The article delves into the critical issue of dust removal during tunnel construction, specifically focusing on the challenges posed by backflow. It integrates Computer Fluid Dynamics (CFD) simulation with laser visualization to analyze airflow dynamics and dust migration within tunnels. The study, conducted in the Zentrum am Berg (ZAB) tunnel in Austria, uses these advanced techniques to understand and optimize the efficiency of respirable dust removal. The research highlights the importance of proper ventilation duct placement and airflow management to mitigate the health risks associated with high quartz dust concentrations. The combination of simulation and observation provides a detailed and practical approach to improving safety and efficiency in tunnel construction.
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Abstract
The removal of respirable dust and harmful gasses in tunnel construction is a crucial topic for the occupational safety of tunnel construction workers. Mechanical ventilation is the most widely used method to remove the dust at present. But respirable dust is difficult to remove by sedimentation because of the small particle size. The setting of airflow rate in the ventilation duct and the distance between the ventilation duct and the working face highly affect the efficiency of dust removal. When the ventilation duct is far away from the working face, there is often no effective air flow reaching the working face due to the backflow. So, understanding the airflow distribution in the tunnel is necessary to evaluate dust removal effects. This contribution simulates the airflow of the Zentrum am Berg (ZAB) tunnel through numerical simulation and also sets up the laser device to visualize the air flow. The backflow sections from numerical simulation and laser visualization are verified and compared with each other to provide guidance on dust removal effect optimization during tunnel construction.
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1 Introduction
Tunnel blasting is a widely used excavation method during tunnel construction. But a massive amount of dust is generated during blasting, and among them there is respirable dust which can enter the alveolar area and react with lung tissue [1]. There is a high chance of suffering potentially irreversible damage, impaired lung function when being exposed to a high quartz dust concentration place for a long time [2]. A considerable amount of literature links quartz dust exposure to lung cancer, and the data shows that silica dust greatly increases the risk of death from respiratory and cardiovascular diseases [3‐5]. And underground workers are more likely to suffer from chronic silicosis compared to the workers of outdoor activities [6].
In most tunnels, forced ventilation is used to remove the dust. This means that the ventilation duct is blowing fresh air into the working face and bringing the polluted air and dust out of the tunnel. This process requires a certain distance and air flow rate to effectively remove the respirable dust. However, on construction sites, the ventilation duct is often not extended in time so the ventilation duct is too far away from the working face in most cases. Backflow happens before the fresh air reaches the working face, resulting in reduced dust removal efficiency in tunnel construction.
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Computer fluid dynamics simulation (CFD) is widely used to simulate the air flow in the tunnel. There are already many findings about the air flow direction and dust migration in the case of forced ventilation. Guo et al. [7] combined the CFD simulation and onsite measurement and found the optimal pressing air flow rate to reduce the dust concentration taking into account sustainable utilization of energy. Xie and Ming Qiao et al. [8, 9] changed the distance between the ventilation and the working face and simulated the air flow and dust concentrations inside the tunnel using the CFD package. Yang et al. [10] proposed a modularized airflow diverging system for ventilation for a better dust control effect and the system was simulated in CFD package and verified by experiments. Xie et al. [11] simulated the air flow and dust concentration and offered the optimal distance recommendation based on the cross section size of the tunnel.
The usage of CFD simulation in the research of air flow can offer the flexibility of the changing parameters, such as the air flow rate and distance between the ventilation duct and the work face, and help the researchers simulate the airflow and dust concentration. Additionally, the model can be verified by the onsite measurements.
There are already many investigations on how backflow influences the dust removal effect during tunnel construction. Zhou et al. [12] investigated the optimal setting of the forced ventilation duct and the ratio of pressing air volume to lab sorption air volume to form an effective flow to improve the efficiency of dust removal effect. Chang et al. [13] revealed that the zone near the working face can be divided into a jet zone, backflow zone, and vortex zone and distance of this zone from working face is crucial for the CO concentration during tunnel construction.
Laser visualization is an effective tool to reveal turbulence, separations, vortices, and more. In 1995, Jambunathan et al. [14] already used laser visualization to study the flow patterns around a cylinder. Laser visualization is already widely used in wind tunnel testing to understand the air flow inside and around the structure, such as the flow analysis around aircraft or urban pollutant propagation experiments [15]. Some scholars also use laser visualization in the context of building fires, such as identifying smoke layers in the case of a fire in a tunnel. [16‐19]. So, laser visualization will also help to capture the turbulence to understand the air flow inside the tunnel under forced ventilation.
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In this contribution, we used a combination of CFD and laser observation to compare and visualize the direction change of the flow from the ventilation duct, which is crucial for the optimization of the respirable dust removal effect during tunnel ventilation.
2 Methodology
2.1 CFD Simulation
The simulation is based on the tunnel of Zentrum am Berg (ZAB). It is an independent research infrastructure focusing on the construction and operation of underground facilities in Eisenerz, Austria. The tunnel part chosen for air flow and dust movement analysis is 105 meters long and the duct is at the right side of the construction direction, as shown in Fig. 1.
Fig. 1
Tunnel onsite picture of the size and duct location
The physical model of the tunnel is established in SpaceClaim by considering a 1:1 equal scale of tunnel with the length of 105 m and the duct is 62.5 m from the working face, as shown in Fig. 2a. The cross section of the tunnel is shown in Fig. 2b, with the following dimensions: 4.2 meters in width and 6.54 meters in height. The pressed-in ventilation duct with a diameter of 0.9 meters is located at the height of 3.75 meters and 2.2 meters from the central cross section of the tunnel. The air velocity of the ventilation duct is 9 m/s. The CFD simulation used is Ansys Fluent. To better understand the air flow distribution inside the tunnel and backflow location, we use vectors and contours to analyze the air flow.
Since the airflow in the tunnel has a high turbulence, using the laser device can more intuitively understand the airflow in the tunnel compared to a velocity measurement. In the ZAB tunnel, a laser light sheet is set under the ventilation duct visualizing the air flow at the central cross section of the ventilation duct downstream. The air flow visualization picture (Fig. 5) has been recorded approximately 30 meters away from the ventilation duct outlet.
The laser observation and the numerical simulation results are compared to analyze the backflow location which is crucial to optimize the respirable dust removal effect during tunnel construction.
3 Results and Discussion
3.1 Air Flow Analysis
The development of the air flow at the central cross section is shown in Fig. 3. It is the vector image showing the direction of the air flow in the central cross section of the ventilation duct, and to fully indicate the flow distribution inside the duct, we put the velocity inlet 10 m away from the ventilation duct outlet with a velocity of 12.8 m/s.
Fig. 3
Air velocity vectors at duct central cross section in length cut
The total flow velocity decreases in the section of 0–30 meters from the ventilation duct outlet, from 12.8 m/s at the duct outlet to 3 m/s at 30 meters from the ventilation duct. The air flow direction changes in the section of 30–35 meters from the ventilation duct outlet. So, in the section close to the working face where the blasting happened, there is nearly no flow towards the working face to remove the respirable dust.
Figure 4 is the contour picture every 10 meters from the ventilation duct outlet. Negative value means the flow towards the working face, and positive value means the flow going towards the outlet. As shown from the three contour pictures at 10 meters, there is still relatively strong air flow towards the working face with the maximum axial velocity of 6.5 m/s, but at 20 meters cross section, the value is reduced to 4 m/s. At the 30 meters cross section, the velocity going towards the working face is lower than 0.8 m/s.
Fig. 4
Contours of axial velocity for three cross sections
We can also observe the air flow direction change from the layers in the contour pictures. The line between yellow and green means the change of the positive value, and the negative value also means the change of air flow direction in our case. The area of the flow going towards the working face is decreasing from 10 meters to 30 meters from the ventilation duct outlet.
3.2 Backflow Comparison Based on Simulation and Observation
We have simulated the air flow in the central cross section of the ventilation duct from our CFD simulation and we compared our laser visualization picture taken in the tunnel with the vector picture from the simulation, shown in Fig. 5. The left picture was recorded at 30 meters from the ventilation duct approximately 5 min after the ventilation duct was switched on, the right picture shows the vectors at the central cross section of the ventilation duct. This is the view from the same location of the laser visualization picture, which is located 30 meters from the ventilation duct. In the laser picture, it can be seen that there is backflow in the lower part of the tunnel cross section, but there is still an effective flow on the upper side. This flow pattern is also shown in the vector picture from the simulation (Fig. 3).
Fig. 5
Comparison of laser visualization and CFD simulation
The laser visualization has successfully captured the happening of backflow before the air flow reaches the working face, which greatly reduces the respirable dust removal effect. It can be verified with the results of CFD simulation. Compared to the numerical simulation method, the laser technology offered a quicker way to visualize the air flow to figure out if there is an effective flow near the working face to remove the dust taking also the actual weather condition of the tunnel into consideration.
4 Conclusions
In this contribution, the CFD simulation method is used to simulate the air flow. We compared the air flow from the laser visualization and the vectors at the central duct cross section from the simulation results. The following conclusions are reported:
1.
In the case of 12.8 m/s, the air velocity from the duct and ventilation duct is 62.5 meters from the working face, the air velocity towards the working face is relatively low after 30 meters, and there is not sufficient air flow to removal the respirable dust near the working face.
2.
Laser air flow visualization is crucial in identifying the turbulence zone and back flow zone to better understand the air flow inside the tunnel and can have guidance on the accuracy of the CFD simulation and help to make decisions about the optimal distance between the ventilation duct and the working face.
3.
Dust particles can be added in the simulation and laser visualization process to further understand the movement trajectory of respirable dust under forced ventilation and offer advice on increasing respirable dust removal effect.
Acknowledgements
The laser visualization process is supported by MCI Innsbruck Fluids & Mechanics team. Thanks for the work and cooperation, and the results presented are from LUQUAS PROJECT, which is funded by the Austrian Research Promotion Agency (FFG). We would also like to thank the project partners for their technical support, namely Zentrum am Berg, BEMO Tunnelling GmbH, MCI Management Center Innsbruck, PORR Austria.
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