Subway Tunnel Research Articles

Discussion on Construction Technology of Subway Tunnel Expansion under Bridge Foundation

As the urban populations grow, the number and size of subway construction projects are increasing while also meeting higher construction standards. So, subway construction projects must have a better understanding of construction technology. This article focuses on the construction technology of the subway tunnel expansion under the bridge foundation. By analyzing the engineering characteristics of the bridge foundation and using a project as an example, this article provides a detailed discussion of the construction process of tunnel expansion under a bridge foundation. This article aims to serve as a reference for subway tunnel construction in China to ensure the key points of construction technology are understood, thus improving construction quality and laying a solid technical foundation for the sustainable development of urban rail engineering.

An Approach to Capturing Residual Energy From the Subway System: Methodological Considerations

Abstract Urban heating and cooling demands account for a significant portion of global energy consumption. It is crucial to explore new energy resources and innovative solutions to meet environmental targets. Urban infrastructures like data centers, water networks, and tunnels move and collect energy, in some cases residual energy, that is valuable because of its proximity to consumers. The novelty of this work lies in the exploration of utilizing the accumulated residual heat that is not used in subway air to improve the energy efficiency of urban areas. The work focuses on the potential use of this residual heat by the installation of heat pumps in subway platforms or tunnels. By installing a heat pump on subway platforms or tunnels, this residual heat can be efficiently utilized for heating demand or producing domestic hot water. A general methodology for assessing the performance of such air source heat pumps in the subway context is presented. The calculation of the coefficients of performance (COP) and seasonal coefficients of performance (SCOP) calculation is outlined, with a detailed example illustrating the methodology. The paper emphasizes a comparative analysis between the proposed system and a traditional heat pump using ambient air, highlighting the advantages of the proposed approach. Finally, the paper concludes with a brief analysis of the different effects of refrigerants on the system performance for the same boundary conditions. Results are promising, increasing the energy efficiency of big cities and reducing CO2 emissions.

Numerical Analysis of the Effect of River Channel Excavation on Existing Subway Tunnels

Numerical Analysis of the Effect of River Channel Excavation on Existing Subway Tunnels

Application and Research of Distributed Acoustic Sensing in Vibration Monitoring of Subway Tunnels

With the booming development of the rail transit industry and the increase in the construction and operation of mileage, the health status of infrastructure such as vehicles, tracks, and trains, as well as operational safety, have received widespread attention. Distributed optical fiber sensing technology has the characteristics of long monitoring distance, strong real-time performance, and highly economical, and has broad prospects in rail transit applications. This paper adopts Distributed Acoustic Sensing technology to obtain vibration information along the subway tunnel, analyzes the time-domain signal and frequency-domain energy characteristics of train vibration, as well as the passing time, direction, and location of the train, providing technical support for the safe operation of the subway.

Analysis of the Influence of Adjacent New Pile Foundation Construction on the Structural Deformation of the In-service Subway Tunnels

Taking the construction project of a new bridge pile foundation above an in-service subway in Xi’an as an example, considering the influence of horizontal symmetrical construction of pile foundation hole forming on the deformation of different sections of asymmetric tunnels, a three-dimensional finite element geometric model of pile-tunnel-soil is established based on ABAQUS software. Through the numerical simulation analysis of the structural deformation behavior of the in-service subway tunnel under the two construction stages of pile foundation hole forming and concrete pouring, the horizontal and vertical deformation laws of the key points of the in-service subway tunnel caused by the construction of the adjacent new pile foundation are analyzed from different angles.The calculation results show that: the deformation of the interval tunnel is mainly caused by vertical displacement, resulting in overall settlement of the tunnel. However, the settlement value is within a controllable range and does not affect the normal operation of the in-service subway tunnel. The concrete pouring stage has a greater impact on subway tunnels. The research work has important reference value for the reasonable safety monitoring and control of similar construction projects.

Three-Dimensional Point Cloud Denoising for Tunnel Data by Combining Intensity and Geometry Information

At present, three-dimensional laser scanners are used to scan subway shield tunnels and generate point cloud data as the basis for extracting a variety of information about tunnel defects. However, there are obstacles in the tunnel such as pipelines, tracks, and signaling systems that cause noise in the point cloud. Usually, the data of the tunnel point cloud are huge, and the efficiency of artificial denoising is low. Faced with this problem, based on the respective characteristics of the geometric shape and reflection intensity of the tunnel point cloud and their correlation, this paper proposes a tunnel point cloud denoising method. The method includes the following three parts: reflection intensity threshold denoising, joint shape and reflection intensity denoising, and shape denoising. Through the experiment on the single-ring segment point cloud of a shield tunnel, the method proposed in this paper takes 2 min to remove 99.77% of the noise in the point cloud. Compared with manual denoising, the method proposed in this paper takes two fifteenths of the time to achieve the same denoising effect. The method proposed in this paper meets the requirements of a tunnel point cloud data survey. Thus, it provides support for the efficient, accurate, and automatic daily maintenance and surveys of tunnels.

3D numerical investigation of the interaction between interchange tunnels at different angles

The development of subway and highway tunnels has led to the spatial intersection of tunnels, significantly impacting tunnel deformation, lining stress, and ground settlement during construction. To study the influence of critical parameters such as the cross angle and centre-to-centre distance on the tunnel performance, a series of numerical simulations were carried out. The influence range and magnitude of stress in the spatial cross tunnel under different cross angles were determined. The results indicated that as the crossing angle increased, the stress on the lining decreased, and the vault displacement increased. Meanwhile, the parallel tunnels showed opposite tendencies. Based on these results, the crossing angle of the cross tunnels was suggested to be greater than 45°. Parallel tunnels should be considered individually because the loading is symmetrically distributed. Considering the vault displacement and von Mises stress of the lining, it is recommended that the tunnel spacing be greater than 2D. The numerical model was validated against field data, and the findings of this study can be useful in designing cross tunnels.

Adaptive mutation sparrow search algorithm-Elman-AdaBoost model for predicting the deformation of subway tunnels

A novel coupled model integrating Elman-AdaBoost with adaptive mutation sparrow search algorithm (AM-SSA), called AMSSA-Elman-AdaBoost, is proposed for predicting the existing metro tunnel deformation induced by adjacent deep excavations in soft ground. The novelty is that the modified SSA proposes adaptive adjustment strategy to create a balance between the capacity of exploitation and exploration. In AM-SSA, firstly, the population is initialized by cat mapping chaotic sequences to improve the ergodicity and randomness of the individual sparrow, enhancing the global search ability. Then the individuals are adjusted by Tent chaotic disturbance and Cauchy mutation to avoid the population being too concentrated or scattered, expanding the local search ability. Finally, the adaptive producer-scrounger number adjustment formula is introduced to balance the ability to seek the global and local optimal. In addition, it leads to the improved algorithm achieving a better accuracy level and convergence speed compared with the original SSA. To demonstrate the effectiveness and reliability of AM-SSA, 23 classical benchmark functions and 25 IEEE Congress on Evolutionary Computation benchmark test functions (CEC2005), are employed as the numerical examples and investigated in comparison with some well-known optimization algorithms. The statistical results indicate the promising performance of AM-SSA in a variety of optimization with constrained and unknown search spaces. By utilizing the AdaBoost algorithm, multiple sets of weak AMSSA-Elman predictor functions are restructured into one strong predictor by successive iterations for the tunnel deformation prediction output. Additionally, the on-site monitoring data acquired from a deep excavation project in Ningbo, China, were selected as the training and testing sample. Meanwhile, the predictive outcomes are compared with those of other different optimization and machine learning techniques. In the end, the obtained results in this real-world geotechnical engineering field reveal the feasibility of the proposed hybrid algorithm model, illustrating its power and superiority in terms of computational efficiency, accuracy, stability, and robustness. More critically, by observing data in real time on daily basis, the structural safety associated with metro tunnels could be supervised, which enables decision-makers to take concrete control and protection measures.

Monitoring and early warning mechanism of flood invasion into subway tunnels based on the experimental study of flooding patterns

Monitoring and early warning mechanism of flood invasion into subway tunnels based on the experimental study of flooding patterns

High-Precision Map Construction in Degraded Long Tunnel Environments of Urban Subways

In response to the demand for high-precision point cloud mapping of subway trains in long tunnel degradation scenarios in major urban cities, we propose a map construction method based on LiDAR and inertial measurement sensors. This method comprises a tightly coupled frontend odometry system based on error Kalman filters and backend optimization using factor graphs. In the frontend odometry, inertial calculation results serve as predictions for the filter, and residuals between LiDAR points and local map plane point clouds are used for filter updates. The global pose graph is constructed based on inter-frame odometry and other constraint factors, followed by a smoothing optimization for map building. Multiple experiments in subway tunnel scenarios demonstrate that the proposed method achieves robust trajectory estimation in long tunnel scenes, where classical multi-sensor fusion methods fail due to sensor degradation. The proposed method achieves a trajectory consistency of 0.1 m in tunnel scenes, meeting the accuracy requirements for train arrival, parking, and interval operations. Additionally, in an industrial park scenario, the method is compared with ground truth provided by inertial navigation, showing an accumulated error of less than 0.2%, indicating high precision.

Displacement Monitoring of Subway Tracks and Tunnels According to Adjacent Construction

In the Republic of Korea, large-scale deep excavation construction is being conducted adjacent to structures owing to overpopulation in urban areas. Securing the safety of earth-retaining and underground structures is crucial for adjacent excavation work in urban areas. Accordingly, an automated measurement system is used to monitor the behaviors of subway tunnels and track structures; however, the utilization of its results is extremely low. Existing techniques evaluate the safety of track and tunnel structures based on the measured maximum values. This study introduces an evaluation technique for improving behavior monitoring in subway tunnels and track structures. A substantial amount of long-term measurement data on subway tunnels and track deformation was quantitatively evaluated using the Gaussian probability density function. In addition, the results from the same location where the tunnel convergence meter (TL) and track bed settlement (RM) sensors were located were compared. The comparison results revealed a difference in the vertical displacement of the tunnel and track structure owing to adjacent excavation work. A technique to analyze the continuous behavior of the tunnel was presented by numerically analyzing the tunnel measurement results as input data. In addition, they emphasized the need for simultaneous monitoring of tracks and tunnels.

A Review of Deep Learning Applications in Tunneling and Underground Engineering in China

With the advent of the era of big data and information technology, deep learning (DL) has become a hot trend in the research field of artificial intelligence (AI). The use of deep learning methods for parameter inversion, disease identification, detection, surrounding rock classification, disaster prediction, and other tunnel engineering problems has also become a new trend in recent years, both domestically and internationally. This paper briefly introduces the development process of deep learning. By reviewing a number of published papers on the application of deep learning in tunnel engineering over the past 20 years, this paper discusses the intelligent application of deep learning algorithms in tunnel engineering, including collapse risk assessment, water inrush prediction, crack identification, structural stability evaluation, and seepage erosion in mountain tunnels, urban subway tunnels, and subsea tunnels. Finally, it explores the future challenges and development prospects of deep learning in tunnel engineering.

Crack Width Recognition of Tunnel Tube Sheet Based on YOLOv8 Algorithm and 3D Imaging

Based on the tunnel crack width identification, there are operating time constraints, limited operating space, high equipment testing costs, and other issues. In this paper, a large subway tunnel is a research object, and the tunnel rail inspection car is an operating platform equipped with industrial cameras in order to meet the requirements of the tunnel tube sheet crack width recognition of more than 0.2 mm, with the measuring instrument to verify that the tunnel rail inspection car in the state of uniform motion camera imaging quality has the reliability through the addition of laser rangefinders, the accurate measurement of the object distance and the calculation of the imaging plane and the angle of the plane to be measured, to amend the three-dimensional cracks. The pixel resolution of the image is corrected, the images imaged by the industrial camera are preprocessed, the YOLOv8 algorithm is used for the intelligent extraction of crack morphology, and finally, the actual width is calculated from the spacing between two points of the crack. The crack detection width obtained by image processing using the YOLOv8 algorithm is basically the same as the value of crack width obtained by manual detection, and the error rate of crack width detection ranges from 0% to 11%, with the average error rate remaining below 4%. Compared with the crack detection error rate of the Support Vector Machine (SVM), the crack extraction model is reduced by 1%, so using the tunnel inspection vehicle as a platform equipped with an industrial camera, YOLOv8 is used to realize the recognition of the shape and width of the cracks on the surface of the tunnel tube sheet to meet the requirements of a higher degree of accuracy. The number of pixels and the detection error rate are inversely proportional to each other. The angle between the imaging plane and the plane under test is directly proportional to the detection error rate. The angle between the vertical axis where the lens midpoint is located and the line connecting the shooting target and the lens center point is αi and the angle θi between the measured plane and the imaging plane is reciprocal, i.e., αi + θi = 90°. Therefore, using the inspection vehicle as a mobile platform equipped with an industrial camera and based on the YOLOv8 algorithm, the crack recognition of the tunnel tube sheet has the feasibility and the prospect of wide application, which provides a reference method for the detection of cracks in the tunnel tube sheet.

Optimizing Sequential Excavation Method for Ground Settlement Control in Tehran Subway Tunnel Line 6

Optimizing Sequential Excavation Method for Ground Settlement Control in Tehran Subway Tunnel Line 6

Safety risk assessment model of a subway tunnel collapse system based on improved DOW-FFTA method

Abstract Green construction considers factors such as quality, safety, efficiency, environmental protection and ecology. Under the premise of balancing basic construction capacity and green construction, prioritizing construction safety requirements and exploring the risk assessment system for the green construction of subway projects is crucial. Traditional risk assessment methods in the study of local system risks have been mostly applied to simple systems; thus, risk identification and assessment methods lack universality. The questions of how to change the existing structure of the system safety risk assessment model and establish a realistic modeling approach, as well as implement dynamic risk supervision, have become urgent problems. Here, we investigated the event risk point and proposed an integrated evaluation method of inherent, initial and real risks based on system attributes. The improved DOW chemical method was used to solve the static inherent risk severity index, and fuzzy fault tree analysis (FFTA) was used to judge the probability of out-of-control local state management. Considering the abnormal situation and the emergence of new risk information, a dynamic correction model was proposed. Finally, a static risk assessment model was established in line with the actual state of the system with local management and realistic risk assessment models that could modify the initial risk over time.

Discussion on the Application of Grouting in Underground Engineering

With the development of China's economy, in some large cities, surface transportation alone can no longer meet people's needs today, and the development of underground engineering is increasingly catering to the needs of the public. During the excavation process of subway tunnels, it is inevitable that they may be threatened by groundwater, and grouting technology is one of the effective methods for preventing and controlling water in underground engineering. The mechanism of slurry flow and diffusion varies depending on the soil conditions. When underground projects such as subway tunnels pass through poor geological conditions, it is highly likely to cause significant surface subsidence, and even engineering disasters such as water inrush and collapse may occur. To ensure the safety of underground engineering construction in the geological strata, it is often necessary to carry out advanced grouting in the strata to achieve the purpose of reinforcement or water blocking. Advanced grouting reinforcement belongs to concealed engineering, and the existing advanced grouting construction mostly relies on experience and on-site grouting tests, making it difficult to achieve the expected grouting effect. Therefore, it is of great theoretical and engineering significance to conduct in-depth research on the diffusion mechanism of slurry in geological grouting reinforcement engineering, as well as the influence of factors such as slurry water cement ratio and geological characteristics on the diffusion form of slurry.

Burning characteristic and ceiling temperature of moving fires in a tunnel: A comparative study

Moving fire is a very important fire scenario in highway tunnel and subway tunnel. Compared to fixed fire sources, there is still limited research on moving fires in tunnels. In order to reveal the burning characteristics and evolutionary mechanisms of moving fires in tunnels, this study conducted reduced scale tunnel fire experiments on moving fires under natural ventilation conditions (Movefire) at travelling speeds ranging from 0.5 m/s to 2.0 m/s, as well as fixed fires under longitudinal ventilation (Ventfire) velocities ranging from 0.5 m/s to 2.0 m/s. The results demonstrate that it is unreasonable to solely use Ventfire experiments as a substitute for Movefire experiments to study fire development and ceiling smoke temperature distributions. When the travelling speed of fire and the ventilation velocity were equal, the HRRs of Movefires were less than those of Ventfires. At the same relative moving velocity of 0.5 m/s, Ventfire received more fresh air to increase burning intensity, while Movefire experienced decreases in thermal feedback and burning intensity. The Movefire smoke temperature rise was small and short in duration, while the Ventfire smoke temperature rise was large and long in duration. Furthermore, the dimensionless maximum ceiling temperature rise of the Movefire experiment was lower than that of the Ventfire experiment. And then a modified ceiling temperature model applicable to the Movefire experiment was proposed by introducing a speed correction factor.

Multi visual images fusion approach for metro tunnel defects based on saliency optimization of pixel level defect image features

The multi-vision defect sensing system, lining composed primarily of IRT and RGB cameras, allows for automatic identification and extraction of small surface ailments, greatly enhancing detection efficiency. However, the presence of various issues like train vibration, inconsistent lighting, fluctuations in temperature and humidity leads to the images showing inadequate uniformity in illumination, blurriness, and a decrease in the level of detail. The above issues have led to unsatisfactory fusion processing results for multiple visual images and increased missed detection rates. To address the above-mentioned issue, multi visual images fusion approach for subway tunnel defects based on saliency optimization of pixel level defect image features is proposed. The approach initially analyses the train’s motion status and image blurring conditions. It then eliminates the dynamic blurring in the image. Secondly, Image weights are allocated based on the uniformity of visible light image illumination in the tunnel, as well as real-time temperature and humidity. Finally, image feature extraction and fusion are performed by a U-Net network that integrates channel attention mechanisms. The entire experiment was carried out on a dataset consisting of leakage data from the tunnel lining of Shanghai Metro and tunnel defect data from Beijing Metro. The experimental results demonstrate that this approach improves the image pixel value variation rate by 39.7%, enhances the edge quality by 23%, and outperforms similar approach in terms of average gradient, gradient quality, and sum of difference correlation with improvements of 15.9%, 7.3%, and 26.6% respectively.

A subway tunnel under wear Chan river construction risk evaluation and control methods

Poor rich water sand flow plasticity and permeability coefficient, Angle of internal friction, etc. For effective control, avoid and reduce the subway next in action in the process of river construction risk, guarantee the construction task smoothly. For the construction of risk source analysis and identification of system construction of risk hierarchy, using analytic hierarchy process (ahp) and fuzzy comprehensive evaluation method to find the risk of subway construction. The results show that the construction has a "medium risk" and easy to rise to the "high risk".

Comparing the Velocity Spectrum Caused by the Presence of Circular Urban Subway Tunnels With Free‐Field Conditions

For structures in the near field, the velocity spectrum is significant. The aim of this study is to examine, taking into account the soil–structure interaction (SSI), how metropolitan subway tunnels with a circular cross section in alluvial soils affect the ground surface velocity spectrum. The frequency of the soil–tunnel systems was altered by varying the parameters of the soil and the geometrical features of the tunnel, such as the radius, the lining’s thickness, and the depth of burial. The maximum velocity was determined at several sites on the ground surface as well as the tunnel crown. Based on the soil–tunnel system’s period, the spectrum velocity graph was produced by averaging and squaring the standard deviation of the highest velocity for every frequency. Ansys finite element software and Plaxis2D were used in this study. The findings demonstrate that the tunnel’s presence reduces spectral velocity (SV) relative to free‐field (FF) circumstances during the examined period at the position that corresponds to the ground‐based image of the tunnel crown. The tunnel’s existence lowers the ground‐level velocity range by 14.5 percent. By moving away from the image of the tunnel crown on the ground surface, the presence of the tunnel amplifies the SV at more points by 5.5% at long periods. In addition, the tunnel crown velocity spectrum was developed. The findings indicate that the velocity spectrum diagram’s envelope for the tunnel crown is a nonlinear function of the soil–tunnel system’s period.