0.6	45.34	148.72	10.98	72.51
6	2.8	8	0.6	69.91	79.09	20.02	30.79
7	3.2	8	0.6	49.53	76.33	10.43	33.62
8	1.6	4	0.6	212.41	87.81	66.87	54.36
9	1.6	6	0.6	96.57	59.61	24.31	18.54
10	1.6	10	0.6	56.08	49.27	20.58	22.90
11	1.6	12	0.6	76.04	33.87	29.34	7.45
12	1.6	14	0.6	51.73	28.12	16.40	11.72
13	1.6	16	0.6	60.54	34.69	31.48	16.24
14	1.6	8	0.2	202.47	134.35	48.81	72.89
15	1.6	8	0.3	180.00	124.89	49.40	46.86
16	1.6	8	0.4	174.07	120.59	52.05	49.16
17	1.6	8	0.5	158.40	78.69	47.66	35.69
18	1.6	8	0.7	36.32	65.25	20.38	40.21
19	1.6	8	0.8	24.09	23.98	13.94	9.15

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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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MDPI and ACS Style

Zheng, Y.; Ren, B.; Yu, G. Influence of Long Pressure and Short Suction Ventilation Parameters on Air Flow Field and Dust Migration in Driving Face. Sustainability 2024, 16, 7786. https://doi.org/10.3390/su16177786

AMA Style

Zheng Y, Ren B, Yu G. Influence of Long Pressure and Short Suction Ventilation Parameters on Air Flow Field and Dust Migration in Driving Face. Sustainability. 2024; 16(17):7786. https://doi.org/10.3390/su16177786

Chicago/Turabian Style

Zheng, Yuannan, Bo Ren, and Guofeng Yu. 2024. "Influence of Long Pressure and Short Suction Ventilation Parameters on Air Flow Field and Dust Migration in Driving Face" Sustainability 16, no. 17: 7786. https://doi.org/10.3390/su16177786

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Influence of Long Pressure and Short Suction Ventilation Parameters on Air Flow Field and Dust Migration in Driving Face

Abstract

1. Introduction

2. Model and Method

2.1. Model

2.1.1. Experiment Platform

2.1.2. Construction of CFD Model

2.2. Simulation Parameter

3. Results

3.1. Influence of Mixed Ventilation Parameters on Air Flow Field of Roadway

3.1.1. Influence of L on Air Flow Field of Roadway

3.1.2. Influence of Wind Speed at the Outlet of Pressure Duct on Air Flow Field in Roadway

3.1.3. The Influence of Suction Gas Ratio on Air Flow Field in Roadway

3.2. Influence of Mixed Ventilation Parameters on Dust Field of Roadway

3.2.1. Influence of L on Dust Field of Roadway

3.2.2. Influence of Wind Speed at the Outlet of Pressure Duct on Dust Field in Roadway

3.2.3. Influence of Suction Gas Ratio on Dust Field in Roadway

3.3. Grey Correlation Analysis

4. Discussion

5. Conclusions

Author Contributions

Funding

Data Availability Statement

Conflicts of Interest

Nomenclature

References

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Number	L	V_a	Q
1	0.8	8	0.6
2	1.2	8	0.6
3	1.6	8	0.6
4	2.0	8	0.6
5	2.4	8	0.6
6	2.8	8	0.6
7	3.2	8	0.6
8	1.6	4	0.6
9	1.6	6	0.6
10	1.6	10	0.6
11	1.6	12	0.6
12	1.6	14	0.6
13	1.6	16	0.6
14	1.6	8	0.2
15	1.6	8	0.3
16	1.6	8	0.4
17	1.6	8	0.5
18	1.6	8	0.7
19	1.6	8	0.8

Number	L	V_a	Q
1	0.8	8	0.6
2	1.2	8	0.6
3	1.6	8	0.6
4	2.0	8	0.6
5	2.4	8	0.6
6	2.8	8	0.6
7	3.2	8	0.6
8	1.6	4	0.6
9	1.6	6	0.6
10	1.6	10	0.6
11	1.6	12	0.6
12	1.6	14	0.6
13	1.6	16	0.6
14	1.6	8	0.2
15	1.6	8	0.3
16	1.6	8	0.4
17	1.6	8	0.5
18	1.6	8	0.7
19	1.6	8	0.8

Number	L	V_a	Q
1	0.8	8	0.6
2	1.2	8	0.6
3	1.6	8	0.6
4	2.0	8	0.6
5	2.4	8	0.6
6	2.8	8	0.6
7	3.2	8	0.6
8	1.6	4	0.6
9	1.6	6	0.6
10	1.6	10	0.6
11	1.6	12	0.6
12	1.6	14	0.6
13	1.6	16	0.6
14	1.6	8	0.2
15	1.6	8	0.3
16	1.6	8	0.4
17	1.6	8	0.5
18	1.6	8	0.7
19	1.6	8	0.8