Urban Subway Research Articles

Mechanical characteristics and stability analysis of an innovative type of steel–concrete composite support in shallow-buried excavation tunnels

Under the influence of the principle of New Austrain Tunnelling Method (NATM), the initial support structure of shallow-buried tunnels in urban soft rock mainly adopts the forms of section steel arches or lattice girder arches combined with bolt-mesh-shotcrete. In order to solve the problems of tunnel deformation and collapse caused by untimely support or insufficient support strength during the construction process, the concept of “timely and high-strength support” was put forward, the high-strength steel pipe grid (HSPG) arch was innovatively designed, and the steel pipe grid bolt-shotcrete (SPGB) structure was established. Next, the flexural bearing performance and failure modes of the joint component and jointless component of the HSPG arch were analyzed, and the design scheme was also optimized by finite element simulation. Then, the full-scale model test of steel pipe grid concrete component (SPGC) under the pure bending load was conducted to explore the coupling bearing effect in a laboratory. In addition, relying on the underground excavation tunnel project of urban subway, the characteristic curves and stability coefficient of surrounding rock and SPGB structure were given by using the principle of convergence-confinement method. Theoretical calculations and on-sit measurements showed that SPGB structure had good adaptability in weak surrounding rock tunnel. In general, the research results were of great significance for clarifying the bearing mechanism and applicable conditions of SPGB structure, and also provided a reference for its further application in the tunnel and underground engineering.

An Urban Metro Section Flow Forecasting Method Combining Time Series Decomposition and a Generative Adversarial Network

Urban metro cross-section flow is the passenger flow that travels through a metro section. Its volume is a critical parameter for planning operation diagrams and improving the service quality of urban subway systems. This makes it possible to better plan the drive for the sustainable development of a city. This paper proposes an improved model for predicting urban metro section flow, combining time series decomposition and a generative adversarial network. First, an urban metro section flow sequence is decomposed using EMD (Empirical Mode Decomposition) into several IMFs (Intrinsic Mode Functions) and a trend function. The sum of all the IMF components is treated as the periodic component, and the trend function is considered the trend component, which are fitted by Fourier series function and spline interpolation, respectively. By subtracting the sum of the periodic and trend components from the urban metro section flow sequence, the error is regarded as the residual component. Finally, a GAN (generative adversarial network) based on the fusion graph convolutional neural network is used to predict the new residual component, which considers the spatial correlation between different sites of urban metro sections. The Chengdu urban metro system data in China show that the proposed model, through incorporating EMD and a generative adversarial network, achieves a 15–20% improvement in prediction accuracy at the cost of a 10% increase in the calculation time, meaning it demonstrates good prediction accuracy and reliability.

A Precise Analysis of the Behavior of Pit Side Tunnels Caused by Deep Excavation

As urbanization gathers pace, projects involving adjacent subway tunnels are increasing, thereby amplifying the need for robust tunnel protection measures. Currently, there exists a notable lack of precise analyses on the three‐dimensional (3D) deformation laws and mechanisms of tunnels affected by adjacent deep excavation. Moreover, the influence patterns of retaining wall stiffness and deep excavation depth on the 3D deformation of pit‐side tunnels remain unclear. The purpose of this research is to bridge the existing disparity by adopting the hypoplastic model, which effectively captures soil stiffness that is dependent on soil state, strain, and stress path, even at small strains, as well as soil strength, based on reported centrifuge model tests. This approach facilitates a comprehensive, precise numerical analysis of the interaction between deep excavation and preexisting tunnels located outside the retaining wall. The analysis sheds light on the deformation mechanisms and trends of pit‐side tunnels not solely confined to the longitudinal axis but extending to the transverse plane as well, while systematically examining the influence of varying excavation depths and retaining wall stiffness on key tunnel parameters, including longitudinal deformation, diameter changes, bending strains, and soil pressure distributions around the tunnels. The study reveals that if the tunnel situated outside the retaining structure lies beneath the foundation pit’s base, deep excavation only slightly deforms the tunnel. However, when the tunnel outside the retaining structure is positioned above the pit’s base, its deformation progressively intensifies with deeper excavation, but the growth rate has a decreasing trend. An enhancement in the stiffness of the retaining wall results in a notable decrease in the deformation exhibited by the adjacent tunnels. The findings contribute to a deeper understanding of the complex responses of pit‐side tunnels to excavation activities, ultimately facilitating the design and construction of safer and more resilient urban subway infrastructure.

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.

Post-earthquake functionality assessment for urban subway systems: Incorporating the combined effects of seismic performance of structural and non-structural systems and functional interdependencies

Post-earthquake functionality assessment for urban subway systems: Incorporating the combined effects of seismic performance of structural and non-structural systems and functional interdependencies

Integrating Regional Culture into Public Art within the Metro Public Space

Chinese artists with the development of China's economy and the accelerated construction of urbanization, public art expresses the collective consciousness and mainstream emotions in the process of China's social development. Seeking to express the revival and mutation of traditional culture in a proper artistic language, people hope to express their aspirations for the times through public art. China's urban subway public art is a typical manifestation of public art in the current stage of China's development, and has traveled with every important period of China's reform process, recording the traces of the times with works of art. China's subway public art has been diversified from the initial single form of expression, but there are still many shortcomings and problems, waiting for our artists and art workers to explore, China's subway public art to the world. China's urban subway public art has a successful case, but there is also the phenomenon of serious commercialization. China's urban subway public art has become an important platform for the historical heritage of the Chinese nation. The development of urban subway makes our urban public art more and more recognized by the public.

Evaluation of Different Work Zone Road-Occupation Schemes for Monorail Construction

Due to the increasing demand for transportation, road renovation is inevitable, and the emergence of work zones has become the most common problem in traffic control. There are many research results on the impact of work zones on traffic operation, but most of them focus on various capacity theoretical models or traffic flow control strategies and are mostly concentrated in highway work areas and urban road subway construction work areas. The location of these work zones is often unable to be changed and is mostly considered reasonable. At present, there is still a gap in selecting and evaluating the location of the work zone. Therefore, this article studied a bidirectional six-lane intersection in Xi’an and investigated the situation of traffic flow distortion caused by the setting of work zones at the intersection. Two different positions and forms of work zones were designed for evaluation and analysis. Firstly, we used VISSIM (2022 student) to simulate the original and proposed work zone road-occupation schemes and analyzed six indicators. Finally, in order to determine the optimal work zone locations under different traffic situations, we applied the entropy weight method (EWM) to assign weights to multiple indicators, thereby achieving a comprehensive assessment of various schemes. The results showed that the highest improvement level among the six indicators was 50.2%, and different schemes adapted to different traffic situations. However, occupying two lanes of the median opposite the exit lane performed better under high traffic volume. Occupying the median and lanes on both sides of the median is suitable for low traffic volume. Occupying two lanes of the entrance lane and using the opposite lane as the left-turn entrance lane is suitable for situations with high traffic volume in the opposite lane.

On group evacuation behavior of subway station halls using an improved evolutionary game model

This study is dedicated to examining the impact of stress on group evacuation behaviors in urban subway station fires, with the ultimate goal of improving evacuation efficiency and enhancing public safety. The authors have introduced an advanced evolutionary game model that combines “selfishness coefficient” and “stress threshold.” This introduces the concept of stress threshold and contributes to the exploration of stress propagation within groups. The simulation results indicate that the degree of selfishness in a crowd significantly affects evacuation efficiency. The emergence and propagation of stress emotions fundamentally represent a large-scale shift in individual evacuation behavior strategies within a group. At the onset of evacuation, the majority of the crowd follows an orderly and organized evacuation process, which occurs before the emergence of group stress. When the overall system benefit falls below the stress threshold, evacuees choose to crowd due to negative emotions and their pre-existing behavior strategies, leading the entire system into a “stress state”. Hence, effective strategies must simultaneously consider both physical methods and stress levels, lowering the threshold for orderly evacuation. For example, measures such as circular broadcasting and sending mobile messages can be employed to promptly inform evacuees about the on-site situation, and staff cab be deployed for guidance and comfort to improve people's sense of security. Analyzing evacuation patterns reveals factors influencing efficiency and individual behaviors, contributing insights to evacuation protocols and applications.

Development of High-Precision Urban Flood-Monitoring Technology for Sustainable Smart Cities.

Owing to rapid climate change, large-scale floods have occurred yearly in cities worldwide, causing serious damage. We propose a real-time urban flood-monitoring technology as an urban disaster prevention technology for sustainable and secure smart cities. Our method takes advantage of the characteristic that water flow is regularly detected at a certain distance with a constant Doppler velocity within the radar observation area. Therefore, a pure flow energy detection algorithm in this technology can accurately and immediately detect water flow due to flooding by effectively removing dynamic obstacles such as cars, people, and animals that cause changes in observation distance, and static obstacles that do not cause Doppler velocities. Specifically, in this method, the pure flow energy is detected by generating a two-dimensional range-Doppler relation map using 1 s periodic radar observation data and performing statistical analysis on the energy detected on the successive maps. Experiments to verify the proposed technology are conducted indoors and in real river basins. As a result of conducting experiments in a narrow indoor space that could be considered an urban underpass or underground facility, it was found that this method can detect flooding situations with centimeter-level accuracy by measuring water level and flow velocity in real time from the time of flood occurrence. And the experimental results in various river environments showed that our technology could accurately detect changes in distance and flow speed from the river surface. We also confirmed that this method could effectively eliminate moving obstacles within the observation range and detect only pure flow energy. Finally, we expect that our method will be able to build a high-density urban flood-monitoring network and a high-precision digital flood twin.

Evaluation of Flooding Disaster Risks for Subway Stations Based on the PSR Cloud Model

This study aims to scientifically evaluate the risk of rainstorm waterlogging disasters in urban subway stations, improve the management of disaster prevention and control, and mitigate the impact of such disasters. To achieve this, a risk assessment analysis was conducted using the Pressure-State-Response (PSR) cloud model. The analysis involved examining the components of the subway station rainstorm waterlogging disaster system, including the disaster-prone environment, disaster-affected body, and disaster-causing factors. Based on the PSR framework, a risk assessment index system for rainstorm waterlogging disasters in subway stations was developed. The entropy weight method and cloud model algorithm were then combined to establish a risk assessment method. By utilizing a cloud generator, the digital characteristics of the risk cloud were calculated, and a risk cloud map was generated to determine the level of risk. Finally, an empirical analysis was carried out at Jin’anqiao Station of the Beijing Subway, providing valuable insights for the evaluation of rainstorm waterlogging disasters in subway stations.

Mechanical characterization of subway tunnel construction in urban shallow distributed karst stratums

To address the challenges posed by rapid urban and population growth, China has undertaken extensive urban subway construction. In order to explore the mechanical characteristics of subway tunnel construction in urban shallow karst environment, based on the first phase project of Guiyang rail transit line 3, the concept of “distributed Karst” is proposed according to the occurrence characteristics of karst in urban environment. The dry ice and model soil were used to characterize the karst strata, and the similar model test study on the influence of different volume karst rates on subway tunnel construction was carried out. The influence of tunnel excavation on surrounding rock disturbance, internal force of arch structure and ground settlement under distributed karst stratum condition is studied comprehensively. The following key findings emerged:(1) Karst presence causes an abrupt change in the release curve of surrounding rock earth pressure. Higher degrees of karst development result in smaller changes in earth pressure on the arch top and shoulder after tunnel excavation, with final earth pressure changes of 91.1 kPa, 83.5 kPa, and 74.8 kPa for volumetric karst rates of 5%, 10%, and 20%, respectively. (2) Distributed karst in the tunnel arch has a limited impact on the lateral excavation displacement of the arch girdle but significantly affects the vertical settlement of the tunnel vault. Increasing volumetric karst rates by twofold (from 5% to 10% and 20%) reduces arch settlement by 48.9% and 55.6%, respectively. (3) At volumetric karst rates of 5%, 10%, and 20%, the axial force values at the tunnel top are 58.2 kN, 52.8 kN, and 50.3 kN, while the corresponding bending moment values are 49.6 kN-m, 37.1 kN-m, and 26.0 kN-m, respectively, indicating a more significant difference in bending moment values than axial force values. (4) Karst presence leads to increased surface settlement, with a 48.8% increase in peak ground settlement observed as the volumetric karst rate rises from 5% to 20%.

On-site measurement and environmental impact of vibration caused by construction of double-shield TBM tunnel in urban subway

The vibration generated during the construction of subway tunnels with double-shield tunnel boring machine (TBM) has a significant impact on the environment, which has caused multiple complaints from residents. Taking a double-shield TBM tunnel project as the background, vibration measurements were conducted by installing vibration sensors on-site. By combining theoretical methods—such as normalization, polynomial fitting prediction, and gray correlation analysis—the vibration characteristics, impact range on the environment, and factors affecting the vibration of TBM construction were studied. The key research results included: (1) The amplified zone of X and Y vibration acceleration occurred on the left-hand side of the tunnel from 3.15 to 13.85 m, but rapidly decayed away from the amplification zone. (2) The impact range of TBM vibrations on residential areas at night and during the day was studied according to the official “Urban Regional Environmental Vibration Standard” and it was found to be larger at night than during the day. (3)The main factors affecting the TBM vibration level was studied—including the cutter-head torque, TBM thrust, cutter-head speed, penetration, field penetration index (FPI) and so on. In summary, when the double-shield TBM construction tunnel is adjacent to residential areas, the vibration generated exceeds the national standard limit. In order to reduce the impact of TBM vibration on residential areas, excavation parameters such as cutter head torque, TBM thrust, cutter head speed, and penetration should be appropriately reduced.

Effect of stray current and sulfate attack on cementitious materials in soil

Stray currents in urban subway systems pose a severe risk as they have the potential to corrode both the reinforced concrete structure and cementitious materials within concrete. This study simulated urban rail transit conditions to assess their impact on cement-based materials. Various analytical techniques, including X-ray diffraction (XRD), compressive strength, ion distribution and scanning electron microscopy (SEM/EDS) were employed to examine the degradation of samples. The research findings revealed that electric fields accelerated the migration of sulfate ions in soil conditions. In the presence of an electric field, the migration of SO42- ions was approximately 2–4 times higher than in non-electric field conditions. Additionally, the corrosion resistance coefficient of the samples exposed to electric fields was reduced by up to 0.45, whereas the samples without electric field exposure experienced a reduction of up to 0.12. Notably, the full immersion in a soil environment resulted in less degradation than in a sulfate solution. Although the extent of degradation varies across different conditions, the mechanism governing sulfate attack on the samples remained consistent. These findings underscore the elevated severity of sulfate attack in urban rail transit systems, deepening our understanding of durability challenges in underground constructions.

Does subway mileage affect urban housing prices? An economic growth perspective

ABSTRACT Studying the mechanism by which urban subway construction in China increases housing prices can help deepen the understanding of the factors that rises in housing prices and may assist the government to conduct reasonable macro-control of the real estate market. This article takes unbalanced panel data from 31 major cities in China as research samples and studies the mechanism by which urban subway construction increases housing prices by influencing urban economic growth. Our findings are as follows: (1) Subway construction promotes urban economic growth, and urban economic growth, from both the demand and supply sides, increases housing prices by increasing the disposable income of urban residents and the purchase price of residential land. (2) Urban subway construction increases city land purchase prices by affecting investors’ expectations of urban land development through the regulating effects of urban economic growth, which in turn increases housing prices. (3) Effective policy measures aimed at managing the speculative impact of metro construction on housing prices need to be viewed for the expectation management of housing and land speculative demand from both the demand side and the supply side.

A dual-function system integrating kinetic energy harvesting and passenger sensing for urban subway

In order to achieve intelligent operation of subway transportation, this paper proposed a dual-function system integrating human kinetic energy harvesting and passenger sensing for self-powered subway pedestrian flow diversion. The proposed dual-function system mainly includes the energy harvesting module, the data acquisition and processing module, and the information transmission module. The most important module is the energy harvesting subsystem, which is a pacemaker for the dual-function system to work successfully. Therefore, this paper focuses on the structure, dynamics, electricity, and parameter analysis of the energy harvesting module. First, mechanical motion rectifier-based vibration energy harvester (MMR-based VEH) is designed to scavenging the stepping energy of passengers. Secondly, the parameter analysis of the proposed MMR-based VEH is carried out. Finally, the prototype of the dual-function system is fabricated to test the energy output and passenger sensing performance. The results showed that the dual-function system can output a voltage of up to 18.5V and a power of approximately 1.8W. Simultaneously, the proposed dual-function system can accurately sense the human step and calculate the number of passenger.

The characteristics of particulate matter in different subway station environmental control systems

Particulate matter (PM2.5, PM10) in urban subway stations can significantly impact passengers' health. The particle concentration in subway stations is influenced by many factors. However, few existing studies have explored the impact of environmental control systems in-depth, especially under different outdoor pollution conditions. To address this research gap, this study focused on measuring and comparing the characteristics of PM2.5 and PM10 at subway stations with three control systems (open, closed, and screen door) under varying pollution conditions in Beijing. Particle concentrations from platforms, carriages, and outdoors were monitored and analyzed using statistical methods. The results showed that the particle concentration in the closed system was generally 20–40 μg/m3 higher than that in the screen system at the platform, which might be attributed to the piston wind, as the air from the tunnel with a lot of dirt. The pollution in the carriage was more severe for the open system than that of the screen system. The PM2.5/PM10 ratio in the carriage was 91%, 90%, and 83.84% for the closed, open, and screen systems, respectively. This indicates that the screen door could reduce the particle concentration in the platform to 10%–50%. The particle concentration varied among subway stations with different environmental control systems, suggesting that the prevention and control strategies for particulate matter pollution should be different for stations with different systems.

Monitoring and Comparative Analysis of Hohhot Subway Subsidence Using StaMPS-PS Based on Two DEMS

The subway alleviates the traffic pressure in the city but also brings the potential risk of land subsidence. The land subsidence caused by the subway is a global problem that seriously affects the safety of subway operations and surrounding buildings. Therefore, it is very important to carry out long-term deformation monitoring on the subway system. StaMPS-PS is a time-series Interferometric Synthetic Aperture Radar (InSAR) technique that serves as an effective means for monitoring urban ground subsidence. However, the accuracy of external (Digital Elevation Models) DEM will affect the accuracy of StaMPS-PS monitoring, and previous studies have mostly used SRTM-1 arc DEM (30 m) as the external DEM. In this study, to obtain a more precise measurement of surface deformation caused by the excavation of the Hohhot subway, a total of 85 scenes of Sentinel-1A data from July 2015 to October 2021, as well as two different resolution digital elevation models (DEMs) (ALOS PALSAR DEM and SRTM-1 arc DEM), were used to calculate and analyze the subsidence along the subway line in Hohhot city. The StaMPS-PS monitoring results showed the ALOS PALSAR DEM, as an external DEM, had higher accuracy, and there was regional subsidence in both the construction processes of Line 1 and Line 2 of the Hohhot subway, with a maximum subsidence rate of −21.1 mm/year. The dynamic changes in subway subsidence were fitted using the Peck formula and the long short-term memory (LSTM) model. The Peck formula results showed the width and maximum subsidence of the settlement troughs gradually expanded during the construction of the subway. The predicted values of the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) of the LSTM model were less than 4 mm and 10%, respectively, consistent with the measured results. Furthermore, we discussed the factors that affect settlement along the subway line and the impact of two external DEMs on StaMPS-PS. The study results provide a scientific method for DEM selection and subsidence analysis calculations in the StaMPS-PS monitoring of urban subway subsidence.

Goal-Oriented Modeling of an Urban Subway Control System Using KAOS

The extent to which a safety-critical system, such as an urban subway control system, accomplishes its goals is a fundamental metric of its success. Identifying and assessing these goals should thus be one of the primary tasks in safety-critical system development. The breakdown of these systems may result in the loss of human lives and assets. The failure of these systems is caused by insufficient, incomplete, ambiguous, or conflicting requirements. Non-functional requirements are also separated from requirement specifications. Goal-oriented requirements engineering methodologies, such as KAOS, are used to tackle these challenges by providing adequate, complete, unambiguous, and consistent requirements in terms of goals. As a result, the KAOS approach is utilized in this article to construct a goal-oriented model of an urban subway control system. Variability and obstacle concerns are also addressed in this study.

Optimal Control Algorithm for Subway Train Operation by Proximal Policy Optimization

With the increasing scale of the urban subway, the total energy consumption of the subway has increased dramatically and poses a great challenge to the comfort of passengers and the punctuality of train operation. In order to ensure on-time train operation and passenger comfort, and at the same time reduce the energy consumption of subway operation, this paper proposes a Proximal Policy Optimization (PPO)-based optimization algorithm for the optimal control of subway train operation. Firstly, a reinforcement learning architecture for optimal control of subway train operation is constructed with the position and speed of train operation as the reinforcement learning state, energy consumption and comfort as the optimization objectives, and train operation time as the constraint. The proposed reinforcement learning model is trained by the PPO algorithm, and the reward scaling is added to the training process to accelerate the training speed and improve the efficiency of the algorithm. The experimental results show that the proposed PPO with reward scaling algorithm can effectively reduce train energy consumption and improve passenger comfort while ensuring on-time train operation.

Prediction of GHG emissions from Chengdu Metro in the construction stage based on WOA-DELM

With the mass construction of urban subways, the global greenhouse gas (GHG) emissions have been on the rise. This paper provides statistical evidence to support the infrastructure of subway emissions reduction through a study of GHG emissions during the construction stage of 6 stations and 7 sections of Chengdu Metro Line 18. Using the emission coefficient method, the GHG emissions from building material production, transportation and site construction in subway stations and shield sections were calculated, and a subway GHG emissions prediction model dependent on deep extreme learning machine (DELM) with whale optimization algorithm (WOA) was established(i.e., WOA-DELM). Compared with some optimized DELMs, namely wind driven optimizer (WDO) -DELM, grey wolf optimizer (GWO) -DELM, particle swarm optimizer (PSO) -DELM, artificial bee colony (ABC) -DELM, multi verse optimizer (MVO) -DELM, and atom search optimizer (ASO) -DELM, and some non-optimized algorithm models, namely back propagation neural network (BPNN), kernel extreme learning machine (KELM) and DELM, the correlation consistency of WOA-DELM algorithm prediction results (0.757) was found to be slightly higher. Through sensitivity analysis of the main input variables of subway GHG emissions with the WOA-DELM algorithm model, it was determined that the key influencing factors of station GHG emissions prediction were the station length and the depth of track surface, with relative change rates of corresponding variables of GHG emissions at 30.1% and 23.1% respectively. Finally, a rough prediction formula of GHG emissions from Chengdu Metro stations and shield sections were fitted based on the key influencing factors of GHG emissions. This study provides a practical and effective reference for reducing GHG emissions in subway construction and operation.