Beijing Metro Line Research Articles

Shield machine pose prediction based on CNN-GRU-Attention

This paper presents a shield machine pose prediction method based on Convolutional Neural Network (CNN) - Gated Recurrent Unit (GRU) with Attention mechanism (Attention). Firstly, the Pearson correlation coefficient is employed to select input parameters highly related to the position and posture of the shield machine. Then, a convolutional neural network is introduced to extract the long-term short-term feature dependency features in the operation data of the shield machine, optimizing the model’s input. The attention mechanism is integrated into the gated loop unit to make the model more targeted in using key information in the input sequence and improve the accuracy of the shield machine pose prediction model. The effectiveness of this method is verified by the example of Beijing Metro Line 10. Compared with GRU-Attention and LSTM-Attention models, the mean value of determination coefficient R2 increased from 0.872 and 0.886 to 0.959, and the mean value of root mean square error RMSE decreased from 2.78 and 2.52 to 2.14. This method can provide effective prediction for the attitude and position of shield machines in actual tunnel engineering.

Experimental study on the performance of shield tunnel tail grout in ground

Shield tail grouting is an important measure to control tunnelling-induced ground deformation by injecting prepared grouting materials to fill the tail gap. The working performance of grout is usually invisible and hard to obtain in construction. This paper carries out an experimental study to investigate the tail grout behavior in ground. In the current research, a testing device is developed to explore the grout behavior in varying soils. The grout working performance is evaluated not only by the liquid grout properties such as fluidity, consistency, bleeding rate, stone rate and compressed deformation but also solid grout properties such as unconfined compressive strength and permeability. Three typical grouts are chosen and their behaviors in the various soils are observed. To take an insight on the behaviors, scanning electron microscopy and mercury intrusion porosimetry analysis are employed. The microstructure of solid grout is a sign of its working performance. The observation shows that the solid grout micro-structure is influenced by grout proportions, pressure, and ground permeabilities. The experimental results are applied in the case of Beijing Metro Line 12 for validation and as a result, the ground movement is inhibited due to high performance of tail grout.

Intelligent optimization prediction of screw conveyor speed for earth pressure balance shield machine based on complete ensemble empirical mode decomposition of adaptive noise and deep learning

The excavation stratum of the earth pressure balance (EPB) shield machine is complex and changeable. For ensuring the excavated interface stabilization, the rotational speed of screw conveyor must be precisely controlled to maintain the balance of earth pressure in sealed cabin and to avoid accidents such as ground collapse or upliftment. A data-driven intelligent optimal model is presented by the paper, which organically integrates the complete ensemble empirical mode decomposition of adaptive noise (CEEMDAN), sparrow search algorithm (SSA) and long short-term memory (LSTM) network to achieve accurate prediction of screw conveyor rotation speed. Firstly, Pearson correlation analysis method is used to analyze the historical data of shield tunneling, and the tunneling parameters strongly related to the change of screw conveyor rotation speed are obtained as model input. Secondly, the CEEMDAN is used to decompose the obtained parameter data set into several modal components, and then the denoised data is reorganized to capture the changing characteristics of the original data and reduce the complexity of the data. Then, the parameters such as the learning rate of the LSTM network are optimized by using the strong global search ability of SSA to enhance the prediction precision further in the model. Finally, based on decomposed and reorganized data, SSA-LSTM is used to establish a rotation speed intelligent prediction model realize precise controlling of screw conveyor rotation speed. The simulation experiment is carried out by using the construction data of a section of Beijing Metro Line 10, and the results of three evaluation indexes of the model are given: Mean Absolute Error (MAE) is 0.02878, Mean Absolute Percentage Error (MAPE) is 0.00882 and R2 is 0.99909, which shows that the model has good prediction performance. The control effect of the method on the earth pressure balance of the sealed cabin is tested, and the maximum error value is 0.25%, which verifies the engineering applicability of the method.

Multi-step intelligent prediction of shield machine position attitude on the basis of BWO-CNN-LSTM-GRU

Abstract Realizing automatic control of shield machine tunneling attitude is a challenging problem. Realizing multi-step intelligent prediction for attitude and position is an important prerequisite for solving this problem in the tunneling process with complex and varied geological environments. In this paper, a multi-step intelligent predictive scheme based on beluga whale optimization-convolutional neural network-Long Short-term memory-gated recurrent unit (BWO-CNN-LSTM-GRU) is proposed for shield machine position attitude. First, Pearson correlation analysis is utilized to determine the input feature variables from the construction data and temporalize the input features. Subsequently, CNN-LSTM-GRU predictive models are established for the six positional parameters, separately. Among them, CNN performs feature extraction on the input variables, and LSTM-GRU realizes the predictions for the target positional parameters. In the end, the optimization of the convolutional layer dimension, the number of convolutional layers, iterations, the learning rate, the number of neurons in the LSTM layer and GRU layer of each position predictive model is performed on the basis of BWO, separately, and the best hyperparameters found are built into a BWO-CNN-LSTM-GRU position predictive model, which realizes the multi-step intelligent predictions for the shield machine’s position. The proposed approach is examined by utilizing the Beijing Metro Line 10. The results show that the predictive deviation of the position predictive model is within 3 mm, and the positional trajectory points obtained on the basis of the predicted values and the 3D coordinate system are highly coincident with the actual trajectory points. Therefore, the approach provides a more accurate predictive result for shield attitude and position and can provide a decision-making scheme for further realizing the coordinated autonomous control of shield machine.

Mechanism of rail corrugation formation on metro curves with a type of floating-slab track

ABSTRACT A steel spring floating-slab track (SSFST) capable of mitigating railway-induced vibrations has been widely used in a metro line in Beijing. In sharp curves with radii of less than 500 m, severe corrugation with wavelengths of about 125–200 mm and passing frequencies of 70–80 Hz occurred on low rails. Field measurements and numerical simulations were used to investigate the cause of the corrugation. The results show that the wavelength of corrugation is related to the speed of the vehicle and the corrugation passing frequency is a fixed frequency. The formation of the rail corrugation in the sharp curves does not depend on the torsional and bending resonances of wheelsets and P2 resonance. The wheel–rail vertical fluctuating force at frequencies of 67–75 Hz arises easily under a broadband excitation of the rail irregularity due to the vertical bending of the rail and the floating slab relative to the subgrade. The numerical simulations show that the corrugation with dominant wavelengths of 160–200 mm initiates when the vehicle passes over the irregularity. The simulation results are consistent with the field test results. The corrugation occurs on SSFST as a result of the vertical bending of the entire track, driven by a wavelength-fixing mechanism.

A unified empirical method for predicting both vertical and horizontal ground displacements induced by tunnel excavation

An empirical model for describing the soil movements induced by tunneling is proposed, then the mathematical relationship between horizontal displacement and vertical displacement is obtained. By analyzing 25 sets of data from field engineering and 35 sets of data from model tests, the formula for the maximum settlement Sv, max( z) is optimized to adapt to different ground conditions. The Modified Gaussian function is developed by introducing the existing width coefficient of the settlement trough i( z) and the optimized Sv, max( z) to describe the surface and subsurface vertical displacement. Subsequently, the formula for the horizontal displacement is derived based on the Modified Gaussian function. H( z) representing the position of the oriented point of the soil movement is a variable in the formula for horizontal displacement. Based on measured results, a logarithmic function and a quadratic polynomial function are proposed to describe the variation of H( z) with depth in the clay stratum and sand stratum, respectively. Then, the rationality of the proposed method is validated by 4 sets of in-situ data and 4 sets of test data. Finally, the implementation process of the proposed method is illustrated, and the inversion results of the ground displacement field in Beijing Metro Line 12 are presented.

Assessment of adjacent building vibrations induced by metro with a multigrid fully coupled method

The vibrations generated by metro operations can cause structural damage and discomfort to occupants adjacent to the metro lines. In this study, a multigrid fully coupled method of metro vehicle-track-station-soil-building systems is proposed to predict and assess building vibrations before construction. This approach facilitates the efficient calculation of the fully coupled system, while ensuring precise simulations through the utilization of multigrid techniques for wheel-rail contact, track, station, soil, and building components. Using the newly built opera theatre along Beijing metro line 4 as a case, the study demonstrates that the multigrid fully coupled model can predict the dynamics characteristics of metro-induced vibrations and distribution with high accuracy compared with the field tests. Specifically, it was found that metro operations could result in vibrations exceeding specified limits in the opera theatre, particularly at 10∼40 Hz (the building’s natural frequency) and 60∼80 Hz (the main frequency band of vibration caused by the metro). Finally, the mechanism of excessive vibration and the effectiveness of targeted vibration mitigation measures were analyzed with the proposed method. These findings have promising implications for wider applications in environmental assessments and control strategies for new metro lines or vibration-sensitive buildings.

Research on the deformation laws of buildings adjacent to shield tunnels in clay strata

Earth pressure shields are widely used in tunnel construction due to their low environmental impact and mechanized operations. However, ensuring the stability of the excavation surface during the construction process is crucial. Any instability in the excavation surface can lead to soil destruction, such as body collapse or surface uplift. Additionally, the tunneling process can cause deformation disturbances to nearby buildings. In the case of Beijing Metro Line 17, detailed survey data and construction monitoring data were collected through field surveys and tests. The study combined theoretical analysis and numerical simulations to investigate the impact of shield tunneling in clay layers on neighboring buildings. The focus was on analyzing the physical deformation and the response law of influencing factors, such as stratum parameters and engineering effects on surface settlement, building inclination, and distortion. Furthermore, sensitivity analysis of the deformation impact was conducted, and corresponding measures for deformation control were proposed.

Fast Quasi-Optimal Power Flow of Flexible DC Traction Power Systems

This paper proposes a quasi-optimal power flow (OPF) algorithm for flexible DC traction power systems (TPSs). Near-optimal OPF solutions can be solved with high computational efficiency by quasi-OPF. Unlike conventional OPF algorithms, quasi-OPF does not utilize mathematical optimization algorithms but adopts a new methodology. First, we adopt a new modeling method and successfully reveal the physical meaning of OPF solutions in flexible DC TPSs. Then, by converting the physical meaning of OPF solutions into mathematical expressions, a simple mapping from the power flow solution to the near-optimal OPF solution is obtained, and the quasi-OPF algorithm is designed based on power flow and this mapping. Since calculating power flow is computationally cheap and the mapping is based on simple arithmetic, the quasi-OPF algorithm can solve OPF with much less execution time, achieving subsecond level calculation and a speed-up of 57 times compared to the primal-dual interior point method. The effectiveness is verified by mathematical proofs and a case study with Beijing Metro Line 13. This study provides insight into the physical meaning of OPF solutions and is a powerful tool for flexible DC TPSs to analyze the effects of coordinated control, design real-time coordinated control strategies, and solve operational problems in planning.

Leveraging cost-effectiveness of photovoltaic-battery system in metro station under time-of-use pricing tariff

As the cornerstone of contemporary urban transit infrastructure, the metro rail transit system significantly contributes to both energy consumption and carbon emissions. Recognizing the potential of rooftop photovoltaic (PV) applications in elevated stations to mitigate the carbon footprint of the metro system, harnessing this potential becomes imperative for advancing toward a cleaner future in the metro transit sector. However, the techno-economic feasibility of the rooftop PV application in elevated metro stations has not been fully reported in existing literature. Addressing this research gap, our study delves into the impact of the photovoltaic-battery (PVB) system on energy conservation and economic benefits within the elevated stations of a metro line in Beijing, China, and a multi-objective nonlinear mixed-integer programming (MIP) is formulated under a 3-tier time-of-use tariff scheme for minimizing grid load and maximizing economic benefits. The results demonstrate that the incorporation of both the battery energy storage device and the PV subsystem leads to an 8.3% and 19.2% reduction in annualized costs, respectively. When applied across the entire metro line, the PVB system is anticipated to yield a substantial annualized cost reduction ranging from 26.1% to 47.8%. Moreover, outcomes from the multi-objective MIP optimization reveal that the simultaneous achievement of economic benefits maximization and grid load minimization is infeasible, and the weighted sum method offers a decision-making platform for investors to choose one option or another according to extra criteria.

Two‐objective train operation optimization based on eco‐driving and timetabling

AbstractIn urban railway systems, the timetable guides the section operation of the single train and the arrangement of the train group to meet the dual needs of cost and passengers. This paper proposes a two‐objective train operation optimization based on eco‐driving and timetabling to restore a more realistic scene, including a method level and an objective level. For the method level, the speed curve optimization of the single train and the timetable optimization of the train group are adopted jointly. For the objective level, both the total energy consumption of the train group and the consuming time of passengers are considered. A hybrid solution strategy based on quadratic programming and improved artificial bee colony algorithm is proposed. A hardware‐in‐the‐loop platform is built to carry out validation experiments. Both the cases in general hours and special hours are verified based on the actual data from Beijing Metro Line 15. The results show that both the energy consumption and the passenger consuming time are reduced simultaneously. Correspondingly, the speed curve and the time distribution of the timetable are individually optimized based on the fluctuating passenger flow.

Mechanical response and field measurement analysis of custom-shaped steel sleeves during urban shield tunnel construction

Urban shield tunnel construction is typically affected by limited construction space and the inability to begin from the main line. Conventional lateral initiation solutions result in construction delays and incurs additional construction costs. Hence, based on the Beijing Metro Line 27 project, a novel custom-shaped steel sleeve for lateral initiation is proposed. Numerical simulations are conducted to analyse the stress and deformation characteristics of the steel sleeve during shield initiation. The simulation results, which are validated based on on-site measurements, show that the maximum tensile stress of the shaped steel sleeve structure increases with the shield thrust, and that the average maximum stress occurred at the waist position at the long side of the barrel. However, the stress at the base reduced significantly and a stress concentration occurred at the connection between the sleeve and tunnel portal. The deformation of the sleeve is characterised by a larger long side and a smaller short side owing to the constraint of the tunnel portal. The axial force on the connection bolts below the waist of the sleeve is the highest, whereas the axial force near the tunnel portal is lower. The waist position and the lower section of the sleeve structure are areas where the stress and deformation are weak during the shield initiation of the steel sleeve. Results of engineering test shows that using a shaped steel sleeve for lateral initiation is safe and feasible. However, the waist and bolt connections of the shaped steel sleeve must be scrutinised when used in engineering practice, and standardised construction operations and strengthened monitoring should be implemented.

Coupling analysis method of grouting construction with deformation response of adjacent existing tunnel

In the new tunnel under close distance through the existing tunnel risk source, the grouting scheme developed to compensate for stratum losses is still based on empirical methods, relying on the overburden thickness of existing tunnels. This can potentially lead to an excessively high or low probability of uplift of existing tunnels. Proposing a coupled deformation analysis method between the grouting construction and adjacent existing tunnels is of great theoretical significance for developing grouting schemes. In order to reasonably limit the design parameters of grouting construction, based on the theory of fluid–solid coupling elastic pore-column expansion and the theory of random media, the calculation method of stratum displacement which simultaneously considers the coexistence of grout compaction expansion and permeability diffusion mode is derived, and the accuracy of the calculation method is verified by engineering examples. The accuracy of this calculation method was verified through engineering examples. Combined with the deformation coordination condition, the existing tunnel is regarded as an elastic Euler-Bernoulli continuous beam, and the finite element coupling balance equation of the interaction between the existing tunnel and the surrounding soil is obtained. Based on this, a coupling calculation model of the grouting construction and the deformation response of the adjacent existing tunnel is established. Combined with three times of grouting construction examples in the shield tunneling project of Beijing Metro Line 12 under the existing airport line, the reliability of the coupling calculation model to determine the grouting construction parameters is verified. The calculation parameters in the coupling calculation model have clear physical meanings, which can provide a theoretical basis for the grouting design of similar risk source projects.

Research on the Influence of Weather Factors on Urban Rail Transit Passenger Flow

In recent years, cities have been increasingly confronted with frequent and severe extreme weather events, such as heavy rainfall, high temperatures, and strong winds. These extreme weather conditions not only impact urban transportation operations but also directly affect passengers' travel patterns and behaviors. In this context, gaining a deeper understanding of the mechanisms through which weather factors influence urban subway passenger flow becomes crucial. This study aims to investigate the relationship between passenger flow and weather factors, and provide valuable insights for urban rail transit management to enhance proactive decision-making. To achieve this research objective, we first establish a framework for studying the impact of weather on passenger flow. Based on this framework, an analysis is conducted using passenger flow data and weather data from Beijing Metro Line 4. The findings of this study reveal significant effects of different weather factors on subway passenger flow. Increasing severity of weather conditions and higher wind speeds have a negative influence on passenger flow, leading to a decrease in ridership. Conversely, a significant positive correlation is observed between the highest temperature and subway passenger flow, indicating that as the highest temperature rises, the passenger volume also increases.

Optimization of system resilience in urban rail systems: Train rescheduling considering congestions of stations

In urban rail systems, unexpected events, due to equipment breakdown, extreme weather, etc., frequently cause the delay of trains and overcrowding of platforms, significantly affecting the service quality to passengers. Therefore, improving system resilience to recover to normal conditions more quickly has become a critical problem in the management of urban rail systems. In contrast to most previous studies that focused only on train rescheduling, our paper proposes optimizing the resilience of urban rail systems by considering the influence of delayed trains and overcrowded passenger flows. Specifically, we define a resilience-oriented quantitative evaluation index. Using the evaluation index as the objective function, we construct a mixed-integer nonlinear programming model. In our formulation, we consider a practical case in which the boarding and alighting of passengers at overcrowded stations may further delay trains. To solve the model, we develop a two-phase iterative optimization approach, in which phase 1 focuses on the adjustment of trains to enhance system resilience, and phase 2 evaluates the impact of passengers on the adjusted train schedule. Through the comparison of three different rescheduling methods, we prove the validity of the derived inequalities and our approach balances the computational time and system performance. Case studies are conducted on the Beijing Metro Line 1 to verify the effectiveness of the proposed approach. The results demonstrate that system resilience can be improved by as much as 39.7% using our optimization approach.

Virtual Dynamic Marshalling of Trains under Severe Epidemic Situation

In the context of the global epidemic, urban rail transit has the risk of spreading the virus. Taking Beijing Metro Line 1 as an example, this project establishes a dynamic model of train variable marshalling by studying passenger behavior and virus transmission, aiming to explore more intelligent marshalling mode, optimize transportation organization, and improve the flexibility of train marshalling and dispatching of urban rail transit, so as to improve its transportation efficiency and reduce the station personnel density, Then reduce the risk of disease infection of passengers in the process of taking urban rail transit under the background of the outbreak. The results show that: Dynamic marshalling technology can significantly improve the transport efficiency of urban rail transit trains and effectively control the risk of infection of passengers.

Train schedule optimization for commuter-metro networks

The interconnection and synchronization among different transport modes have been more and more attractive as the modern transportation system is moving towards Mobility-as-a-Service. In this study, we address the train scheduling problem for “commuter rail-metro” systems, where the trains from commuter rail lines can go directly into metro systems to provide seamless services for passengers. To optimize the schedule of trains for both commuter rail lines and metro lines, we propose a job shop scheduling model where precedence constraints from commuter-metro networks are taken into account and develop a mixed-integer programming (MIP) model with quadratic constraints. Our model considers the orders of different types of trains and the safety constraints, due to different types of signalling equipment in commuter and metro systems. Since these constraints involve a set of IF-THEN rules, we prove that these constraints can be equivalently reformulated as linear inequalities, without adding new variables. To solve the proposed model efficiently, we design an iterative solution framework, which generates a feasible solution using dynamic programming, next solves a MIP model, then calculates the train speed profiles, and if train speed profiles violate the safety constraints, re-optimizes the MIP model with modified alternative constraints. To verify the effectiveness of the proposed approaches, numerical experiments are performed on small and real-world instances based on the Beijing metro Line 1 and the Batong Line operational data.

Tunnelling-induced ground deformation subjected to the behavior of tail grouting materials

The deformation of tail grouting plays an essential role in the settlement control of shield tunnelling, which has not been visualized in construction. The conventional methods can only evaluate the quality of tail grouting by the calculating deformation of ground surface, and the mechanism of grouts deformation under the earth pressure is not yet understood in construction. In this study, a novel lab apparatus is designed to explore the mechanism of grouts deformation in respect to the behavior of grouting materials. The purpose of lab tests is to visually analyze the behavior of grouting materials and to investigate the mechanism of grout consolidation induced by varying proportions of grouts and earth pressure. The XRD (X-ray diffraction) and SEM (Scanning Electron Microscope) analysis is used to reveal the micromechanics of the deformation and strength of grouts. Based on laboratory tests results, the parameters of the displacement convergence method are calibrated to optimize numerical analysis. The comparison of results of the proposed method with those obtained by analytical methods and equivalent layer method shows the high performance of the proposed method. The parameters of the proposed numerical method are derived through laboratory tests as opposed to empirical estimations, which could result in more accurate predictions of ground deformation. By comparing the predicted surface settlement to measured data, the Beijing Metro Line 12 project verifies the adaptability of the proposed method.

Adjusting Train Timetables Based on Passenger Flow for Cross-Line Trains

Urban rail transit becomes increasingly convenient for passengers by networking single lines. The urban rail transit network with cross-line trains has different characteristics from the traditional network. The trains can run to different lines at the crossing station, and the operation delay may be spread to different lines because of the operation schedule. A model for adjusting the running delay of cross-line trains is proposed in this paper. The optimization objective is to minimize the total delay time and the number of stranded passengers. In this paper, different scales of delay are analyzed and the operation order of the trains is allowed to be changed at the crossing station. Case simulations achieve good optimization results on the total delay time and the number of stranded passengers. Optimization diagrams are given under different strategies. The model and methodologies are also applied to Beijing Metro Line 13, and good simulation results are achieved for different scales of delay.

Prediction of Surface Settlement in Shield-Tunneling Construction Process Using PCA-PSO-RVM Machine Learning

Surface settlement is one of the key engineering issues during shield construction process. In order to accurately predict surface settlement, this paper proposes a new machine learning method based on relevance vector machine (RVM), principal component analysis (PCA), and particle swarm optimization (PSO). Taking Beijing Metro Line 6 as a case study, the PCA-PSO-RVM model is used to make the prediction and compared with the prediction results of the RVM model using the same samples. In order to evaluate the reliability of the model, three evaluation indexes including mean relative error (MRE), root mean square error (RMSE), and Theil inequality coefficient (TIC) were calculated, and sensitivity analysis was carried out on them. The results show that the minimum relative error between PCA-PSO-RVM and the actual value is only 0.06%. The calculated MRE, RMSE, and TIC are 0.17%, 0.0714 mm, and 0.027%, respectively, which shows that PCA-PSO-RVM model has higher prediction accuracy, smaller deviations, and higher reliability compared with the three other models. Through sensitivity analysis, it is found that the weighted average internal friction angle (φ) has the most significant impact on the surface settlement, which should be focused on in relevant research.