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Keywords = existing subway station

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22 pages, 7152 KiB  
Article
Comprehensive Substantiation of the Impact of Pre-Support Technology on a 50-Year-Old Subway Station During the Construction of Undercrossing Tunnel Lines
by Bin Zhang, Shaohui He, Jianfei Ma, Jiaxin He, Yiming Li and Jinlei Zheng
Infrastructures 2025, 10(7), 183; https://doi.org/10.3390/infrastructures10070183 - 11 Jul 2025
Viewed by 196
Abstract
Due to the long operation period of Beijing Metro Line 2 and the complex surrounding building environment, this paper comprehensively studied the mechanical properties of new tunnels using close-fitting undercrossing based on pre-support technology. To control structural deformation caused by the expansion project, [...] Read more.
Due to the long operation period of Beijing Metro Line 2 and the complex surrounding building environment, this paper comprehensively studied the mechanical properties of new tunnels using close-fitting undercrossing based on pre-support technology. To control structural deformation caused by the expansion project, methods such as laboratory tests, numerical simulation, and field tests were adopted to systematically analyze the tunnel mechanics during the undercrossing of existing metro lines. First, field tests were carried out on the existing Line 2 and Line 3 tunnels during the construction period. It was found that the close-fitting construction based on pre-support technology caused small deformation displacement in the subway tunnels, with little impact on the smoothness of the existing subway rail surface. The fluctuation range was −1 to 1 mm, ensuring the safety of existing subway operations. Then, a refined finite difference model for the close-fitting undercrossing construction process based on pre-support technology was established, and a series of field and laboratory tests were conducted to obtain calculation parameters. The reliability of the numerical model was verified by comparing the monitored deformation of existing structures with the simulated structural forces and deformations. The influence of construction methods on the settlement changes of existing line tracks, structures, and deformation joints was discussed. The research results show that this construction method effectively controls the settlement deformation of existing lines. The settlement deformation of existing lines is controlled within 1~3 cm. The deformation stress of the existing lines is within the concrete strength range of the existing structure, and the tensile stress is less than 3 MPa. The maximum settlement and maximum tensile stress of the station in the pre-support jacking scheme are −5.27 mm and 2.29 MPa. The construction scheme with pre-support can more significantly control structural deformation, reduce stress variations in existing line structures, and minimize damage to concrete structures. Based on the monitoring data and simulation results, some optimization measures were proposed. Full article
(This article belongs to the Special Issue Recent Advances in Railway Engineering)
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23 pages, 7247 KiB  
Article
Pit Collapse Risk Fusion Early-Warning Method Based on Machine Learning and Improved Cloud Dempster–Shafer
by Jiajia Zeng, Bo Wu and Cong Liu
Appl. Sci. 2025, 15(13), 7571; https://doi.org/10.3390/app15137571 - 5 Jul 2025
Viewed by 349
Abstract
Considering the complexity of the metro pit construction environment, the existing risk early-warning methods cannot ensure high-precision early warning. A high-accuracy metro pit collapse risk fusion early-warning method is proposed in present study. The main contributions include (1) presenting a new input to [...] Read more.
Considering the complexity of the metro pit construction environment, the existing risk early-warning methods cannot ensure high-precision early warning. A high-accuracy metro pit collapse risk fusion early-warning method is proposed in present study. The main contributions include (1) presenting a new input to the fusion model by optimizing the machine learning model through a multi-step rolling method, and then using the basic probability assignment values obtained from the cloud model as input to the fusion model and (2) developing an improved methodology to address the paradoxical results of the fusion of traditional Dempster–Shafer evidence theory when there is a high level of conflict in multi-source risk prediction data. The proposed method is successfully applied to the Guangzhou Metro station project. By analyzing the early-warning results of 240 moments in 6 monitoring points, compared with the single information source method and the traditional D-S method, the early-warning accuracy of this method is increased by 15.8% and 10.8% respectively, the false alarm rate is reduced by 6.3% and 5.5%, respectively, and the missed alarm rate is reduced by 9.5% and 5.3%, respectively. The high-accuracy fusion early-warning method proposed in this paper has good universality and effectiveness in the early warning of subway foundation pit collapse risk. Full article
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29 pages, 20382 KiB  
Article
Research on the Vibration Propagation Characteristics of Non-Uniform Speed Trains Entering and Leaving Stations Based on Field Measurements
by Ying Shi, Na Cai and Yekai Chen
Buildings 2025, 15(7), 1091; https://doi.org/10.3390/buildings15071091 - 27 Mar 2025
Viewed by 408
Abstract
Urban rail transit systems, while alleviating traffic congestion, generate environmental vibrations that impact adjacent structures and residents, particularly during train acceleration and deceleration near stations. Existing research predominantly focuses on constant-speed operations, leaving a gap in understanding vibration propagation during variable-speed phases. This [...] Read more.
Urban rail transit systems, while alleviating traffic congestion, generate environmental vibrations that impact adjacent structures and residents, particularly during train acceleration and deceleration near stations. Existing research predominantly focuses on constant-speed operations, leaving a gap in understanding vibration propagation during variable-speed phases. This study investigates vibration characteristics and propagation behaviors using field measurements from a subway station in Foshan, China. Wireless vibration sensors were deployed across nine measuring points at varying distances (15–35 m) from the subway station’s external wall, capturing time-domain and frequency-domain data during train operations. The analysis incorporated China’s JGJ/T 170-2009 standards, evaluating vibration acceleration levels (VAL) and 1/3 octave band spectra. Key findings revealed background vibrations (0–10 Hz) exhibited negligible interference, whereas vehicle-induced vibrations (40–60 Hz) demonstrated directional disparities: urban-bound trains produced higher accelerations (0.004–0.008 m/s2 vertically) than suburban-bound ones (0.001–0.005 m/s2) due to track damping measures and propagation distance. Vibration attenuation with distance was found to be non-linear, influenced by soil hardening and train speed. Vertical vibrations near the station (15 m) approached the 70 dB regulatory limit, emphasizing proximity risks. Doppler effects were observed during train acceleration/deceleration, though data limitations precluded precise quantification of speed impacts. This work supplements knowledge on non-uniform train-induced vibrations, offering insights for urban planning and mitigation strategies. Full article
(This article belongs to the Special Issue Vibration Prediction and Noise Assessment of Building Structures)
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23 pages, 6735 KiB  
Article
Passenger Flow Simulation of Airport Terminal Subway Station Based on System Dynamics
by Wei Chen and Yi Ai
Systems 2025, 13(2), 133; https://doi.org/10.3390/systems13020133 - 18 Feb 2025
Viewed by 1291
Abstract
Grasping the effective carrying capacity of airport hub subway stations in real-time serves as the foundation for enhancing the safety assurance capability of the hub. Starting from the perspectives of multiple subsystems, including people, stations, and trains, and combining passenger flow, system structure, [...] Read more.
Grasping the effective carrying capacity of airport hub subway stations in real-time serves as the foundation for enhancing the safety assurance capability of the hub. Starting from the perspectives of multiple subsystems, including people, stations, and trains, and combining passenger flow, system structure, and multiple attributes of trains, a system dynamics (SD) model for passenger travel in airport hub subway stations is established. The model is simulated using Vensim PLE 5.9d to analyze the effective carrying capacity of the transfer system under the existing configuration and layout of transfer facilities and equipment in the hub. The model features a modular architecture and interface, enabling quick and easy model establishment, and adapts to various configurations and operational characteristics of airport hub subway stations in a user-friendly manner. Multiple sensitivity simulation analysis experiments are designed to analyze changes in passenger flow density from multiple perspectives. This method can calculate the effective carrying capacity of airport hub subway stations, providing a scientific basis for planning, construction, and operational management. The effectiveness of the model is verified by analyzing the Pudong International Airport terminal subway station. Full article
(This article belongs to the Section Systems Theory and Methodology)
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24 pages, 19530 KiB  
Article
How Does the Urban Built Environment Affect the Accessibility of Public Electric-Vehicle Charging Stations? A Perspective on Spatial Heterogeneity and a Non-Linear Relationship
by Jie Sheng, Zhenhai Xiang, Pengfei Ban and Chuang Bao
Sustainability 2025, 17(1), 86; https://doi.org/10.3390/su17010086 - 26 Dec 2024
Cited by 1 | Viewed by 1721
Abstract
The deployment of electric vehicle charging stations (EVCSs) is crucial for the large-scale adoption of electric vehicles and the sustainable energy development of global cities. However, existing research on the spatial distribution of EVCSs has provided limited analysis of spatial equity from the [...] Read more.
The deployment of electric vehicle charging stations (EVCSs) is crucial for the large-scale adoption of electric vehicles and the sustainable energy development of global cities. However, existing research on the spatial distribution of EVCSs has provided limited analysis of spatial equity from the perspective of supply–demand relationships. Furthermore, studies examining the influence of the built environment on EVCS accessibility are scarce, and often rely on single methods and perspectives. To explore the spatial characteristics of EVCS accessibility and its influencing factors, using multi-source urban spatial data, this study initially employs the Gaussian two-step floating catchment area (G2SFCA) method to measure and analyze the spatial distribution characteristics of EVCS accessibility in Guangzhou, China, with consideration of supply–demand relationships. Subsequently, it integrates the MGWR and random forest (RF) models to comprehensively investigate the impact mechanism of the built environment on EVCS accessibility from the perspectives of spatial heterogeneity and non-linear relationship. The results show that the EVCS accessibility exhibits a “ higher in the west and lower in the east, with extreme core concentration” distribution pattern, and has significant spatial autocorrelation. The built-environment variables exhibit different scale effects and spatial non-stationarity, with widespread non-linear effects. Among them, the auto service, distance to regional center, and distance to subway station play important roles in influencing EVCS accessibility. These findings offer important guidance for the efficient and equitable layout of EVCSs in high-density cities. Full article
(This article belongs to the Topic Sustainable Built Environment, 2nd Volume)
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29 pages, 7890 KiB  
Article
Study of the Optimal Control of the Central Air Conditioning Cooling Water System for a Deep Subway Station in Chongqing
by Xingyu Shu, Yu Dong, Jun Liu and Xinhua Xu
Buildings 2025, 15(1), 8; https://doi.org/10.3390/buildings15010008 - 24 Dec 2024
Viewed by 901
Abstract
Cooling water, a crucial component of the central air conditioning setup, exerts a relatively minor direct impact on the thermal comfort of building indoor environments while it has a great effect on the system’s energy efficiency. Numerous studies exist on the cooling water [...] Read more.
Cooling water, a crucial component of the central air conditioning setup, exerts a relatively minor direct impact on the thermal comfort of building indoor environments while it has a great effect on the system’s energy efficiency. Numerous studies exist on the cooling water system, particularly focusing on the process by which the cooling tower system operates, but the linkage between the chiller and the cooling tower is typically overlooked. When the connection is long and the passage environment for the pipeline is not conventional, it cannot be neglected for the optimal control for system efficiency improvement and energy consumption reductions. Throughout this research, a control strategy of the cooling water system for deep subway stations with long pipelines is presented. This cooling system was connected with outdoor cooling towers through a corridor about one hundred meters long. In this process, the cooling water temperature is influenced by the corridor’s thermal environment. For this study, an online control strategy optimizes the cooling water temperature, and a simulation platform of the air conditioning cooling water system of the deep subway station was also developed to evaluate the energy-saving potential of the control strategy of this cooling water system. Atop this platform, a simplified heat transfer model of the pipe corridor was created to determine the cooling capacity provided by the cooling water pipe in the corridor. The outcomes suggest that, as opposed to the conventional control mode, the energy-saving ratio of the optimal control strategy during a typical day may reach 4.1%, and the cooling source system’s Coefficient of Performance (COP) might see an increase of about 4.2%. The energy consumption of the water system throughout the whole cooling season may decrease by 9778 kWh, and the energy-saving rate is 4.1%. The results also demonstrate that the cooling water pipes release heat to the air in the corridor most of the time, and the released heat is larger than the absorbed heat. The maximum heat dissipation to the air in the corridor from the cooling water supply and return pipe can be up to 24.3 kW. The cooling effect of the corridor of subway stations with large depths below the ground surface cannot be ignored when optimal control is considered for the cooling water system. Full article
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)
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21 pages, 4151 KiB  
Article
Subway Multi-Station Coordinated Dynamic Control Method Considering Transfer Inbound Passenger Flow
by Linghui Xu, Jia Lu, Shuichao Zhang, Gang Ren and Kangkang He
Sustainability 2024, 16(24), 11292; https://doi.org/10.3390/su162411292 - 23 Dec 2024
Cited by 1 | Viewed by 881
Abstract
The prominent contradiction between passenger demand and capacity in rush hours at subway stations causes inconveniences to travel and even leads to safety risks. Existing research on the cooperative control of passenger flow at stations mostly focuses on a single direction, rarely considering [...] Read more.
The prominent contradiction between passenger demand and capacity in rush hours at subway stations causes inconveniences to travel and even leads to safety risks. Existing research on the cooperative control of passenger flow at stations mostly focuses on a single direction, rarely considering transfer passenger flow control. This study formulated a coordinated dynamic control strategy for multiple stations in both directions as a deterministic mathematical programming model to optimise the crowded passenger flow. The optimisation objectives were set as the warning levels of crowded passenger flow and the detention time of all passengers. The constraints included limitations on station service capacity, train capacity, and the number of people boarding trains. Additionally, considering separate control over the transfer inbound passenger flow at transfer stations, an upward- and downward-direction coordinated dynamic control model was constructed. Numerical experiments based on real-world data from the Nanjing Metro Line 1 were conducted to investigate the effectiveness of the proposed cooperative control scheme and evaluate its performance. Full article
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19 pages, 3440 KiB  
Article
A Hybrid Strategy-Improved SSA-CNN-LSTM Model for Metro Passenger Flow Forecasting
by Jing Liu, Qingling He, Zhikun Yue and Yulong Pei
Mathematics 2024, 12(24), 3929; https://doi.org/10.3390/math12243929 - 13 Dec 2024
Cited by 3 | Viewed by 1388
Abstract
To address the issues of slow convergence and large errors in existing metaheuristic algorithms when optimizing neural network-based subway passenger flow prediction, we propose the following improvements. First, we replace the random initialization method of the population in the SSA with Circle mapping [...] Read more.
To address the issues of slow convergence and large errors in existing metaheuristic algorithms when optimizing neural network-based subway passenger flow prediction, we propose the following improvements. First, we replace the random initialization method of the population in the SSA with Circle mapping to enhance its diversity and quality. Second, we introduce a hybrid mechanism combining dimensional small-hole imaging backward learning and Cauchy mutation, which improves the diversity of the individual sparrow selection of optimal positions and helps overcome the algorithm’s tendency to become trapped in local optima and premature convergence. Finally, we enhance the individual sparrow position update process by integrating a cosine strategy with an inertia weight adjustment, which improves the algorithm’s global search ability, effectively balancing global search and local exploitation, and reducing the risk of local optima and insufficient convergence precision. Based on the analysis of the correlation between different types of subway station passenger flows and weather factors, the ISSA is used to optimize the hyperparameters of the CNN-LSTM model to construct a subway passenger flow prediction model based on ISSA-CNN-LSTM. Simulation experiments were conducted using card swipe data from Harbin Metro Line 1. The results show that the ISSA provides a more accurate optimization with the average values and standard deviations of the 12 benchmark test function simulations being closer to the optimal values. The ISSA-CNN-LSTM model outperforms the SSA-CNN-LSTM, PSO-ELMAN, GA-BP, CNN-LSTM, and LSTM models in terms of error evaluation metrics such as MAE, RMSE, and MAPE, with improvements ranging from 189.8% to 374.6%, 190.9% to 389.5%, and 3.3% to 6.7%, respectively. Moreover, the ISSA-CNN-LSTM model exhibits the smallest variation in prediction errors across different types of subway stations. The ISSA demonstrates superior parameter optimization accuracy and convergence speed compared to the SSA. The ISSA-CNN-LSTM model is suitable for the precise prediction of passenger flow at different types of subway stations, providing theoretical and data support for subway station passenger density and trend forecasting, passenger organization and management, risk emergency response, and the improvement of service quality and operational safety. Full article
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27 pages, 7920 KiB  
Article
Risk Evaluation of Urban Subway Site Selection: Balance, Attractiveness, and Financing Models
by Yun Liu, Zhiqiang Xie, Ping Wen, Chunhou Ji, Ling Zhu, Qisheng Wang, Zheng Zhang, Zhuoqian Xiao, Bojin Ning, Quan Zhu and Yan Yang
Land 2024, 13(12), 2015; https://doi.org/10.3390/land13122015 - 26 Nov 2024
Cited by 1 | Viewed by 1050
Abstract
As a crucial form of public transportation, subways are becoming essential infrastructure that cities in China increasingly prioritize for development. However, there is a lack of effective risk assessment methods for subway station and line siting. To address this gap, this paper uses [...] Read more.
As a crucial form of public transportation, subways are becoming essential infrastructure that cities in China increasingly prioritize for development. However, there is a lack of effective risk assessment methods for subway station and line siting. To address this gap, this paper uses the subway system in Kunming, China, as a case study, establishing a subway site risk evaluation framework (SIRE-BAF) that integrates three dimensions: balance (B), attractiveness (A), and financing mode (F). An extended NP-RV model is proposed to assess the balance (or imbalance) characteristics of subway stations based on sub-dimensions of traffic supply, land use, and urban vitality. Findings indicate that (1) the balance (or imbalance) of subway stations is distinctly distributed along the line and simultaneously exhibits a spatial pattern radiating from the urban core to the periphery. (2) Stations with high urban vitality and minimal imbalance are highly attractive and tend to face “undersupply” during operation, whereas stations with lower attractiveness are more prone to “oversupply”. A higher level of BAF coupling coordination suggests a more suitable subway site selection and lower investment risk, while lower coupling coordination indicates increased risk. (3) Excessive reliance on the “subway + real estate” model, without considering urban vitality, may lead to high vacancy rates and reduced efficiency in subway service. This paper further assesses the site selection risks for the proposed Kunming subway. This study contributes to risk assessments of existing subway operations and maintenance in Chinese cities, enhances planning rationality and site selection for proposed subways, and holds potential applicability for other cities. Full article
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21 pages, 7600 KiB  
Article
A Multi-Objective Prediction XGBoost Model for Predicting Ground Settlement, Station Settlement, and Pit Deformation Induced by Ultra-Deep Foundation Construction
by Guangkai Huang, Zhijian Liu, Yajian Wang and Yuyou Yang
Buildings 2024, 14(9), 2996; https://doi.org/10.3390/buildings14092996 - 21 Sep 2024
Cited by 8 | Viewed by 1890
Abstract
Building a deep foundation pit in urban centers frequently confronts issues such as closeness to structures, high excavation depths, and extended exposure durations, making monitoring and prediction of the settlement and deformation of neighboring buildings critical. Machine learning and deep learning models are [...] Read more.
Building a deep foundation pit in urban centers frequently confronts issues such as closeness to structures, high excavation depths, and extended exposure durations, making monitoring and prediction of the settlement and deformation of neighboring buildings critical. Machine learning and deep learning models are more popular than physical models because they can handle dynamic process data. However, these models frequently fail to establish an appropriate balance between accuracy and generalization capacity when dealing with multi-objective prediction. This work proposes a multi-objective prediction model based on the XGBoost algorithm and introduces the Random Forest Bayesian Optimization method for hyperparameter self-optimization and self-adaptation in the prediction process. This model was trained with monitoring data from a deep foundation pit at Luomashi Station of Chengdu Metro Line 18, which are characterized by a sand and pebble stratum, cut-and-cover construction, and a depth of 45.5 m. Input data of the model included excavation rate, excavation depth, construction time, shutdown time, and dewatering; output data included settlement, ground settlement, and pit deformation at an operating metro station only 5.7 m adjacent to the ongoing pits. The training effectiveness of the model was validated through its high R2 scores in both training and test sets, and its generalization ability and transferability were evaluated through the R2 calculated by deploying it on adjacent monitoring data (new data). The multi-objective prediction model proposed in this paper will be promising for monitoring the data processing and prediction of settlement of surrounding buildings for ultra-deep foundation pit engineering. Full article
(This article belongs to the Special Issue Research on Intelligent Geotechnical Engineering)
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22 pages, 543 KiB  
Article
A Novel Evaluation Model of Subway Station Adaptability Based on Combination Weighting and an Improved Extension Cloud Model
by Weiying Wu, Cheng Song, Xiaolin Wang, Hengheng Su and Bo Huang
Buildings 2024, 14(9), 2867; https://doi.org/10.3390/buildings14092867 - 11 Sep 2024
Viewed by 1274
Abstract
The rational selection of subway station locations is an interdisciplinary problem encompassing architecture, transportation, and other fields. Few evaluation index systems and quantitative evaluation methods exist for choosing subway station locations; thus, this paper establishes a novel evaluation framework. Overall, 21 indicators covering [...] Read more.
The rational selection of subway station locations is an interdisciplinary problem encompassing architecture, transportation, and other fields. Few evaluation index systems and quantitative evaluation methods exist for choosing subway station locations; thus, this paper establishes a novel evaluation framework. Overall, 21 indicators covering the construction and operation phases are selected by a literature review, providing a basis for planning decision makers. The Projection Pursuit Method (PPM) and the Bald Eagle Search (BES) algorithm are employed to assign objective weights. The Continuous Ordered Weighted Averaging (COWA) operator is utilized to obtain subjective weights. A combination weighting method is used based on game theory to improve the accuracy of weight calculation. Game theory and extension cloud theory are applied to develop an improved extension cloud model and evaluate the suitability based on optimal cloud entropy. We conduct a case study of 15 stations on the Chengdu Metro Line 11, China. The results reveal that the coordination of the development plans, the alignment with the land use plan, and regional population density are the most crucial tertiary indicators that should be considered in selecting subway station locations. These findings agree with the actual conditions, demonstrating the scientific validity of the proposed evaluation method, which outperforms classical evaluation methods. The proposed method is efficient and feasible for selecting subway station locations. Full article
(This article belongs to the Special Issue Advances in Life Cycle Management of Buildings)
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16 pages, 8344 KiB  
Article
Deformation Effects of Deep Foundation Pit Excavation on Retaining Structures and Adjacent Subway Stations
by Zhijian Jiang, Shu Zhu, Xiangcheng Que and Xinliang Ge
Buildings 2024, 14(8), 2521; https://doi.org/10.3390/buildings14082521 - 15 Aug 2024
Cited by 11 | Viewed by 2035
Abstract
In complex underground conditions, the excavation of deep foundation pits has a significant impact on the deformation of retaining structures and nearby subway stations. To investigate the influence of deep excavation on the deformation of adjacent structures, a three-dimensional numerical model of the [...] Read more.
In complex underground conditions, the excavation of deep foundation pits has a significant impact on the deformation of retaining structures and nearby subway stations. To investigate the influence of deep excavation on the deformation of adjacent structures, a three-dimensional numerical model of the foundation pit, existing subway station, and tunnel structure was established using FLAC 3D software, based on the Shenzhen Bay Super Headquarters C Tower foundation pit project. The study analyzed the deformation characteristics of retaining structures, adjacent subway stations, and tunnels during different stages of deep excavation, and the accuracy of the numerical simulation results was validated through field monitoring data. The results indicate that during the excavation process of the foundation pit, the lateral horizontal displacement of the retaining structure is generally small, with a typical “concave inward” lateral deformation curve; the horizontal displacement value of the contiguous wall section is less than that of the interlocking pile section. The bending moments of the retaining structure show a distribution pattern with larger values in the middle and smaller values at the top and bottom of the pit, with a relatively uniform distribution of internal support forces. The maximum displacement of the nearby subway station is 8.75 mm, and the maximum displacement of the subway tunnel is 2.29 mm. The research findings can provide references for evaluating the impact of newly built foundation pits near subway stations and contribute to the rational design and safe construction of new projects. Full article
(This article belongs to the Topic Sustainable Building Materials)
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27 pages, 5014 KiB  
Review
A Review of Intelligent Subway Tunnels Based on Digital Twin Technology
by Yuhong Zhao, Yuhang Liu and Enyi Mu
Buildings 2024, 14(8), 2452; https://doi.org/10.3390/buildings14082452 - 8 Aug 2024
Cited by 5 | Viewed by 3603
Abstract
The construction of a new generation of smart cities puts forward higher requirements for the digitization and intelligence of subway tunnel engineering. Digital twin technology has shown great potential in high-fidelity modeling, virtual–real mapping, and decision support based on data analysis, but its [...] Read more.
The construction of a new generation of smart cities puts forward higher requirements for the digitization and intelligence of subway tunnel engineering. Digital twin technology has shown great potential in high-fidelity modeling, virtual–real mapping, and decision support based on data analysis, but its research is still in its infancy. To this end, this paper first discusses in depth the inherent complexity and safety risks of subway tunnel construction and emphasizes the significant advantages of digital twin technology compared with traditional technology. Then, by summarizing the existing concepts, this paper proposes a specific explanation of DT applicable to subway tunnel engineering. In order to deeply analyze the potential of digital twin technology in subway tunnel engineering, this paper first conducts a bibliometric analysis and organizes the relevant research directions in recent years based on a visual map. Then, the application of DT in the field of subway tunnel engineering is discussed, including the modeling method of the subway digital twin, intelligent management of the construction process, safety guarantee, operation and maintenance, and resource optimization of traffic facilities in subway stations. Finally, this paper discusses the prospects and gaps of digital twin technology in theoretical and practical applications, aiming to promote the practical application of this technology in subway tunnel engineering. Through the summary and prospect of the existing research, this paper provides a valuable reference for future research directions and practical applications. Full article
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)
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20 pages, 17116 KiB  
Article
Numerical Simulation Study on the Impact of Excavation on Existing Subway Stations Based on BIM-FEM Framework
by Yi Qiu, Junwei Wang, Chao Zhang, Lingxiao Hua and Zhenglong Zhou
Buildings 2024, 14(5), 1444; https://doi.org/10.3390/buildings14051444 - 16 May 2024
Cited by 5 | Viewed by 1501
Abstract
Building information modeling (BIM) and finite element method (FEM) models have a wide range of applications in underground engineering design, construction, and operation and maintenance. This study employs a BIM-FEM framework to numerically simulate the impact of excavation on existing subway stations, using [...] Read more.
Building information modeling (BIM) and finite element method (FEM) models have a wide range of applications in underground engineering design, construction, and operation and maintenance. This study employs a BIM-FEM framework to numerically simulate the impact of excavation on existing subway stations, using the Yanjiang New City Station TOD project as a case study. This framework simplifies the smooth integration of BIM and FEM models, automating functions such as assigning material properties, conducting construction simulations, and generating high-quality meshes. Simulation results reveal significant horizontal and vertical displacements in diaphragm walls, support structures, and subway station structures, with the greatest impacts occurring closest to the excavation site. The BIM-FEM framework is validated as an effective tool for designing foundation pit support structures, enhancing numerical modeling accuracy and efficiency in underground engineering. The findings contribute to a better understanding of the dynamic interactions between excavation and underground structures, informing the development of construction strategies and protective measures to ensure structural safety. Full article
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)
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12 pages, 3103 KiB  
Article
Intelligent Early Warning and Decision Platform for Long-Term Ground Subsidence in High-Density Areas for Sustainable Urban Development
by Baoping Zou, Kejian Xia, Yansheng Deng, Jundong Mu, Siqi Cheng and Chun Zhu
Sustainability 2024, 16(7), 2679; https://doi.org/10.3390/su16072679 - 25 Mar 2024
Viewed by 1169
Abstract
Long-term ground subsidence (LTGS) is a relatively slow process. However, the accumulation of long-term subsidence has an adverse impact on the normal operation and safety of a subway, hindering sustainable urban development. A wide gap exists between early warning theory and its application [...] Read more.
Long-term ground subsidence (LTGS) is a relatively slow process. However, the accumulation of long-term subsidence has an adverse impact on the normal operation and safety of a subway, hindering sustainable urban development. A wide gap exists between early warning theory and its application in the control of LTGS during subway operation due to time span limitation. Providing decision support for LTGS in high-density urban areas during subway operation is difficult, and a collaborative decision system for real-time early warning and intelligent control is currently lacking. This study establishes the functional components of an intelligent early warning and decision platform, proposes a software system module, constructs an overall software framework structure, and develops a mobile intelligent early warning and decision platform. Moreover, this study introduces an early warning method for LTGS in high-density urban areas during subway operation. This method integrates an intelligent early warning decision-making platform, namely Differential Synthetic Aperture Radar Interferometry (DInSAR), land subsidence monitoring, operation tunnel subsidence monitoring, and other multisource data coupling. The method is applied to sections of the Hangzhou Metro Line 4 Phase I Project (Chengxing Road Station (CRS)–Civic Center Station (CCS)–Jiangjin Road Station (JRS) and Xinfeng Station (XS)–East Railway Station (ERS)–Pengbu Station (PS)). This work can serve as a reference for ensuring urban safety and promoting sustainable development. Full article
(This article belongs to the Special Issue Remote Sensing in Geologic Hazards and Risk Assessment)
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