To address the conflict between high-intensity operation and frequent maintenance of urban rail transit trains under the traditional maintenance strategy, an optimization method for multi-day operation scheduling of urban rail transit rolling stock considering a flexible maintenance strategy was studied under a decentralized execution mode of maintenance tasks. Firstly, an optimization model was constructed to minimize the sum of the fixed maintenance cost, the over-maintenance cost, and the insufficient-maintenance cost of rolling stock caused by unbalanced maintenance, considering constraints such as transportation task execution, maintenance task execution, depot maintenance capacity, rolling stock maintenance demand, and standby train arrangement. Secondly, in view of the characteristics of the multi-day operation plan, such as large scale, complex constraints, and strong correlation, a rolling stock space-time connection network with transportation tasks and maintenance tasks as nodes was established, and an improved depth-first search algorithm was designed to solve the constructed model. Finally, a case study was conducted taking an urban rail transit line as an example. The results indicate that compared with the traditional maintenance strategy, the flexible maintenance strategy reduces the over-maintenance and insufficient-maintenance mileages of rolling stock by 59.42% and 49.75% on average, respectively, decreases the total maintenance cost of rolling stock by 6.60% on average under scenarios with different numbers of operating rolling stock, and saves the minimum number of rolling stock required for the operation plan by one train; under the scenario with the same number of operating rolling stock, the decentralized execution of maintenance tasks reduces the standard deviation of the operation mileage of all rolling stock by 7.08% and reduces the number of maintenance rolling stock by two trains; the insufficient-maintenance cost of rolling stock under the same operation mileage level increases with the decrease of the failure rate parameter, and thus the rolling stock tends to execute maintenance before reaching the maintenance mileage standard; the proposed method can flexibly adjust the maintenance locations and timings of rolling stock under the conditions of limited depot maintenance capacity and increased transportation tasks during holidays, which verifies the robustness of the model in extreme scenarios.

To consistently describe the mechanical response of sand and clay under generalized stress paths, a unified critical state constitutive model (CASM-SG) applicable to generalized loading conditions was proposed based on the unified constitutive clay and sand model (CASM) with state parameters and by employing the subloading surface theory and the transformed stress method. In the model based on the original CASM model, a plastic internal variable associated with the initial state of the soil was established by using the concept of subloading surface, and the original two-dimensional yield surface determined from triaxial compression tests was transformed into the three-dimensional stress space through the transformed stress method. A complete constitutive framework was constructed for the CASM-SG model under generalized stress conditions, including the stress dilatancy relationship and the hardening rule. Explicit expressions for the plastic modulus and the elastoplastic stiffness matrix were derived based on the consistency condition. Finally, the proposed model was employed to simulate the mechanical behavior of Hostun sand and Fujinomori clay under drained and undrained triaxial compression and extension conditions. The simulation results indicate that the CASM-SG model can accurately capture the mechanical behavior of both sand and clay under various stress paths. For Fujinomori clay, the triaxial extension strength decreases by approximately 24% compared with the triaxial compression strength, and the CASM-SG model captures this characteristic. Compared to the original CASM model, the CASM-SG model introduces two additional material parameters with clear physical interpretations, demonstrating a favorable balance between modeling accuracy and simplicity.

Fabric anisotropy is an important factor affecting the mechanical properties of sandy soil, and the formation disturbance caused by shield tunnel excavation in sandy soil is largely affected by the mechanical properties of the overlying sandy soil. This study utilizes the two-dimensional discrete element method to model particles as overlapping ellipse-like clusters, specifically arranging the long-axis orientation to create sand samples with varying anisotropy. The long-axis orientation and horizontal deposition direction form the bedding plane. A two-dimensional RVE biaxial test shows that the peak friction angle initially decreases and then increases with the bedding angle, aligning with experimental findings. Subsequently, strata with different bedding angles are generated, and tunnel excavation is analyzed based on Park's stratum loss model. In anisotropic strata, the disturbance range exhibits asymmetry about the tunnel's central axis. The surface settlement curve divides into three zones: influence, expansion, and weakening. The effect of bedding angle is evident only in the influence and expansion zones. Maximum settlement occurs at a bedding angle of 0°, while it is minimized at 45°. As the bedding angle increases, maximum settlement trends upward on the left side and downward on the right side of 45°. The principal stress deflection of the tunnel correlates with the displacement-induced asymmetry. In the samples with bedding angles of 0° and 90°, the main direction of the distribution of the contact normal did not change.

To improve the passing performance of high-speed trains on curved sections, reduce wheelset wear, and extend service life, the LMA/CHN60N wheel-track combination was taken as the research object. Six dimensions of the wheel tread in close contact with the track when the train passes through the curved track section were set as design variables, and the maximum lateral displacement, maximum climb, and maximum contact stress between the wheel and track on both sides were defined as objective functions. The response surface optimization design of the wheel tread dimensions was conducted, and the transient dynamics analysis of the optimization scheme was performed. The results indicate that compared with existing wheelsets of high-speed trains, the maximum lateral displacement, maximum climb, and maximum contact stress of the optimized outer wheels decrease by 1.74%, 1.34%, and 4.49%, respectively, and the maximum lateral displacement, maximum climb, and maximum contact stress of the inner wheels decrease by 0.41%, 1.53%, and 3.92%, respectively. Under the premise of ensuring other performances of the train, the optimization scheme improves the passing performance of the vehicle on curved track sections and can reduce wheelset wear; moreover, the indicators of straight passing performance, safety, smoothness, and durability are all within allowable ranges, thereby extending its service life.

Cloudy weather causes cloud coverage and information loss in multi-temporal remote sensing image (MTRSI), affecting the subsequent application performance. In recent years, cloud removal methods based on low-rank matrix/tensor decomposition and sparse regularization have ignored the consistency features across different bands and different temporal dimensions of image. To this end, under the framework of low-rank matrix decomposition, a novel MTRSI cloud removal model based on factor group sparsity regularization was proposed. Specifically, global spatiotemporal correlations of clean image were characterized by the model using low-rank matrix decomposition; by imposing group sparsity regularization on the factors corresponding to multi-dimensional data, the consistency of spatially smooth regions across bands and time was accurately captured and constrained. Furthermore, a proximal alternating minimization algorithm embedded with the alternating direction method of multipliers was designed to decompose the original optimization problem into two sub-problems, namely low-rank constraint and sparse regularization term optimization, which were updated alternately and iteratively, thereby achieving an efficient solution to the original problem. In simulation experiments, compared with the suboptimal method, the average peak signal-to-noise ratio of the proposed cloud removal method increases by 18.01%; the average spectral angle mapper decreases by 43.01%; the average structural similarity increases by 4.1 × 10⁻³; the average correlation coefficient increases by 2.3 × 10⁻³; and the required running time decreases by 78.43%. Meanwhile, better cloud removal results are also achieved in real-scene experiments.

Wind-induced vibration of catenary is a typical disaster of railway power supply systems in windy areas. It is difficult for existing theoretical analyses of vibration characteristics and finite element software to accurately simulate field conditions, which makes it difficult to verify their calculation results with field measurement data, and is not conducive to improving the calculation accuracy of subsequent nonlinear models. Therefore, a small-scale catenary model was built. Firstly, a finite element numerical calculation program integrating the large-deformation geometric nonlinearity of catenary and the stretching-contracting stiffness nonlinearity of suspension string was written in MATLAB, and the vibration modes of the small-scale catenary model under lateral excitations of different frequencies were solved. Secondly, an experimental platform with adjustable lateral excitation frequency was built, and the vibration modes under horizontal airflows at various frequencies were measured by a laser displacement sensor. Finally, the vibration waveforms obtained by the two methods were comparatively studied. The calculation results indicate that in a certain frequency range, the vibration frequency of the model is the same as the lateral excitation frequency, and when the lateral excitation frequency is equal to the fundamental frequency of the model, the maximum horizontal displacement distance reaches the maximum. Under the lateral excitations of different frequencies, the trajectories of the measuring point are different: When the frequency is less than the fundamental frequency, the trajectory is mostly 8-shaped; when the frequency is greater than the fundamental frequency, it is mainly a flat oval; when the frequency is equal to the fundamental frequency, it is almost a horizontal straight line. By comparing the test results, it is revealed that the finite element numerical calculation method can accurately calculate the fundamental frequency of the model, as well as the response frequency, vibration mode, and variation trend of amplitude with frequency under excitation. However, there is a significant deviation between the calculated amplitude values and the test results. Therefore, the calculation and prediction of key amplitude values need to be corrected by combining with experiments.

Fractured surrounding rock zones encountered during tunnel construction can easily trigger geological hazards such as collapses, roof falls, water inrushes, and mudbursts. To comprehensively improve the accuracy and efficiency of dynamic optimization design and multi-field coupled risk analysis, a modeling method for fractured surrounding rock integrating multi-source short-range advanced geological forecasting data was proposed. Firstly, a machine learning algorithm was employed to accurately extract the feature information of fractured surrounding rock from tunnel face images and ground-penetrating radar images. Secondly, the geometric and semantic features of the two types of data were registered and fused within a unified spatiotemporal reference framework to generate a unified semantic point set. Finally, a dense voxel grid was constructed, and the semantic point sets within the neighborhood of each voxel were traversed to build a three-dimensional fractured surrounding rock voxel model using the inverse distance weighting interpolation algorithm. A typical long and deep-buried tunnel was selected as a case to conduct experimental evaluation, and the voxel model and registered deepened blast hole data were subjected to voxelization processing and attribute alignment comparative analysis. The results indicate that the average classification accuracy of the constructed voxel model is 83.31% in fractured risk zones and 82.89% in non-risk zones; the model demonstrates high consistency with the blast hole data in terms of spatiotemporal distribution at the voxel scale, effectively characterizing the spatiotemporal evolution characteristics of the fractured surrounding rock during the dynamic excavation process.

In order to investigate the lateral load–displacement behavior of helical steel piles in sand, by considering the nonlinear pile-soil interaction, three p-y curves (p denoted soil reaction per unit length, and y denoted lateral displacement of the pile shaft) were selected to predict and compare lateral bearing behaviors. First, the existing classical sand p-y curve and two CPT-based p-y curves (power function and hyperbola) were analyzed, and their shortcomings were identified. Second, a linearly varying correction factor was introduced within the helical plate influence zone to modify three p-y curves, thereby incorporating the lateral bearing action of the helical plates. Third, the finite-difference method was employed to solve the bending differential equation of the laterally loaded helical steel pile, with pile shaft displacements obtained through iterative solution. Finally, by using the field tests of lateral bearing capacity for helical steel piles conducted in the literature, the prediction results of the three modified p-y curves were subjected to error and statistical analysis against the actual field measurements. The results show that the hyperbola-modified p-y curve produces load–displacement predictions closest to the measurements, with an average predicted-to-measured ratio of 1.04 and a goodness of fit of 98.5%. Among the three methods, the hyperbola approach yields the mean absolute percentage error of 11.63%, compared to 36.32% for the power function method and 24.25% for the classical p-y curve method. Its 95% confidence interval for mean prediction error spans from −6.0% to 11.9%, and the average error of 90% confidence interval spans from −4.6% to 10.5%, which verifies the reliability of the method. These findings provide a robust reference for accurately predicting the lateral load–displacement behavior of helical steel piles.

To investigate the friction and sliding performance of laminated-rubber bearings under aging conditions, heat aging tests and quasi-static tests were conducted based on the related provisions of shear aging resistance in the bearing specification. Firstly, the actual working state of the bearing in bridge engineering was simulated. Then, the bearing samples were subjected to hot air accelerated aging treatment through an aging chamber and then to horizontal cyclic quasi-static loading through a compression-shear machine. Finally, comparative analyses were conducted on the deformation state, hysteresis behavior, and related mechanical responses of the bearing specimens under different loading conditions. The results show that the shear deformation degree of the aged specimens is large during loading; the sliding degree is small, and the hysteresis loop is narrow and long. The sliding displacement of the bearings is negatively correlated with surface pressure and loading rate. The shear stiffness of the bearings first decreases and then increases as equivalent shear strain rises, and the shear stiffness of aged specimens decreases; the equivalent stiffness increases. At the average surface pressure of 10 MPa during the use of the bearings, there is less difference in the friction coefficient between the two types of specimens, both of which are lower than the recommended value of 0.20 in the specifications. The friction coefficient of the aged specimens is generally greater than that of unaged specimens, and insufficient energy dissipation is observed. There is a performance change point in the unaged specimens, and the overall mechanical behavior shows a three-fold trend. However, the friction and sliding behaviors of the aged specimens are stable, and there is no sudden change as the equivalent shear strain increases from 0 to 250%.

To optimize the T-shaped retrofitting scheme of diagonal members, the influence of structural and material parameters on the bearing capacity of the members after retrofitting was investigated through theoretical analysis, experimental study, and finite element analysis. Firstly, a theoretical model of the T-shaped retrofitting section was established based on the composite beam theory, so as to analyze the improvement in flexural stiffness after T-shaped retrofitting. Secondly, eccentric compression static experiments of single-side connected angle steels for T-shaped retrofitting were conducted. Finally, the finite element model was used to analyze the effects of the slenderness ratio, width-to-thickness ratio, and material strength on the selection of the number of connectors. The results indicate that the improvement in flexural stiffness after T-shaped retrofitting decreases with increasing load. A decrease in the number of connectors leads to relative slip perpendicular to the direction of member deformation. For the experimental members, an increase in the number of connectors leads to greater bearing capacity, with a maximum retrofitting effect of 100.4%. For the T-shaped retrofitting scheme of diagonal members, two connectors are sufficient when the slenderness ratio is below 150. Otherwise, three connectors are required. The width-to-thickness ratio and material strength have no effect on the selection of connectors.

To simplify the steel shell–concrete composite pylon structure and improve construction efficiency, a novel ribbed straight-hooked rebar (RSHR) shear connector was studied. Firstly, the push-out and pull-out tests of the shear connector were designed. The shear bearing capacity, pull-out bearing capacity, and failure characteristics of each specimen were obtained. Secondly, the corresponding relationship between the failure mode and the bearing capacity of the specimen was obtained by using finite element analysis software. Finally, based on model analysis, the influence of the burial depth on the shear connector performance was further discussed, and the formula for calculating the shear and pull-out bearing capacity of the RSHR shear connector was proposed. The results show that under shear loading, the RSHR shear connector undergoes yielding of its stiffening ribs, while under pull-out loading, concrete punching failure occurs. Along with the yielding of the straight-hooked rebar, the difference in failure modes can cause the shear connector’s bearing capacity to vary by up to five times. Under push-out loading, the steel–concrete bonding force accounts for 30% of the total bearing capacity. The position of the straight-hooked rebar determines its stress characteristics and failure modes under pull-out loading. Reducing the spacing between the straight-hooked rebar and stiffening ribs increases the pull-out bearing capacity of the shear connector by 35%, while doubling the burial depth of the shear connector makes the pull-out bearing capacity increase by one time.

This study aims to address the issue of vortex-induced vibrations (VIV) in long-span bridges under low wind speeds, which can lead to structural fatigue of the bridge and affect driving comfort. Based on the wake oscillator model and a variable-damping coefficient eddy current damper, a semi-active control strategy was developed. Firstly, a dimensionless VIV force model of the bridge wake oscillator was established, and its parameters were fitted using experimental data via a genetic algorithm. Then, a variable-spacing ball screw eddy current damper was designed, and the corresponding relationships between the damping coefficient and the axial velocity–air gap, as well as the damping force and the axial velocity–air gap, were determined through COMSOL simulations. Next, a genetic algorithm was applied to optimize the semi-active control parameters for the selected linear quadratic regulator (LQR) and sliding mode control (SMC) algorithms. Finally, a comparative study was conducted on the VIV suppression effects of an uncontrolled system, LQR, and SMC semi-active control by using the Hei-Bai-Shui River Bridge as the engineering case. The results show that the wake oscillator model accurately describes the VIV characteristics of the bridge. At the maximum VIV wind speed of 16.5 m/s, LQR and SMC semi-active controls can reduce the bridge amplitude to 4.95% of the uncontrolled amplitude, which is well below the regulated limit. Overall, the damping effects of LQR and SMC control are similar, but under the LQR control, the air gap of the damper remains unchanged, while under the SMC control, the air gap varies periodically. The former offers more favorable conditions for engineering implementation.

To address the problems in the space vector pulse width modulation (SVPWM) of current source inverter (CSI) that switching signals cannot be directly generated through the comparison between digital modulation signals and carrier signals, and that the required additional hardware logic conversion circuits cause reliability degradation and signal delay, a direct digital implementation method of SVPWM for CSI was proposed. Firstly, the spatial distribution of basic vectors formed by all switching states was analyzed, and a sector determination method for the reference current vector was provided. Taking the first three sectors as an example, the calculation method for the duty cycle of adjacent vectors was derived; the expressions for vector selection and duty cycle calculation in all sectors were summarized, and the duty cycle in the over-modulation region was corrected. Then, the vector action sequence within a carrier cycle was mapped into switching action signals, and the configuration methods of action qualifier registers and compare value registers of the digital signal processor (DSP) under different sectors were summarized. Finally, the loop structure of the control system was designed, the proposed method was verified on a 3 kW experimental platform, and its steady-state performance was compared with that of the scheme adopting hardware logic conversion circuits. The experimental results indicate that the proposed method enables the DSP to output correct switching signal waveforms; the total harmonic distortion (THD) of current is only 0.99%, and the 5th and 7th harmonic contents are 0.100% and 0.105%, respectively. The current THD of the scheme adopting hardware logic conversion circuits is 1.46%, and the 5th and 7th harmonic contents are 0.18% and 0.16%, respectively. The proposed direct digital implementation method of SVPWM is correct and feasible, and it has superior steady-state performance due to the avoidance of signal transmission delay.

To address the problems of limited endurance of unmanned aerial vehicles and unstable power transmission caused by positional offset during hovering charging, a T-shaped asymmetric magnetic coupling mechanism based on demagnetizing field theory was proposed. Firstly, the magnetic field concentration ability was enhanced, and the demagnetization effect was suppressed by optimizing the magnetic circuit design, thereby improving the coupling coefficient; the influences of key parameters such as the upper side length, lower side length, and middle magnetic column height of the launch mechanism on the coupling performance were analyzed. Secondly, the optimal structural dimension combination was determined using a parametric sweep method. Finally, an experimental prototype was built to conduct performance testing. The research results indicate that the mutual inductance fluctuation rate of the structure is only 2.3% within a rotational offset range of ±20° and 4.1% within an axial offset range of ±20 mm, exhibiting excellent anti-offset characteristics; the mutual inductance fluctuation rate under rotational offset is 2.4%, and the output power fluctuation rate within an axial offset range of ±20 mm is 4.2%, which are basically consistent with the simulation results; under varying load conditions, the system can achieve constant current output, and the designed coupling mechanism has good robustness and stability under dynamic working conditions. The proposed T-shaped coupling mechanism has advantages such as compact structure, strong anti-offset ability, and stable output and is suitable for unmanned aerial vehicle application scenarios requiring continuous power supply, such as relay communication and power inspection.

To quantify the functionality recovery weighting coefficient in the seismic resilience assessment of cable-stayed bridges and avoid the subjectivity relying on experience or expert questionnaires, a seismic resilience assessment method based on a modular functionality recovery function was proposed. First, a Pair Copula hierarchical model was employed to divide a cable-stayed bridge into three levels, i.e., components, subsystems, and the system, and the seismic fragility of each level was calculated. Second, based on the probability ratio of each subsystem under different damage states, probability weighting was performed to construct a quantitative model of the functionality recovery weighting coefficient. Furthermore, a modular functionality recovery function was established by comprehensively considering functionality recovery, repair time, and repair path. Then, a system-level functionality recovery function was formed by integrating the repair sequence of subsystems. Finally, a seismic resilience assessment procedure for cable-stayed bridges was established, and a seismic resilience assessment was conducted taking a cable-stayed bridge as an example. The results indicate that the functionality recovery weighting coefficient varies with the ground motion intensity and is closely related to the damage degree of each subsystem. If a constant weighting coefficient is adopted, the recovery contribution of the bearing subsystem is underestimated by approximately 50%. The seismic responses of the components of cable-stayed bridges have strong correlations; if the components are assumed to be completely independent, the calculation error of the system fragility can reach 28%–53.3%. Within the ground motion intensity range specified by codes, if the repair sequence of subsystems is neglected, the system resilience index is underestimated by approximately 9%.

To address the issues of degraded communication quality, reduced task offloading performance, and constrained computational efficiency in unmanned aerial vehicle (UAV) edge computing networks caused by poor communication conditions and limited wireless device energy when terrestrial wireless infrastructure fails, supported by intelligent reflecting surface (IRS) and wireless power transfer (WPT) technologies, UAV edge computing networks were studied, and corresponding optimization schemes were proposed. On the one hand, by adopting IRS technology, the communication quality of wireless links was optimized through real-time adjustment of the reflected signal phase to direct signals toward the target, thereby improving the task offloading capability. On the other hand, WPT technology was used to supply temporary energy to wireless devices, providing power support for them to execute computation tasks. Under this network, through an iterative optimization method, the spectrum resources, CPU frequencies and transmitting power of wireless devices, time allocation between WPT and task offloading, IRS coefficients, and UAV flying trajectory were analyzed and derived, and the network’s computation rate was optimized. The simulation results verify that the proposed scheme effectively improves the overall computing performance of the network. In terms of computation rate, the proposed scheme outperforms various UAV flying schemes by at least 34.3%, various task processing mechanisms by at least 15.3%, and different optimization schemes by at least 15.9%. The above results demonstrate that the proposed scheme can significantly improve the edge computing performance in UAV scenarios and can provide an efficient and reliable solution for wireless device energy supply and collaborative computation task processing in UAV edge computing network.

Because of the train operation adjustment considering transfer under the railway line faults, minimizing the total train knock-on delay time and the number of passengers failing to transfer caused by railway line faults was taken as two objectives, and an optimization model for train operation adjustment under the influence of railway line faults was constructed. In light of the model as a large-scale hybrid integer programming model, an improved particle swarm based on Gaussian walk (IPS&GW) was designed. Road network composed of some upward-direction sections of the Beijing–Guangzhou Railway and downward-direction sections of the Zhengzhou–Xuzhou Railway was used to form a testing scenario. The proposed IPS&GW algorithm was used to solve the optimization model for train operation adjustment based on different train operation recovery strategies (strategy Ⅰ–strategy Ⅳ). The results show that compared to strategy Ⅰ, when the disturbance duration of railway line fault ranges from 10 to 30 minutes, the decreasing ratio of train knock-on delay time based on strategies Ⅱ, Ⅲ, and Ⅳ is respectively in the range from 82.5% to 86.6%, from 70.5% to 81.49%, and from 55.8% to 58.7%. The decreasing ratio of the total number of stranded passengers is respectively in the range from 28.3% to 39.1%, from 57.3% to 61.9%, and from 88.4% to 89.4%. Under different disturbance scenarios, a significant decrease in the number of passengers failing to transfer can be achieved by increasing the total train delay time by a certain amount. Finally, the proposed IPS&GW algorithm is compared with the traditional particle swarm optimization (PSO) algorithm. The former shows an advantage in the convergence speed of the objective function, so that the scheduled operation requirements for the train can be met, and the number of stranded passengers in the transfer hub stations is reduced.

To solve the problems of insufficient data volume and unbalanced category distribution in the detection of the stator surface of maglev tracks, a vision-language fusion detection method based on a large language model-guided diffusion model was proposed. First, given the current situation of scarcity and unbalanced distribution of five types of samples (spalling, cracking, scratching, stator gap, and beam gap), a prompt word generation strategy guided by a large language model was designed to generate diversified semantic descriptions of defects through chain-of-thought reasoning. Secondly, the generated prompt words and spatial mask constraints were input into a latent diffusion model to generate high-quality samples with similar distributions, effectively expanding the data of scarce categories. Finally, a detection network fusing vision and language modalities was constructed, where bidirectional cross-attention fusion of images and texts was achieved through a feature enhancer, a language-guided query selection mechanism was adopted to dynamically generate detection queries, and a cross-modal decoder was designed to complete multi-stage feature interaction. The research results indicate that under the condition of data augmentation assisted by the large language model, the quality of generated samples increases by approximately 15% compared with traditional generation methods, and the average detection accuracy of the detection network on the five categories increases by approximately 7% compared with baseline methods.

To address the problems of insufficient geometric freedom and difficulty in balancing multi-physics requirements in the lightweight design of rotor laminations for traditional interior permanent magnet synchronous motors, an optimization design method integrating parametric geometry, sampling under complex constraints, and machine learning was proposed. First, a lightening cavity contour was constructed using two connected second-order Bézier curves defined by five control points, achieving a geometric description with few parameters and high flexibility. Second, an experimental design method integrating acceptance-rejection sampling and a parameter bias strategy was proposed to generate 100 sets of high-quality samples under complex constraints. Then, a surrogate model based on feature engineering, kernel density estimation, and an adaptive weighting strategy was constructed to perform high-precision prediction of average torque, torque ripple, and maximum equivalent stress, with a coefficient of determination R² > 0.89. Finally, a multi-objective optimization scheme was established and solved using a differential evolution algorithm. Finite element simulations indicate that, compared with the lightweight design with traditional circular cavities, the optimized scheme increases the lightening cavity area by 174.6% and reduces the maximum equivalent stress by 18.2% while maintaining electromagnetic performance almost unchanged. This achieves synergistic optimization of multi-physics fields and lightweighting, helps to improve motor economy and power density, and provides a new approach for low-inertia and fast-response motor design.

To address the insufficient durability of recycled concrete structures in the Hetao irrigated saline soil region, a typical geomorphological environment in the area was simulated, and concrete specimens were placed in a dry, wet, and freeze-thaw environment to investigate the erosion regularity and mechanism of sodium sulfate. Concrete type, water-cement ratio, and sodium sulfate solution concentration were employed as experimental variables. The quality evaluation parameter ƞ_a and the dynamic elastic modulus evaluation parameter ƞ_b were selected as key evaluation parameters to establish a comprehensive damage evaluation index. Based on this, a two-parameter Weibull reliability analysis was conducted, and a sensitivity analysis of each influencing factor was performed using grey relational grade. The results show that ordinary concrete exhibits better erosion resistance than recycled concrete; after the fourth cycle, the ƞ_b value of ordinary concrete is four times that of recycled concrete. Furthermore, appropriately reducing the water-cement ratio can improve the erosion resistance of recycled concrete. Under the influence of multiple factors, the damage to recycled concrete is caused by the cumulative effects of sodium sulfate crystallization expansion and chemical corrosion. The sodium sulfate with a higher concentration leads to faster damage development. After three cycles, the ƞ_b value of the RC-0.46-0% group is still 0.051, while the ƞ_b value of the RC-0.46-10% group is −0.066, indicating that the specimen has already been destroyed. The Weibull distribution function can effectively describe the erosion damage process of recycled concrete. By establishing an accelerated life reliability function, the service life of the specimen can be intuitively predicted, and the prediction results are consistent with the experimental results. According to the analysis results of the grey relational grade, after four cycles, the ƞ_a value of the specimen with a water-cement ratio of 0.53 is 0.36 and 0.65 lower than that of the specimens with water-cement ratios of 0.46 and 0.39, respectively, while the ƞ_b values of the latter two groups of specimens are basically the same, Therefore, the water-cement ratio is the main factor influencing the durability of recycled concrete.

During the operation of a piston pump, the contact behavior of the spline pair between the cylinder and the shaft aggravates the tooth surface wear of the spline and reduces its operational reliability. To predict the service life of the shaft spline, the Archard model and the SWT model were combined to analyze the fretting damage and fatigue life of the spline pair under different outlet pressures of the piston pump. First, a finite element model for fretting damage of the spline pair between the cylinder and the shaft of an axial piston pump was established using the finite element method. Second, based on the established finite element model, the distribution of Ruiz fretting damage parameters on the tooth surfaces of the piston pump under different outlet pressure conditions was analyzed, and the fretting wear increments of the spline tooth surfaces were predicted. Finally, combined with the Miner-Palmgren (M-P) rule and the response under cyclic fatigue loading, the predicted tooth surface fatigue life of the axial piston pump was obtained. The results show that the maximum Ruiz damage parameter of the piston pump spline tooth surface is mainly concentrated at the ends of the spline tooth surface. The damage at both ends of the spline is more severe, while the damage in the middle region is relatively slight, and the wear at the front and rear ends of the spline is 114% and 62% higher than that in the middle region, respectively. An increase in the outlet pressure of the piston pump intensifies tooth surface wear and significantly reduces the service life of the spline pair, and the fatigue life at an outlet pressure of 30 MPa is reduced by 60% compared with that at 20 MPa. The results provide guidance for the operational reliability and subsequent optimization analysis of piston pump splines.

To address the lane-changing decision-making challenge of autonomous vehicles in autonomous transportation systems, a lane-changing decision model based on an incomplete-information dynamic game was proposed. First, grounded in game-theoretic principles, core issues such as lane-changing intention recognition, game-based lane-changing conditions, and model solution methods were delineated, and a corresponding game framework was established. To optimize the payoff function, a multi-objective payoff function that comprehensively considers safety, efficiency, and comfort was constructed, with appropriate features selected to quantitatively evaluate the payoff of each objective. In conjunction with inverse reinforcement learning, the weight allocation was learned from the NGSIM dataset, ensuring multi-dimensional consideration in decision-making. Experimental results indicate that the proposed model effectively enhances decision safety and efficiency in both successful and failed game traffic scenarios. Compared with traditional defensive lane-changing models, the proposed model demonstrates superior performance in improving driving efficiency, demonstrating its practicality and advantages in autonomous vehicle lane-changing decision-making. Furthermore, validation through SUMO simulation shows that the model exhibits good safety and traffic efficiency performance in realistic highway scenarios, effectively adapts to variations in traffic flow, and supports safe and efficient vehicle operation, thereby verifying its practical value in autonomous vehicle lane-changing decision-making.

To investigate the interference of stray currents from the power supply system of urban rail transit lines on adjacent buried metal pipelines and their control, the electrical coupling effects and dynamic control strategies between the urban rail transit power supply system and buried pipelines were analyzed. First, a dynamic coupling parameter calculation model integrating dynamic control strategies was proposed for the urban rail transit power supply system and buried metal pipelines. Based on actual line parameters, simulations were conducted to analyze the dynamic distribution of power supply system parameters and pipeline parameters under different coupling scenarios, clarifying the influence of multi-return-path coupling interactions. Second, to address the electrical coupling interference between the urban rail transit power supply system and pipelines, a dynamic control strategy was proposed, and the structure of a dynamic control device was designed, with its control characteristics analyzed. Finally, by using parameters from an actual urban rail transit line in China as an example, simulation analysis was performed to verify the dynamic control effect on pipeline stray current and pipe-to-soil potential. The results indicate that electrical coupling between the urban rail transit power supply system and adjacent pipelines leads to an increase in both the return system parameters of the urban rail transit and the pipeline safety parameters. By taking simulation case 3 as an example, the maximum instantaneous pipeline potential reaches 16.2 V. The coupling effect is related to the insulation condition of the running rails, the insulation condition of the pipeline, and the rail potential at the coupling location. The proposed dynamic control strategy can effectively suppress the electrical coupling impact of the urban rail transit power supply system on pipelines, clamp the pipeline voltage within the standard limits, and redirect the stray current on the pipeline back to the urban rail transit power supply system.

To simplify the connection construction of precast concrete beam-column joints and improve construction efficiency, a precast beam-column joint with bolt-plate mechanical connection was proposed. The pseudo-static loading tests of seven specimens were carried out to analyze the effects of high-strength bolts, longitudinal reinforcement ratio of the beam, anchorage length and methods, as well as embedded steel plates on the enlarged head surface on the seismic performance of the joints. Results show that the joints exhibit excellent bearing capacity and ductility, with a reliable mechanical connection and a ductility coefficient of 3.79–5.69. The targets of plastic hinge failure at the beam end and the ductile design principle of “strong joint” can be achieved. When the anchorage length of longitudinal reinforcement of the beam is increased from 200 mm to 300 mm, the joint’s peak bearing capacity, ductility coefficient, and cumulative energy dissipation can be enhanced by 24.38%, 16.36%, and 38.08%, respectively. The peak bearing capacity and ductility coefficient of the joint with embedded steel plates on the enlarged end surface can be increased by 18.69% and 13.29%, respectively. While the reinforcement ratio of longitudinal reinforcement of the beam is increased from 0.75% to 1.18%, the failure mode of the specimen transfers from flexural-shear failure at the beam end to wedge-shaped failure at the enlarged head. The peak bearing capacity and cumulative energy dissipation can be improved by 20.65% and 20.30%, but the ductility coefficient decreases by 16.34%. Optimizing bolt edge distance and spacing, as well as enhancing the parameters including reinforcement along the beam direction on the enlarged head are recommended for subsequent research, thereby ensuring the rational formation of a plastic hinge at the beam end and ultimately achieving the ductile design principle of “strong joint”.

To obtain the analytical solution formula of the stiffness matrix of a 2-node 6-degree-of-freedom explicit variable cross-section curved beam element, the variable cross-section curved beam element was incorporated into the widely used finite element system of rod structures. Based on Castigliano’s second theorem, the stiffness matrix of the spatial variable cross-section curved beam element was derived, and the flexibility matrix of the variable cross-section curved beam element was deduced by using the principle of stationary potential energy of elastic bodies; then, the cantilever end stiffness matrix of the variable cross-section curved beam element was obtained through inverse calculation. According to the static equilibrium condition and the principle of virtual work, the element stiffness matrix of the overall variable cross-section curved beam was obtained. In addition, the finite element formulation of the variable cross-section curved beam element could be degenerated into the formulation of uniform cross-section and uniform curvature beam elements and the standard formulation of uniform cross-section straight beam elements. A static calculation program for variable cross-section curved beam bridges was developed using MATLAB, and it was compared with the ANSYS solid finite element model to verify the static analysis theory of variable cross-section curved beams. The results indicate that the developed theory analyzes the bending-torsion coupling of the variable cross-section curved beam based on the finite element theory. The maximum deflection error between the variable cross-section curved beam theory and the ANSYS solid finite element model is 3.72%, and the maximum error compared with the ANSYS beam element model is less than 0.5%; furthermore, the maximum deflection error between the variable cross-section straight beam degenerated from the developed theory and the ANSYS solid finite element beam model is 1.72%, and the maximum error compared with the ANSYS beam element model is less than 0.1%.

To investigate the influence of stray currents from urban rail transit on power grid transformers, the characteristics and causes of the neutral point current of transformers along metro lines were analyzed based on long-term monitoring data from the Hubei Observation and Research Station of Earth Stray Currents and Energy Equipment Safety. First, the balance and difference in the neutral point current among transformers within the same power grid were statistically analyzed. Second, the current characteristic quantities in different power grids were compared based on the wavelet transform. Finally, the differences in current waveform characteristics before and after metro operations, as well as during different operation periods, were examined. The results indicate that stray currents generated by urban rail transit cause an imbalance in the amplitude of the neutral point current among different transformers in the same grid, with a maximum difference of over 10 times. Denser metro lines around a substation result in a larger amplitude of the neutral point current of its transformer. When metro lines and power grids are geographically closely interconnected, the similarity of neutral point current waveforms among different transformers in the grid is high, with a correlation coefficient of over 0.8. The direct current generated by some metro lines flows only between local stations in the grid, which significantly reduces the similarity of current waveforms within the grid. Within the same grid, the waveform similarity is high when the wavelet scales of the neutral point current waveforms of transformers are close; however, the wavelet characteristics of the neutral point current of transformers from different grids are not comparable. When there are obvious differences in the alignment or operation of metro lines, the influence of different metro lines on the neutral point current of transformers can be identified based on wavelet scales.

To address deficiencies of insufficient constraint consideration, single speed grade coverage, and unclear parameter influence mechanism in existing alignment design of flexible-bendable normal-conducting high-speed maglev turnouts, multi-dimensional constraint conditions for alignment design were clarified, and a “transition curve, circular curve, and transition curve” alignment design method integrating standard stator unit length constraints, vehicle construction constraints, and interface matching requirements was proposed. Finite element analysis models of turnout beams with different lengths were established. The mapping relationship between beam length and structural stress was quantified via nonlinear regression fitting, and the minimum theoretical turnout length was determined. Alignment designs for turnouts with different lateral passing speeds were performed to obtain alignment parameters for each speed grade. The influence laws of lateral passing speed and acceleration on alignment parameters were analyzed. Results show that maximum beam stress decreases nonlinearly with increasing length, and the length effect on stress weakens significantly beyond 90.00 m. With a safety factor of 1.3, the minimum theoretical length of the flexible-bendable turnout is 56.76 m. When lateral passing speed does not exceed 50 km/h, or the turnout number is less than 7.500#, a single circular alignment is recommended. The “transition, circular, and transition” alignment is particularly suitable for medium-to-high-speed scenarios above 70 km/h. When lateral passing speed does not exceed 80 km/h, vehicle construction radius constraint is dominant, exhibiting “short transition, small radius, long circular curve, and small turnout number” characteristics. When speed exceeds 100 km/h, centrifugal force balancing is the core requirement, forming a structure with “long transition, large radius, short circular curve, and large turnout number” characteristics, with circular curve proportion decreasing significantly and transition curve gradually becoming dominant. With increasing lateral acceleration, transition curve length increases, while circular curve radius, circular-transition ratio, and total turnout length decrease. When acceleration exceeds 1.000 m/s², turnout alignment parameter changes tend to be gradual.

To address the challenges posed to the safe and economic operation of distribution networks by the large-scale integration of electric vehicles (EVs) and wind and solar power, as well as the issue of low accuracy in traditional single timescale optimization dispatching methods, a multi-timescale coordinated distribution network optimization dispatching strategy that considered the dispatchable potential of charging stations was proposed. Firstly, an assessment method for the dispatchable capacity of charging stations based on the Minkowski sum was proposed. By aggregating EV clusters within the stations and treating them as generalized energy storage systems, the real-time dispatchable potential of each station was accurately calculated. Subsequently, a day-ahead and intra-day two-stage optimization dispatching strategy for the distribution network based on model predictive control was introduced. In the day-ahead dispatching stage, with the objective of minimizing the daily operating cost of the distribution network, the electricity purchase and sales plans, along with the output schedules of controllable distributed generators and energy storage systems, were coordinately optimized to achieve optimal allocation of global resources. In the intra-day dispatching stage, by leveraging rolling optimization and feedback correction mechanisms based on the day-ahead plan and real-time states, the day-ahead output schedules of controllable devices were dynamically corrected to cope with intra-day fluctuations in wind power, photovoltaic power, and load, ensuring the stable operation of system state variables under disturbances. Finally, the performance of the proposed strategy in fulfilling day-ahead dispatching instructions under uncertain disturbances was analyzed. Simulation results demonstrate that by exploiting the dispatchable potential of charging stations, the proposed strategy reduces the daily operating cost of the distribution network by 10.86% compared to scenarios without V2G capability. Furthermore, it achieves an additional 13.66% cost reduction compared to day-ahead optimization strategies, while limiting the deviation from the day-ahead tie-line power to merely 1.77%. This approach realizes distributed optimization dispatching for the distribution network, significantly enhancing its economic efficiency and robustness amidst uncertainties.

To address urban traffic congestion propagation, a lane-level Micro Cell Transmission Model (Micro-CTM) was proposed from a microscopic perspective. By leveraging the multimodal semantic cognition capabilities of a large language model (LLM), a lane-level traffic congestion evolution model, the coupled map lattice-driven lane congestion evolution model (CML-LCEM), was constructed. First, a traffic flow feature recognition framework was constructed by integrating an LLM with a mixture-of-experts (MoE) architecture, enabling multimodal semantic cognition of urban traffic through cross-modal semantic alignment and model fine-tuning. Secondly, transfer entropy was employed to analyze the causal relationships between lane-level cells, based on which a lane-level traffic congestion evolution model was constructed to predict key cells in traffic congestion situations. Finally, experiments were conducted on a local road network within the Beijing High-level Autonomous Driving Demonstration Zone, and multiple types of cells were classified to validate the model’s ability to characterize lane-level saturation and congestion propagation. The results show that the proposed method significantly improves lane-level prediction accuracy during peak hours compared to traditional models. Early intervention on key cells can reduce average vehicle travel time by 28.3%, providing a data-driven large-model solution for real-time congestion warning, mitigation strategy formulation, and integrated vehicle-road-cloud applications in intelligent transportation systems.

As the intelligent technologies continuously develop, the transportation system is shifting toward autonomous and unmanned operation modes. To clarify the technical characteristics and functional advantages of autonomous transportation systems (ATS) at different autonomy levels, this paper deconstructs ATS into five layers of the system, scenario, function, technology, and service by quantifying the generational evolution standards of ATS, evaluating system topology, and simulating and analyzing the generational evolution paths of ATS. Meanwhile, in terms of the linkages between traffic scenarios, traffic entities, and traffic services, it employs the quantized values of technological types and their development levels required by each function as the link cost, and proposes a hierarchical evolvable architecture model for ATS based on classical network theory. Finally, by taking the priority passage service under road intersection scenarios as an example, the interaction relationship between ATS traffic entities, functional realization, and information flow is analyzed in depth by calibrating the link cost via questionnaires. The results show that increasing interoperable linkages can significantly improve the autonomy level of ATS, with the key milestone for full autonomy being “human participation reduced to less than 10%”. The proposed hierarchical evolvable architecture model provides a quantitative analysis framework for ATS generational evolution, filling the gap of existing theories in system-level dynamic evolution modeling. The findings can assist transportation authorities in ATS development planning and provide a quantitative basis for priority setting in technological research and development.

As typical application scenarios for autonomous vehicles, intersections pose severe challenges to the prediction systems of autonomous driving due to the complex interaction patterns of traffic participants and multi-modal behavioral trajectory features. In view of the problems of existing map-free trajectory prediction methods, such as insufficient accuracy in modeling vehicle interactions, coarse characterization of motion direction features, and limited stability in long-term predictions, a multi-vehicle trajectory prediction method based on spatio-temporal feature enhancement (wave-enhanced spatio-temporal transformer, WAGT) was proposed. Firstly, a spatial interaction modeling framework based on graph neural networks was constructed to characterize the interaction intensity among vehicles through weighted adjacency matrices. Secondly, a dual-channel feature enhancement module based on a wave superposition mechanism was introduced to adaptively model the differences in lateral and longitudinal vehicle motions from the perspectives of amplitude and phase. Finally, a Transformer encoder-decoder integrating time-aware positional encoding was designed to alleviate the problems of position confusion and error accumulation in long-sequence prediction. Quantitative evaluation of the method performance was conducted based on the SIND dataset of Chinese signalized intersections, and comparisons with various map-free trajectory prediction models were performed. Experimental results indicate that the method achieves optimal performance in different prediction horizons. Compared with the representative graph interaction model GRIP, the average displacement error (ADE) and final displacement error (FDE) of the method are improved by 39.70% and 22.90%, respectively, which verifies the advantages of the model in prediction accuracy and robustness under complex intersection scenarios.

Operation interruption is a safety factor that cannot be ignored in the actual operation of urban rail transit. To address train operation adjustment under unidirectional operation interruption in urban rail transit, a combined adjustment strategy of “reverse operation + short turning” was proposed. From the perspective of passenger time value, taking the minimum waiting time of passengers at the station as the optimization objective, a two-stage model of urban rail transit train operation adjustment under unidirectional operation interruption was established for the interruption stage and the recovery stage. Considering the complexity of the model and the requirements of the adjustment problem for solution efficiency, an adaptive large-scale neighborhood search algorithm based on different service patterns was specifically designed for the proposed model, so as to achieve effective solutions for large-scale instances. The case study shows that, under unidirectional operation interruption, the “reverse operation + short turning” strategy reduces passenger waiting time by 5.19% compared with the reverse operation strategy. Compared with closing the interrupted direction line, it can reduce the waiting time of passengers on the whole line by 19.80%, and the transportation services in both directions are more balanced. In addition, when the interruption duration is more than 15 minutes, adopting the strategy of “reverse operation + short turning” to organize train operation adjustment can achieve better results than closing the interrupted direction line.

The normal force of linear motors possesses time-varying characteristics and controllability, which are critical to the stable operation of maglev trains. To investigate the influence of normal force direction variations caused by different motor arrangement modes on the dynamic response of the levitation system and vehicle operating behavior, the motion equation of the levitation module was established, and the influence of normal force on the transfer function and rated operating point of the levitation system was analyzed. Furthermore, a dynamic model of the maglev vehicle-bridge coupled system was constructed, which incorporated levitation control, magnetic saturation effect, electromagnetic force of motor, bridge flexibility, rail irregularity, and other factors. The influences of motor arrangement mode, slip frequency, and operating speed on the system response were studied. The results show that with the under-rail motor arrangement (abbreviated as under-rail mode) scheme, a larger normal force of the motor leads to a smaller rated levitation current, a higher relative permeability of the electromagnet core, higher sensitivity of magnetic induction intensity to coil current variation, and better controllability of the levitation system. Meanwhile, the levitation air gap fluctuation and vibration acceleration of the levitation module are significantly reduced. The effect becomes more prominent with a smaller slip frequency and a higher speed. Under the conditions of 8-Hz slip frequency and 140 km/h operating speed, the levitation air gap fluctuation and the vibration acceleration amplitude of the levitation module under the under-rail scheme are reduced by 59% and 49%, respectively, compared with those under the on-rail motor arrangement (abbreviated as on-rail mode) scheme. In addition, the under-rail scheme significantly reduces the rated current and levitation force of the electromagnet, and the difference is more significant with a smaller slip frequency and a lower speed. Under the conditions of 8-Hz slip frequency and 40 km/h speed, the rated current and levitation force are reduced by 43% and 67%, respectively. The results can provide a theoretical basis and technical guidance for the optimization of the running gear of medium-low-speed maglev and the selection of motor slip frequency.

To address the challenges of unclear distribution patterns and inaccurate calculation of surrounding rock load for shield tunnels within rock stratum environments, field monitoring tests were conducted based on the Jinxiu Tunnel of the Chengdu–Zigong Railway. The temporal variation pattern of water and soil load on the external segments during the construction process was analyzed, and the distribution patterns of tunnel surrounding rock loads in a mudstone environment were summarized. The applicability of commonly used calculation theories for rock stratum load was explored, and the calculation method of the surrounding rock load was improved by introducing a lateral gradient coefficient of the surrounding rock load. The results show that during the segment assembly phase, the external load distribution is uniform, with field test results indicating that the external load on each segment is within 60 kPa. Upon stabilization, the external load generally attenuates to approximately 80% of the peak load during the construction process. In the weathered mudstone strata of the tunnel site area, the distribution pattern of the surrounding rock load more closely resembles that of loose pressure distribution, and it is more appropriate to account for the influence of groundwater load by adopting the combined water-soil calculation method. Inversion of field test results suggests that the equivalent rock column height for tunnels in the weakly weathered mudstone strata of Chengdu is 1.13 times the tunnel diameter. After optimizing the calculation of lateral rock pressure in the rock layer, the root mean square error (RMSE) compared to field monitoring data is below 36.4 kPa, indicating a significant improvement in calculation accuracy.

In recent years, incidents of misoperation of relay protection devices caused by excitation inrush current have occurred multiple times when transformers are put into no-load operation by railway departments on site after modification, maintenance, or fault removal, which seriously affects power supply reliability. To ensure the safe and reliable operation of the railway power supply system, based on on-site investigations and comprehensive analysis of extensive literature, the hazards of excitation inrush current to electrical equipment and railway operation in the Chinese railway power supply system were systematically analyzed. Meanwhile, based on the electromagnetic equivalent model of transformers, a qualitative analysis of the formation causes of excitation inrush current was conducted, pointing out that residual magnetism and closing bias magnetism are the main factors affecting the magnitude of excitation inrush current. In addition, the current research status of Chinese and international scholars on suppressing excitation inrush current by coordinating residual magnetism and closing time, as well as adding external electrical components, was introduced, and the research progress of excitation inrush current waveform recognition technologies, such as the waveform feature method, time-frequency domain analysis method, and neural network method, was summarized. Finally, multi-scenario and full-characteristic transient simulation of excitation inrush current, the research and development and application of high-performance new materials and new structures for transformers, as well as waveform recognition technology based on new neural networks and its protection coordination measures were prospected, which were considered as key areas for future research.

To enable real-time monitoring, intelligent evaluation, and assisted control of the state of a magnetic levitation planar motor, a digital twin system for a magnetic levitation planar motor was constructed. The communication scheme based on EtherNet/IP was adopted between the magnetic levitation planar motor and its twin model; the real-time key state data of the magnetic levitation planar motor, such as mover position and control outputs, was acquired by means of a virtual system of communication module; the relevant information was sent to the real-time control system. The magnetic levitation planar motor employed an NI PXIe-8880 as the core control platform, performing high-real-time tasks including position-sensor signal acquisition, position computation, and execution of control algorithms. The digital twin system implemented a graphical user interface by using PySide6 and employed the OpenGL graphics library for three-dimensional visualization of the virtual model, enabling a physical mapping of the virtual system to the motor. Ultimately, by using C ++ computational libraries, the virtual system performed rapid virtual measurement of the motor’s magnetic field intensity, current magnitude, coil force, and motion states based on measurable real-time key parameters of the motor, thereby supporting real-time visualization monitoring, intelligent evaluation, control tracking, and other requirements for the motor. Research results show that the twin model’s virtual measurements of magnetic fields, currents, coil forces, and coil temperature, together with its motion state simulation, closely match those of the physical motor. The proposed digital twin system offers an accurate mapping of the magnetic levitation planar motor, and its measurement approach provides a feasible pathway for intelligent control and expanded applications of the motor.

To effectively suppress the airgap overshoot and collision issues during the zero-power control process of the hybrid permanent magnet electromagnetic levitation system, an adaptive super-twisting sliding mode zero-power controller based on current integral feedback was proposed, and the particle swarm optimization (PSO) algorithm was utilized for online tuning of the current integral coefficient. First, the mathematical model of the hybrid levitation system was established, and a zero-power controller was designed based on the current integral feedback strategy. On this basis, a fast non-singular terminal (FNST) sliding mode surface was constructed to accelerate convergence, and an adaptive dual-mode switching strategy was introduced into the super-twisting sliding mode control to form the zero-power controller, realizing rapid airgap adjustment and tracking under disturbances. To address the problems caused by the fixed integral coefficient in the controller, its impact on the dynamic performance of the system was analyzed. The PSO algorithm was utilized for online optimization of the integral coefficient, enabling it to adjust in real time according to the system state, effectively suppressing airgap overshoot, improving convergence speed, and thereby enhancing the overall control performance. Furthermore, to reduce the risk of track collision during the zero-power control process, airgap velocity information was introduced based on the traditional airgap threshold strategy to construct a “velocity + size” dual criterion, enhancing the collision prediction capability in the vertical direction. Simulation and experimental results indicate that the proposed strategy significantly reduces airgap overshoot and accelerates the convergence process. The overshoot is less than 0.30 mm, and the convergence time is shortened to 0.67 s; compared with the traditional threshold method, the proposed dual criterion advances the decision time by approximately 0.10 s, reduces the airgap overshoot by 1.70 mm, and can more effectively predict and prevent the occurrence of collisions.

The increase in speed of normal conducting magnetic levitation trains leads to an increased fluctuation range of the levitation air gap, making the motor’s magnetic field more likely to enter the saturation region, which aggravates the nonlinearity of the iron core’s magnetic reluctance and weakens the accuracy of the conventional magnetic circuit method parameter model. Therefore, an analytical parameter modeling method for normal conducting high-speed magnetic levitation motors considering the influence of magnetic saturation was proposed to improve the calculation accuracy of the parameter model for long-stator linear synchronous motors. First, an equivalent air gap model considering the variation in the iron core’s magnetic reluctance was constructed based on the magnetic circuit method. Second, combined with finite element magnetic field data, a dynamic characterization method for the magnetization effect based on differential permeability was adopted to obtain the relative permeability of the iron core material, realizing the quantitative description of the magnetic saturation degree. Finally, the dynamic differential permeability was combined with the equivalent air gap model to establish a motor parameter model capable of reflecting multiple factors such as iron core saturation, slotting effect, and air gap variation, and its accuracy was verified. The research results indicate that under the magnetic saturation state, the parameter model by the conventional magnetic circuit method exhibits significant distortion, with the relative errors of various inductance parameters generally exceeding 45%. After introducing the equivalent air gap and the magnetization characterization method based on differential permeability, the response capability of the model to the iron core’s magnetic reluctance and different saturation degrees is enhanced, and the parameter prediction accuracy is improved. By taking a suspension height of 5 mm as an example, the prediction accuracies of the stator self-inductance, the mutual inductance between stator and excitation, and the excitation self-inductance are improved by 39.43%, 30.14%, and 40.11%, respectively.

The rail potential and stray current in urban rail transit are mitigated by the active return traction power system (AR-TPS) by transferring the running rail current to the return cables through the return current node (RCN). To improve the mitigation performance of the AR-TPS, an optimization layout method of RCNs was proposed. First, a two-layer distributed parameter model and an RCN current transfer model were established to reveal the influence laws of RCN number and layout position on the current transfer capability. Then, based on engineering constraints and node functions, the number of RCNs was simplified to two, and the layout positions were optimized near the midpoint of the section with the optimal mitigation performance as the objective. Finally, a simulation verification was conducted based on the typical train operation curve. The results indicate that the outer RCN working in coordination with the active resistance converter is the primary path for transferring the return current to the return cables. The mitigation performance of the AR-TPS continuously improves as the RCN approaches the midpoint of the section. When the conventional traction power system is adopted, the maximum rail potential is 34.86 V; the maximum stray current is 2.89 A, and the total leakage charge is 134.00 C. When the AR-TPS with uniformly distributed RCNs before optimization is adopted, the above indicators are reduced to 14.84 V, 0.94 A, and 55.70 C, and the suppression rates are 57.42%, 67.47%, and 58.43%, respectively, compared with the conventional traction power system. When the AR-TPS optimized by the proposed method is adopted, the above indicators are further reduced to 8.66 V, 0.66 A, and 38.67 C, and the suppression rates are increased to 75.16%, 77.16%, and 71.14%.

To locate the metro stray current leakage points from the source, an equivalent resistance network model of the metro traction power supply system was first established. According to the characteristic of invariant topology of the equivalent resistance network before and after the rail insulation damage, the relationship between the rail-to-ground transition resistance and the branch voltages and currents of the traction substations and trains was derived based on Tellegen’s theorem. Secondly, by considering the spatiotemporal correspondence between train operations and the related electrical quantities of the traction substations and trains, a multi-time-section solving equation system for the rail-to-ground transition resistance was constructed. The locating interval was progressively subdivided by using the bisection method to increase the dimensionality of the equation system, and a genetic algorithm was combined to iteratively optimize the equation system to obtain the distribution of the rail-to-ground transition resistance along the line. Finally, the calculation results of the rail-to-ground transition resistance were compared with the identification threshold of stray current leakage points to realize the localization of stray current leakage points. Simulation verification was conducted based on actual metro line parameters and measured track inspection train data, and the applicability of the proposed localization method was analyzed from three aspects: stray current leakage point location, leakage severity, and leakage section length. The results show that under the three types of simulation scenarios of different leakage point locations, different leakage severities, and different leakage section lengths, the maximum localization errors are 9.375 m, 0 m, and 6.875 m, respectively, and the relative errors are all below 0.4%. It can be seen that the localization results of the proposed localization method are basically consistent with the preset locations. In summary, the method can realize the localization of the section where the stray current leakage points are located and can provide a theoretical basis for stray current mitigation in scenarios such as rail fastener damage and localized insulation degradation.

To analyze the influence of metro stray current on the cable metal sheath-to-ground potential, by considering its dual intrusion paths through the metal sheath and the ground, electrical quantity analysis models for the cable metal sheath under double-end grounding and cross-bonded grounding methods were respectively established. Based on the superposition theorem, the induced voltage and the voltage drop generated by stray current were superposed, and a calculation method for the sheath-to-ground potential at any position of the cable metal sheath under the two grounding methods was derived. The calculated values were verified by the measured current of a 110 kV cable under the cross-bonded grounding method, and the calculation results of the sheath-to-ground potential under the two grounding methods were verified based on the PSCAD simulation platform. On this basis, the proposed models were adopted to analyze the influence of stray current amplitude, frequency, and soil resistivity on the metal sheath-to-ground potential. The research results indicate that the trend of the calculated value of the cable metal sheath current is basically consistent with that of the measured value, with a relative error of 3.08%; the calculation error of the sheath-to-ground potential at the cross-bonded joint is 0.86%, and the calculation error of the sheath-to-ground potential at the midpoint position of the metal sheath under the double-end grounding method is 1.13%; under the double-end grounding method, the cable metal sheath-to-ground potential always remains within the safety limit, and when the stray current increases from 0 A to 300 A, the sheath-to-ground potential at the midpoint position of the metal sheath increases from 1.10 V to 30.25 V; under the cross-bonded grounding method, when the stray current exceeds 162 A, the sheath-to-ground potential at the cross-bonded joint exceeds the 50 V limit; the stray current frequency has no obvious influence on the amplitude of the cable metal sheath-to-ground potential under the two grounding methods but only makes the peak appear more frequently; the increase of soil resistivity raises the cable metal sheath-to-ground potential, and the raising amplitude under the double-end grounding method is more significant than that under the cross-bonded grounding method.

The medium-speed maglev transportation system has broad application prospects in the field of intercity and urban rail transit. However, the exact calculation problem of the transport capacity of maglev lines cannot be effectively solved by using the calculation methods of traditional wheel-rail systems. According to the actual needs of operation organizations, based on the technical characteristics of the medium-speed maglev system and integrating the constraint requirements of operation control and safety protection, the calculation method of transport capacity of medium-speed maglev lines was studied. Firstly, through an in-depth analysis of the rigid protection constraint of “one block partition for one running train” followed by medium-speed maglev trains, as well as the stop-point stepping control mechanism and quasi-moving block tracking protection mode adopted by the operation control system, the adaptability between the blocking time theory and the technical characteristics of the medium-speed maglev operation control system was demonstrated. On this basis, taking “blocking time theory and identification of the most unfavorable partition handover application point” as the core research paradigm, quantitative models of partition blocking time under four types of typical full-process operation scenarios, including interval operation, station arrival stop, platform departure, and station rear turn-back, were constructed, and an algorithm for solving transport capacity of lines based on time window compression was proposed. Finally, a specific line case was selected, and the validity of the output results of the proposed calculation models and algorithms was verified through a dual verification system combining simulation experiments and limit pressure tests. Simulation results indicate that the theoretical limit value of the transport capacity of the target line is 11 trains/h. If an extra running line is added, the running process of the following train is inevitably interfered by the preceding train. The proposed models and algorithms possess good calculation accuracy and engineering applicability.

Maglev transportation systems have become an important development direction for future rail transit by virtue of their advantages such as non-contact operation, high speed, and low noise; however, their complex operating environments, high safety requirements, and high operation and maintenance costs put forward higher requirements for the autonomous perception, decision-making, and control capabilities of the systems. In this context, critical embodied intelligence, as an important paradigm of next-generation artificial intelligence, emphasizes the real-time interaction and continuous learning between intelligent agents (such as onboard intelligent control agents, trackside sensing agents, and robots) and the physical environment, promotes the deep integration of perception, decision-making, and control, and provides a new technical pathway for the intelligent development of maglev transportation systems. In specific applications, critical embodied intelligence firstly empowers operational safety and the precise control of levitation and guidance. By fusing multimodal sensor data to dynamically construct the vehicle-track-environment situation, it achieves millimeter-level perception, state prediction, and the autonomous generation of levitation-guidance and traction-braking strategies, ensuring stability and comfort under extreme working conditions; secondly, in the field of autonomous infrastructure inspection and intelligent maintenance, robots or unmanned aerial vehicles driven by embodied intelligence can replace manual labor to execute high-risk tasks, identify defects through interactive detection, predict component lifespans based on experience, and optimize maintenance cycles; finally, in terms of global scheduling and collaborative optimization, multiple embodied intelligent agents constitute a distributed system, and by sharing local perception information, they dynamically negotiate and adjust timetables to achieve high-density, collaborative, and energy-efficiency optimized operations of train groups. In summary, critical embodied intelligence is driving the transformation of maglev transportation systems from “automated execution” to “autonomous evolution”. While enhancing safety, operational efficiency, and system resilience, it helps to reduce full life-cycle costs and is a key pathway to constructing the next-generation adaptive and evolvable intelligent rail transit. Future research should focus on the high-reliability validation of intelligent agents, multi-agent collaboration mechanisms, and robustness enhancement in complex environments to accelerate their engineering application process.

To enhance the accuracy of document-level event causality identification, the implicit knowledge within large language models was first leveraged to filter out events related to the target event from the document, constructing a candidate event set. Next, the candidate event set was organized into a fully connected event relationship graph, which was then subjected to conditional constraints. These constraints simplified the fully connected graph into a constrained event relationship graph, reducing noise propagation from irrelevant events. Finally, a self-attention mechanism was used to compute the influence of any node on other nodes in the graph network, and the model was trained with a binary classification loss function incorporating focal loss, further mitigating false positives in causality identification. Experimental results show that in the causality identification tasks, the model achieves a precision of 77.3% for intra-sentence event pair causality identification on the Causal-TimeBank dataset. On the EventStoryLine dataset, it achieves a precision of 75.2% for intra-sentence event pair causality identification, an F1-score of 60.6% for inter-sentence event pair identification, and an F1-score of 59.6% for document-level event pair identification.

To address the relatively limited research on the coupled dynamic interaction between superconducting electrodynamic suspension trains and continuous beam bridges, a coupled dynamic model of a superconducting electrodynamic suspension train and a two-span continuous beam bridge was established. The effects of bridge span and train marshalling on the dynamic response of the continuous beam were analyzed, and the parameters of the continuous beam bridge were selected based on the dynamic amplification factor. On this basis, the coupled vibration responses of the train-bridge system were calculated. The results indicate that the influence of train marshalling on the dynamic response of the bridge depends on the ratio of the bridge span to the vehicle spacing. When the ratio approaches 1.5, a significant vibration suppression effect of the bridge is observed. When the ratio is higher than 1.5, although primary resonance occurs, the superharmonic resonance response is small and insensitive to the number of train marshalling. When the ratio is lower than 1.5, the resonance energy accumulates significantly with the increase in train marshalling, resulting in poor train-bridge matching. Parametric analysis based on the limit of the dynamic amplification factor shows that the two-span continuous beam is slightly superior to a simply supported beam with the same span in terms of superharmonic resonance control. Within the speed range of 0–600 km/h, the continuous beam allows for a lower limit of the fundamental frequency, indicating that structural stiffness requirements can be reduced while satisfying dynamic safety, thereby improving economic efficiency. In the coupled train-bridge vibration analysis under the selected bridge parameters, the Sperling ride index of all vehicles consistently remains within the “excellent” limit. Notably, because the intermediate vehicles satisfy the vibration suppression matching conditions, the change in dynamic response at the resonance speed is minimal.

To study the influence of guideway irregularity on ride comfort of 600 km/h high-speed maglev trains and to address the limitations of conventional dynamic models, which lack detailed descriptions of human biological structures and thus fail to reveal the complex interactions between vehicle body motion and resonance of human internal organs, an integrated full-chain “vehicle-guideway-human” coupled dynamic simulation method was proposed. First, a system simulation framework was established based on multibody dynamics and finite element theory, incorporating spatial flexible guideway beams, active levitation/guidance control algorithms, and multibody vehicle dynamics. Second, a 45 degrees of freedom (DOF) three-dimensional seated human biomechanical model was introduced to construct a full-system coupled dynamic model, thereby addressing the distortion at the human perception end in the vibration transmission path. Then, system modal analysis was employed to reveal the coupling mechanism between vehicle body motion and the resonance of human internal organs and skeletal system. Finally, the model was validated using measured data from the Shanghai high-speed maglev demonstration line. The results indicate that according to the standard (GB/T 5599—2019), the measured vertical and lateral ride quality indices are 2.33 (excellent) and 2.61 (good), respectively, while the simulated values are 2.28 and 2.56, with relative errors of only 2.15% and 1.92%, respectively. Furthermore, for the seat surface vibration directly perceived by the human body, the measured peak vertical and lateral accelerations are 0.915 m/s² and 1.115 m/s², respectively, with corresponding simulation errors controlled within 5.00% (0.76% and 2.91%, respectively). In the frequency domain, the model not only accurately reproduces the car body’s rigid body mode at approximately 1.5 Hz but also precisely captures the coupled resonance peaks in the 4.0–6.0 Hz band dominated by human biomechanical characteristics, thereby verifying the effectiveness of the model in refined ride comfort prediction.

When maglev vehicles operate at an ultra-high speed, boundary conditions such as track irregularity and air resistance significantly affect the operational safety and stability of the vehicles. Based on the polymorphic coupled dynamic simulation test platform for rail transit, a dynamic model of an ultra-high-speed maglev model vehicle system was established, which considered conditions including superconducting pinning suspension and guiding force characteristics, air resistance, and track irregularity. The traction, coasting, and braking conditions achieving a maximum speed of 1500 km/h on a 1.6 km test line were simulated. Based on the dynamic model, the vibration responses of the model vehicle system operating under different multiples of track irregularity amplitude, speeds, and limit clearances were simulated and analyzed. The results indicate that under a low-vacuum environment, when the track irregularity amplitude is 0.15 mm, and the maximum speed is 1,500 km/h, the mover exhibits a left-and-right swing vibration form during operation, and the maximum vertical displacement of the Dewar reaches 4.88 mm. As the operating speed of the model vehicle system increases, the system vibration strengthens, and the amplitudes of various dynamic indicators show an upward trend; an increase in the lateral limit clearance is beneficial to weaken the lateral vibration of the model vehicle system, while an increase in the vertical limit clearance intensifies the vertical vibration of the model vehicle system. The research results can provide a theoretical reference for the design of the ultra-high-speed maglev dynamic simulation test platform.

As the seismic design philosophy of bridges gradually shifts from performance-based to resilience-oriented, the current research focus lies not only in ensuring structural safety under the action of earthquakes, but also in paying more attention to the preservation and recovery capacities of post-earthquake traffic function. Railway bridges serve as critical nodes in transportation networks, and their post-earthquake traffic capacity directly influences the operational efficiency of the lines and the recovery process of earthquake-stricken areas. Based on this, a shear-type viscoelastic damper was proposed to decrease track damage risk by controlling the relative transverse displacement of main beams, thereby enhancing the bridge’s post-earthquake traffic function. By taking a typical five-span railway simply-supported bridge as a case study, a comparative analysis was conducted on the traffic function vulnerability, post-earthquake function recovery capacity, and seismic resilience in the three constraint conditions of no constraint (NC), steel restrainer (SR) only, and SR combined with the shear-type viscoelastic damper (DP). The analytical results demonstrate that proposing the concept of a “component recovery weight coefficient” provides a quantitative index for determining the sequence of component repairs. Additionally, the proposed shear-type viscoelastic damper can significantly control the relative transverse displacement of main beams at beam ends, effectively reducing track alignment irregularity under the strong action of earthquakes and consequently enhancing the bridge’s post-earthquake traffic function. The addition of the viscoelastic damper to SR can notably shorten the post-earthquake repair time. In particular, under higher ground motion intensities, such as peak ground acceleration (PGA) of 0.8g, the repair time can be reduced by up to 9.1 days compared to the NC system. Furthermore, the DP configuration demonstrates significantly better post-earthquake residual traffic function and seismic resilience indices than the SR and NC configurations at various PGA levels. For instance, under PGA=0.4g, the post-earthquake residual traffic function improves by 20.0% and 56.9%, and seismic resilience increases by 13.1% and 34.4% respectively, confirming the remarkable effectiveness of this device in enhancing both post-earthquake traffic function and seismic resilience of bridges.

To improve the detection accuracy of the mover position of a primary segmented winding linear motor and reduce the direct current (DC) bias and harmonic interference introduced into the output signals of magnetoresistive sensors by harmonic magnetic fields, temperature variations, and other factors, a position detection method based on a frequency-adaptive cascaded delayed signal filter was investigated. First, a frequency-adaptive cascaded delayed signal filter was designed to suppress DC bias and multi-order harmonic disturbances by introducing signal delay and cascading the filters, thereby addressing the limitations of traditional methods, which required prior knowledge of harmonic orders and showed poor filtering performance for interferences near the fundamental frequency. Second, combined with type-Ⅲ phase-locked loop technology, quadrature phase locking was performed on the filtered signals to achieve synchronous extraction of the motor’s magnetic pole angle and mover position information. Finally, an experimental platform for the primary segmented winding linear motor was established to verify the filtering performance and position detection accuracy of the proposed method. The research results indicate that the proposed filtering method can effectively suppress harmonic voltages near the fundamental frequency and DC bias without relying on a motor model; under complex harmonic interference conditions, compared with the detection scheme combining traditional filters and phase-locked loops, it reduces the estimation error of the mover position of the linear motor by 68.75%.

Electrified railways rely heavily on public power grids dominated by fossil fuels, and actively carrying out the development and utilization of renewable energy in rail transit is one of the important measures to achieve China’s “carbon peaking and carbon neutrality” goals. To extensively and comprehensively use green power to construct electrified railways with zero-carbon emission, a technical scheme of zero-carbon feed-through power supply and its zero-carbon operation control strategy were proposed. First, the basic methods of new energy connection in electrified railways were analyzed, and the connection points and energy flow paths of renewable energy in the traction power supply system were clarified. On this basis, a technical framework for green power utilization based on feed-through power supply was constructed, and the natural flow of train traction and regenerative power was realized by using the feed-through traction network, thereby reducing the capacities and investment of green power and energy storage equipment. Second, a three-component power balance control strategy covering green power, traction, and energy storage was proposed. Green power was controlled according to maximum power point tracking to maximize on-site power generation; the energy storage devices in the traction substation were controlled for charging and discharging according to the active power specified in the green power purchase/sale agreement with the power grid, thereby achieving zero-carbon operation. Finally, by taking an actual railway line as an example, the effectiveness and economy of the proposed scheme were verified. The results indicate that the zero-carbon feed-through power supply system does not obtain fossil power from the power grid and causes no impact on the power grid; when the active power exchanged with the power grid is zero, the negative-sequence power and through power are also zero. The feed-through power supply traction network eliminates electrical phase separation, and the regenerative braking energy and green power are fully utilized. In the verified case, the total regenerative braking energy of the traction substation accounts for only 0.6% of the traction energy and is all effectively utilized, with a photovoltaic curtailment rate of less than 10%. Green power and energy storage adopt local independent control, which significantly reduces the complexity of communication and power flow control. Based on capacity configuration and economic analysis using actual data of heavy-haul railways, the zero-carbon power supply requirements are met when lithium iron phosphate batteries with a charge/discharge rate of 0.5 C and an energy storage configuration capacity of 145 MW•h are adopted. According to the annual average irradiance and the irradiance under extreme weather conditions, the installed photovoltaic capacities of the entire line need to be configured as 45 MWp and 83 MWp, respectively, with cost recovery periods of about 5.9 years and 6.8 years, respectively.

Given the complex construction processes and significant procedural variations in railway tunnels, a model for accounting carbon emissions covering the engineering materialization phase and the operation and maintenance phase was established to accurately assess carbon emission characteristics throughout the whole life cycle of railway tunnel engineering and support specialized analysis and emission reduction strategies. Combined with the unit rate method by procedure and the carbon factor method by material, quantitative accounting and variance analysis of carbon emissions were conducted in a case study. Furthermore, Pareto analysis was employed to identify high-emission sectors and key influencing factors, realizing the decomposition and hierarchical management of carbon emissions. The results indicate that the total carbon emissions during the whole life cycle of the case tunnel engineering are 68.107 5 × 10⁴ tCO₂e, with the engineering materialization phase generating 59.404 0 × 10⁴ tCO₂e (accounting for 87.2%) and the operation and maintenance phase generating 8.703 5 × 10⁴ tCO₂e (accounting for 12.8%). During the engineering materialization phase, material production and on-site construction processes contribute up to 95.76% of the carbon emissions, among which the carbon emission intensity of drill-and-blast section construction is 13 843 tCO₂e/km, and that of shield section construction is 39.8% of the former. During the operation and maintenance phase, the maintenance of ventilation systems, waterproofing and drainage systems, and reinforced concrete precast pipes accounts for 73.54% of the carbon emissions. In the whole life cycle, Class A carbon-emitting materials include ordinary cement 42.5 grade (high-performance concrete), ordinary cement 42.5 grade, and ribbed steel bars; Class A carbon-emitting machinery includes axial flow fans, rail-type internal combustion locomotives, and dump trucks; Class A carbon-emitting processes include the lining of shield section, the support of drill-and-blast section, and the support of shield section.

To improve the torque transmission control accuracy of the shift clutch in hydraulic mechanical transmission (HMT) and enhance its shift quality, an adaptive sliding mode control method based on linear quadratic optimization was proposed. Firstly, the shift dynamics model of HMT and the numerical model of the clutch were constructed. Secondly, the optimal torque transmission trajectory of the shift clutch was solved under the target functional based on the linear quadratic optimization model. Combined with the dynamic friction coefficient model, the trajectory variable was converted into the expected oil pressure trajectory considering the time-varying effect of the lubricating oil film and the dynamic contact characteristics of the friction interface. Finally, the adaptive sliding mode control algorithm was used to track and control the expected oil pressure trajectory. Simulation results show that compared with the direct application of the linear quadratic control scheme, the proposed algorithm effectively improves the torque transmission control accuracy of the shift clutch, shortens the shift time by 13.8%, reduces the sliding friction work by 11.2%, and decreases the maximum shock by 39.1%. Experiments further confirm that the algorithm not only effectively improves the torque transmission control accuracy of the shift clutch but also improves the shift quality of HMT. The research results can provide a reference for the formulation of shift control strategies in the engineering application of HMT devices.

To clarify the distribution and migration characteristics of volatile organic compounds (VOCs) in organic pollution sites, 120 soil and 48 soil gas sampling holes were arranged at a site where a chemical plant was once located, and 97 pairs of soil/soil gas samples were collected from 14 holes in the heavily polluted area. The pollutant concentrations in the samples were determined through laboratory analysis. The distribution characteristics of the pollutants were analyzed using Sufer software, and the distribution and migration characteristics of trichloroethylene (TCE) were interpreted in combination with the stratigraphic lithology. The applicability of two models for predicting the content of soil gas VOCs was analyzed with predicted and measured values. The results show that as the hole depth increases, the TCE concentration in the soil in the heavily polluted area decreases with an exceedance rate of 50.4%. The maximum value is in the clayey silt layer (1610 mg/kg), exceeding the standard by 2300 times. The TCE concentration in soil gas first increases and then decreases, with the maximum value occurring in the sandy soil layer (643 mg/m³), exceeding the standard by 546 times with an exceedance rate of 97.9%. The TCE concentration in soil and soil gas outside the heavily polluted area first increases and then decreases with soil depth, and the exceedance rate is 6.6% and 54.9%, respectively. The horizontal migration of TCE is weaker than its vertical migration. The area that exceeds the standard first increases and then decreases with soil depth, and the average exceedance area is 7.3 × 10³ m². TCE in soil gas spreads rapidly from the heavily polluted area to the surrounding areas. The exceedance area covers the entire chemical plant area and pollutes the area outside the chemical plant. The average exceedance area is 2.4 × 10⁴ m². Based on the soil TCE concentration, both the linear model and the dual equilibrium desorption (DED) model can predict the soil gas TCE concentration. The proportion of data points with a prediction error of one order of magnitude or less for the two models is 78.6% and 71.4% for the fill and sandy soil, respectively. Regression analysis shows that the DED model predicts soil gas TCE concentrations more close to the actual values for fill (irreversible adsorption degree f = 0.1), silty clay (f = 1.0), and clayey silt (f = 0), while the linear model and DED model yield relatively close predictions of soil gas TCE concentrations for sandy soil. When a pollution assessment and secondary development of similar sites are conducted, the concentrations of soil gas pollutants should be monitored or predicted to avoid underestimating the degree and scope of site pollution.

To promote energy conservation and emission reduction, as well as green and low-carbon development of electrified railways, two technical schemes for a photovoltaic-integrated energy storage-based co-phase power supply system were first proposed. Then, the operating conditions of the system were analyzed, and the negative sequence compensation principle was formulated. On this basis, according to the photovoltaic power generation output and lithium battery state of charge (SOC), a two-layer cooperative control strategy was constructed with the control objectives of achieving load peak shaving and valley filling and efficient energy utilization. The upper layer was responsible for energy management and negative sequence control, while the lower layer controlled the converter operation in real time. Finally, through case analysis, the curtailment of photovoltaic generation, charging and discharging, and negative sequence compensation were controlled under comprehensive consideration of multi-dimensional factors, such as load magnitude under traction and regeneration conditions, solar irradiance, and lithium battery charging and discharging. The results indicate that the system exhibits good adaptability and stability under different operating conditions, and the correctness and effectiveness of the proposed control strategy are verified. The photovoltaic integration scheme eliminates 50% of electrical phase separations, realizes controllable negative sequence, promotes multi-energy integration and complementarity, facilitates local and nearby consumption of photovoltaics, and mitigates severe fluctuations of traction load.

To address the severe interference problem caused by non-orthogonal multiple access (NOMA) and device-to-device (D2D) technologies in enhancing the capacity of heterogeneous cellular networks, an efficient resource allocation algorithm was proposed to improve the system and rate. Firstly, a reconfigurable intelligent surface (RIS)-assisted heterogeneous cellular NOMA-D2D communication network model was constructed. Under the constraints of signal-to-noise ratio (SNR) of users, transmission power, and unit membrane of RIS phase shift, an optimization problem aiming to maximize the number of D2D users and rate was established. However, this problem was a mixed integer nonlinear problem and was difficult to solve directly. Therefore, it was decomposed into three sub-problems: D2D user-cellular user (CU) matching, D2D user power control, and RIS reflection phase shift optimization. Based on this, the D2D cluster channel allocation was completed by using the bipartite graph maximum matching algorithm, and a deep reinforcement learning algorithm based on a deep deterministic gradient strategy (DDPG) was proposed to jointly optimize the D2D transmission power and RIS phase shift matrix. Simulation results show that under the same conditions, the average value of the D2D link and rate of the proposed algorithm increases by 1.96%, 10.64%, and 14.29%, respectively, compared with that of the game algorithm, random phase shift algorithm, and RIS-assisted-free algorithm, verifying its effectiveness in interference suppression and spectral efficiency improvement.

To improve the anti-disturbance capability of the electromagnetic levitation system, an adaptive nonsingular terminal sliding mode control based on disturbance upper bound compensation (ANTSMC-DUBC) was proposed. The strategy used nonsingular terminal sliding mode control based on disturbance upper bound compensation (NTSMC-DUBC) to speed up the convergence of the system state and avoid singularity. The disturbance compensation term in the reaching control law can suppress the lumped disturbance, so that a smaller switching gain can be selected to reduce chattering. A switching gain that can adaptively change with the state of the sliding mode function was designed to ensure the dynamic performance of the system while improving the steady state performance and the efficiency of disturbance compensation. The theoretical derivation proved that the designed levitation controller satisfied the Lyapunov stability criterion. The experimental results show that the proposed ANTSMC-DUBC controller exhibits good steady state and dynamic performance in signal tracking, anti-disturbance, and load variation tests, and demonstrates excellent anti-disturbance when facing internal and external disturbances in the system. Compared with that of NTSMC, the gap fluctuation of ANTSMC-DUBC is less than 0.21 mm under the equivalent external disturbance, and the system root mean square error and time-weighted absolute error are reduced by 56.26% and 57.57%, respectively. The maximum gap fluctuation is 0.22 mm with no steady state error when the 1.5 kg load variation is performed.

High-precision control of electromagnetic thrust bearings can enhance the coordination and stability of sorting robotic arms or auxiliary joints in collaborative robots. Flux density feedback control under cascaded control systems is recognized as an effective solution for high-frequency applications; however, there are currently few suitable miniature Hall sensors capable of accurately capturing the real-time magnetic flux density of the air gap. To address the problem of insufficient accuracy in traditional flux density estimation under high-frequency operating conditions, first, a rational approximation of an equivalent reluctance model considering eddy current, magnetic leakage, and edge effects was performed. Secondly, based on the coupled stiffness and an eddy current compensation model incorporating effective inductance, a flux density observer using measurable displacement and current as joint input signals was designed. In the outer loop, a PID controller considering dynamic stiffness was designed to compensate for flux density hysteresis, and the internal flux density control loop was reconstructed. Finally, a cascaded displacement-flux density control loop for the electromagnetic thrust bearing was eXstablished and validated. The results indicate that compared to the current control strategy, the flux density feedback control method can increase the gain margin of the electromagnetic thrust bearing system to 35 dB, maintain the phase margin above 50°, and extend the control bandwidth to 400 Hz. When the current control becomes unstable, the flux density feedback control can suppress the overshoot to below 41.2%, and it demonstrates a smaller overshoot and a faster settling speed in step responses under different parameters and square-wave tracking tests.

Quasi-static tests were conducted on three types of concrete-filled square steel tube (CFSST) column-H-shaped steel beam joints with external stiffening rings featuring different structures to investigate the seismic performance of prefabricated CFSST column—H-shaped steel beam joints with external stiffening rings. The bearing capacity, failure processes and modes, stress distribution in joint zones, and various seismic performance indicators were studied. The experimental results show that joint failures all occur near the beam ends, characterized by buckling and fracture failure of the beam sections outside the diaphragm. The hysteresis curves of the joints all exhibit a “spindle shape” with significant pinching effects. The loading process is essentially symmetric in the positive and negative directions, with a sliding segment of zero rotational stiffness observed in the curves. The ductility coefficient of joints ranges from 2.55 to 4.20, and the ultimate angle of rotation is between 0.032 rad and 0.062 rad, both exceeding the requirements specified in seismic codes. Compared to the integral external stiffening rings, the separate external stiffening rings exhibit increases of 60.7% in ductility and 209.0% in cumulative energy dissipation. Meanwhile, the cantilever energy-dissipating external stiffening rings show improvements of 38.1% in bearing capacity, 64.7% in ductility, and 400.3% in energy dissipation capacity over the integral connection. This indicates that the structural configuration of “separate multi-layer force transfer” and “dual-stage energy dissipation via cantilever segments and energy-dissipating cover plates” can effectively optimize the seismic performance of joints. There is sound agreement between the simulated and experimental hysteresis curves and failure modes, validating the numerical analysis reliability.

High-temperature active magnetic bearing technology is a key technology to replace traditional bearings and achieve stable operation under high-temperature and high-speed conditions. Its design complexity is significantly higher than that of ambient-temperature magnetic bearings. Based on relevant Chinese and international research literature, the research progress of high-temperature active magnetic bearings in four aspects, including material selection, mechanical system manufacturing processes and fail-safe mechanisms, high-temperature displacement sensor design, and rotor system modeling and dynamic characteristic analysis, was systematically reviewed. Furthermore, in-depth research in directions such as multi-physics coupled high-fidelity modeling, active vibration control strategies, multi-scenario application adaptability, and material-control-structure co-optimization was proposed as a future focus, to improve the reliability and engineering applicability of high-temperature magnetic bearing systems, and theoretical basis and technical support were provided for their stable operation in extreme environments.

To study the noise reduction performance of 3D printed special-shaped noise barrier for high-speed railways, the geometric models of the noise barrier were established by using three-dimensional modeling software, and the noise reduction model of a special-shaped noise barrier for high-speed railways under three sound source modes was established. Based on the acoustic indirect boundary element method, the optimal design parameters of a special-shaped noise barrier were obtained by comparing the noise reduction effect, sound field distribution, spectrum characters, and insertion loss characteristics of the special-shaped noise barrier under different wave distances, wave heights, and barrier heights. The effects of different barrier-line center distances and train speeds on the noise reduction effect of a special-shaped noise barrier were compared and analyzed. The results show that the special-shaped noise barrier has a significant noise reduction advantage for the middle and far field points, the field points in the sound shadow area, and the middle and high frequency noise above 630 Hz. Compared with that of the vertical noise barrier, the additional noise reduction gain of the special-shaped noise barrier can be obtained when the optimized wave distance is in the range of 3.2–4.0 m, and the additional noise reduction effect can reach 1.7 dB (A). In the case of a certain wave distance, with the increase of wave height, the noise reduction effect of the special-shaped noise barrier is enhanced, and the maximum can reach 15–17 dB (A). The additional insertion loss of the special-shaped noise barrier is 1.8 dB (A) when the wave distance is 4 m, and the wave height is 600 mm. When the special-shaped noise barrier height increases by 1 m, the sound pressure level of the four standard field points decreases by 1.6–4.8 dB (A), which mainly acts on the range of 5–10 m near the barrier area and the high frequency cut-off area in space. The additional noise reduction is attenuated from the area to both sides. In the range of 3–4 m, the barrier-line center distance has little effect on the noise reduction level of the special-shaped noise barrier, and the recommended value of the parameter is 3.4–3.6 m. As the train speed increases, the insertion loss of the special-shaped noise barrier decreases. When the train speed is increased from 300 km/h to 340 km/h, the insertion loss of the field point under different working conditions is reduced by 0.17–0.34 dB (A) and 0.55–0.63 dB (A), respectively.

Aiming at the problem of poor controllability of deformation recovery in the process of transverse elliptic deformation of shield tunnel treated by traditional stratum grouting, the experimental study on transverse elliptic deformation of shield tunnel treated by capsular bag grouting was carried out innovatively. Two different capsular bag layout schemes were adopted in the experiment. The analysis of the test results shows that the tunnel has a vertical elliptical deformation near the grouting point, and the additional earth pressure, tunnel diameter and deflection deformation near the grouting point change the most, showing a gradual decreasing trend along the two ends of the tunnel. Under the same amount of grouting, vertical grouting can better control the transverse elliptic deformation of the existing tunnel, and the side bottom grouting can realize the recovery effect of the transverse elliptic deformation of the tunnel while uplifting the tunnel and effectively reducing the settlement of the tunnel during operation. When grouting at the bottom of the tunnel side, due to the influence of the gravity of the built tunnel, the deformation of the tunnel caused by grouting is lower than that caused by vertical grouting during the expansion process of the bag. Therefore, it is suggested to increase the grouting amount appropriately in the grouting process to achieve the expected recovery effect of transverse ellipse deformation. After grouting, the capsular bag presents a cylindrical shape with wide middle and narrow sides. The capsular bag grouting method can effectively limit the slurry diffusion path, and the slurry is squeezed and diffused in the capsular bag, so that the local pressure of the tunnel increases rapidly, and the recovery effect of transverse ellipse deformation is remarkable. Vertical grouting at the side of the tunnel has a significant effect on the recovery of transverse ellipse deformation, but excessive grouting pressure and other reasons can easily induce problems such as dislocation of shield tunnel segments. It is suggested that when the transverse ellipse deformation of the shield tunnel exceeds the limit, the grouting point should be arranged at the bottom of the tunnel side, that is, about 30°～60°away from both sides of the tunnel.

Beam-end integration devices in long-span high-speed railway bridges have complex structures and are prone to generating peak structural track irregularities, which directly affect train running stability. However, targeted monitoring and management criteria for such devices are currently lacking. In this study, monitoring management values for beam-end integration devices are investigated. Monitoring data collected in recent years are analyzed, and a finite element model of the beam-end integration device is established. Based on static irregularity standards, simulation analyses are conducted to propose monitoring management values for beam-end longitudinal displacement, lateral displacement, deflection angle, and fixed steel sleeper lifting and unsupported sleeper. For an operational speed of 250 km/h, the proposed Class Ⅰ monitoring management thresholds are as follows: beam-end longitudinal compression of 160 mm, lateral displacement of 7 mm, deflection angle of 3×10⁻³ rad, fixed steel sleeper lifting of 3 mm, and unsupported sleeper of 2 mm. The results show that the proposed monitoring management values can effectively identify abnormal conditions of the device. Longitudinal compression at the beam end significantly affects track profile and gauge irregularities; lateral displacement primarily influences gauge irregularity; both the fixed steel sleeper unsupported section and lifting impact track profile irregularity. The proposed monitoring management values provide a reference for the operation and maintenance of long-span high-speed railway bridges.

To address the design challenges of heat dissipation and energy efficiency caused by air friction loss in the air gap of high-speed permanent magnet motorized spindles, the formation mechanism of windage loss and the evolution laws of vortex flow under the coupled effect of stator slots and axial ventilation cooling were revealed. First, an ideal air-gap model with smooth walls and a realistic air-gap model containing 18 stator slots were established, respectively. Second, the independent impact of stator slots was quantitatively evaluated by comparing the energy dissipation differences between the two air-gap models under the condition of no axial ventilation. Finally, the nonlinear regulation effect of ventilation intensity on the internal flow field structure and energy dissipation characteristics of the air gap was systematically evaluated by applying axial cooling airflows at different velocities. The results indicate: 1) stator slots are the decisive factor leading to the surge of windage loss. Compared with the ideal air gap with smooth walls, the increase in additional loss caused by stator slots is nearly 80%. 2) In the air gap containing stator slots, the regulation of loss by axial ventilation exhibits significant non-monotonic and multi-stage characteristics: After weak axial ventilation is introduced, the loss decreases to the minimum at 2.00 m/s, with a decrease of more than 19%; when the flow velocity enters the critical range of 6.00–10.00 m/s, the flow field instability leads to a sharp surge in energy dissipation by over 26%; when the flow velocity exceeds 10.00 m/s, the vortex suppression effect dominates the flow field to restore stability, and the energy dissipation shows a steady and monotonic increasing trend after a sudden drop.

To enhance the durability of structural members while ensuring ductility, a new glass fiber-reinforced polymer (GFRP)-steel hybrid reinforced (HRBS) column with a built-in spiral stirrup core column was proposed. Four HRBS columns were subjected to quasi-static loading tests, among which two HRBS columns underwent composite salt dry-wet cycling tests. The failure process, ultimate failure mode, hysteresis curves, skeleton curves, energy dissipation capacity, performance degradation, and residual displacement of the HRBS columns before and after composite salt dry-wet cycling were investigated. The results indicate that HRBS columns demonstrate good seismic performance both before and after composite salt dry-wet cycling, and all specimens exhibit flexural failure. Under conventional environments, the yield load and peak load of HRBS columns increase by 25.77% and 28.68%, respectively, with an increase in the core column diameter. In a composite salt environment, increasing the core column diameter improves the load-bearing capacity, displacement ductility factor, strength degradation factor, energy dissipation capacity, overall stiffness, and self-centering ability of the HRBS columns. After composite salt erosion, the yield load and peak load of specimens with a 200 mm core column diameter decrease by 17.65% and 15.77%, respectively, while the energy dissipation capacity and displacement ductility factor increase by 14.41% and 32.61%, respectively. Therefore, by designing an appropriate core column diameter, HRBS columns ensure good durability and overall seismic performance in both conventional and corrosive environments.

The air friction loss of a motor rotor increases rapidly with the increase in rotational speed. Especially for a high-speed motor supported by magnetic bearings, since the air-gap structure is complex, mastering its air friction loss characteristics is particularly important. A 2 MW、15 000 r/min high-speed permanent magnet motor with magnetic bearings was taken as the research object, and the entire air domain inside the motor was modeled. Firstly, based on the fine simulation technology of computational fluid dynamics (CFD), the distribution characteristics of air friction loss on the rotor surface were obtained. Then, the effects of rotational speed, ventilation wind speed, surface roughness height, air gap structure, and rotor eccentricity on the air friction loss characteristics of the rotor were analyzed in detail. Finally, a dual-motor drag test was conducted, and the air friction loss of the rotor was obtained by the loss separation method. The research results indicate that the air friction loss of the rotor is mainly concentrated in the air gap of the motor. At a rotational speed of 15 000 r/min and a ventilation wind speed of 2.5 m/s, it accounts for approximately 70.1% of the total air friction loss. Meanwhile, the air friction loss at the thrust collar cannot be ignored, accounting for about 23.9% of the total air friction loss under the non-ventilation condition. The synergistic thermal effect of cooling enhancement and loss increase caused by ventilation needs to be comprehensively considered. When the ventilation wind speed increases from 2.5 m/s to 5.0 m/s, the cooling heat transfer coefficient on the rotor surface increases from 315.7 W/(m²•℃) to 469.1 W/(m²•℃), and the air friction loss also increases by 3.13 kW. The maximum error between the experimentally measured values and the simulation calculation results is 8.60%.

In small-to-medium span highway girder bridges in China, laminated-rubber bearings are typically positioned between the steel plate at the beam bottom and the concrete padstone on the pier/abutment. While relevant specifications indicate that relative sliding can occur at the bearing-steel plate interface, under certain conditions, sliding is more prone to occur at the bearing-concrete padstone interface. To investigate the mechanical behavior of this interface, reciprocating compression-shear tests were conducted under three levels of contact pressure: low (8 MPa), medium (10 MPa), and high (12 MPa). A three-phase deformation and failure mechanism was revealed, a bulging failure criterion was established, the evolution laws of the shear modulus and friction coefficient were quantified, and a friction coefficient attenuation model was developed. The results show that the bearing hysteresis curves are characterized by a parallelogram shape with internal crescent-shaped abrupt loops. Bidirectional damage transfer occurs at the bearing-concrete interface, evidenced by bulging of the rubber cover layer on the bearing and the presence of rubber debris adhered to the concrete surface. In the sliding friction stage, the shear modulus decreases with increasing contact pressure and consistently remains below the code-specified dynamic shear modulus of 1200 kPa. The interface friction coefficient, measured to be below the code-suggested values of 0.25 and 0.30, exhibits a negative correlation with the contact pressure. It is recommended to control the bearing contact pressure below 10 MPa in practical engineering to avoid the risks of a sudden drop in the friction coefficient and bulging failure. The proposed models can provide a reference for the seismic design of small-to-medium span bridges.

To investigate the influence of soil layer dip on the dynamic failure of slopes, the failure characteristics and dynamic response laws of bedrock-overburden layered accumulation slopes with different soil layer dips under seismic action were studied based on shaking table model tests. By varying the bedrock-overburden interface dip, three types of slopes with linear, concave, and convex surfaces were designed. Shaking table model tests were subsequently conducted on these slopes, yielding the failure modes of the three types of slopes with various dips. By taking into account the acceleration amplification effect of slope failure, the soil stress state, and the Mohr-Coulomb strength theory, the dynamic response mechanism of slopes and the critical conditions for slope failure were explored. The test results show that the failure characteristics of the concave slope are concentrated in the upper soil layer during the slope failure process, while those of the convex slope are concentrated in the lower soil layer. By contrast, the linear slope exhibits a failure mode characterized by tensile cracking in the upper soil layer and shear sliding in the lower soil layer. Under the same seismic magnitude, the concave slope exhibits the smallest acceleration amplification coefficient, and the acceleration amplification effects of the linear slope, concave slope, and convex slope are concentrated at the slope crest, slope shoulder, and the rear edge of the slope crest, respectively. With the increase in the various dip coefficients, the critical acceleration for slope failure increases accordingly. The research results can provide a scientific basis for the anti-seismic design, stability evaluation, and disaster prevention and mitigation of engineering projects involving bedrock-overburden layered accumulation slopes.

At present, most of the studies on the shear strength parameters of waste soil are carried out based on laboratory waste soil samples, and the parameters obtained through laboratory tests are often quite different from the actual parameters, resulting in a large error in the calculation of waste landfill deformation. In view of the error problem caused by the laboratory test, by relying on the closure and restoration project of the waste landfill under construction, the influencing factors and change laws of the shear strength parameters of the waste soil were analyzed by carrying out the large-scale field direct shear test and the small-size laboratory direct shear test of the waste soil and making a comparison with the literature test results. The results show that the shear capability of waste soil is higher than that of traditional soil, and the shear stress continues to rise and tends to be stable with the increase of shear displacement. The density of waste soil is linearly and positively correlated with its shear strength. When the density increases from 750 kg/m³ to 950 kg/m³, the cohesion increases from 22.5 kPa to 34.5 kPa, and the friction angle decreases from 36.7° to 30.2°. The mean cohesion value (14.91 kPa) obtained by the small-size laboratory shear box test is 6.27 kPa lower than that of the large-size field test (21.18 kPa), and the mean friction angle (35.17°) is 6.61° higher than that of the field test (28.56°).

To address two-phase flow problems with complex gas-liquid interface topology variation, a numerical simulation method capable of balancing computational efficiency and interface resolution accuracy was proposed. First, quadtree/octree Cartesian meshes with tree data structures were employed for spatial discretization. Adaptive mesh refinement was developed by leveraging the mesh’s hierarchical structures. Second, the continuum surface force (CSF) model was implemented within the adaptive mesh framework. By applying double convolution blurring to the volume fraction, the surface tension was smoothly distributed to the interface neighborhood, and the piecewise linear interface reconstruction technique was utilized to track the gas-liquid interface accurately. Subsequently, a mesh refinement criterion was established, and both the discrete error based on wavelet analysis of flow field velocity and the interface curvature distribution were considered, thereby achieving dynamic refinement in regions with sharp flow field variations and phase boundaries. Finally, the accuracy and reliability of the algorithm were validated through numerical examples of classic gas-liquid two-phase flow. The results show that in the verification of the Laplace law of surface tension, when the interface curvature is adopted as the refinement criterion, the computational error of internal and external pressure difference is only about 3.0%, which is significantly superior to the error range from 7.5% to 24% when using the volume fraction as the criterion, and its accuracy is consistent with that of uniform fine meshes. The proposed method can reduce the computational time consumption by approximately one order of magnitude compared with uniform fine meshes. In the numerical examples of surface tension waves, the root mean square error between the numerical solution and the theoretical solutions of regular modal can be reduced to the order of 10⁻⁵. In the simulation of a head-on collision between binary droplets, the experimentally observed dumbbell-shaped and diamond-shaped deformation sequences are reproduced, and the complex interface topology evolution details such as gas film rupture and the formation of tiny bubbles are captured.

In order to study the pullout characteristics of grouted enlarged toe precast pile (referred to as GET pile), a pullout experiment was carried out in a laboratory sand model box. Firstly, precast pile model with enlarged pile toe was assembled by connecting polyvinyl chloride (PVC) pipes and enlarged parts. Then, strain sensors were installed in the pile shaft, and the loading device and gravity sensor were arranged on the top of the piles. The pullout curves of different pile types were obtained by applying load on the top of the piles. Finally, the pullout bearing characteristics of the piles with equal cross section, piles with enlarged pile toe, and GET piles were compared, and the effects of enlarged base and grouting on pullout bearing characteristics were discussed. The experiment results show that GET pile can effectively improve the pile’s pullout bearing capacity. At small displacements, the pullout bearing capacity of piles with enlarged pile toe is twice that of piles with equal cross section and 5–6 times that of piles with pile side grouting. In addition, GET pile changes the mobilization characteristics of side friction resistance of the piles with equal cross section. The enlarged pile toe can increase the mobilization speed and maximum value of total side friction resistance and provide a certain amount of resistance at the pile end in the pullout process. Grouting can enhance the resistance on the pile side and the pile end, providing the initial total side friction resistance for the upper half of the pile shaft. There is a tendency to distribute more loads to the enlarged pile toe.

The system vibration caused by thrust ripple in double-sided linear induction motors (DSLIMs) is an urgent problem to be solved in precision control fields such as high-speed electromagnetic propulsion, rail transit, and industrial drives. An in-depth study on the secondary structure of DSLIMs was conducted, and an arrow-shaped secondary design was proposed to reduce thrust ripple. First, the key shape parameters of the arrow-shaped secondary design were derived. Three-dimensional finite element models of DSLIMs incorporating flat, square-misaligned, and arrow-shaped secondary designs were established to analyze their thrust output characteristics. Then, the eddy current distribution features and layered thrust distribution characteristics of different secondary structures were compared to elucidate the mechanism of thrust ripple suppression by the arrow-shaped secondary design. Finally, the thrust of the arrow-shaped secondary structure before and after optimization under motion conditions was compared using a three-dimensional transient finite element model. The results indicate that the optimized arrow-shaped secondary design improves the utilization of secondary conductors and enhances the thrust ripple suppression effect by optimizing the eddy current path in the end regions. In the region near the operational slip, the thrust ripple rate can be reduced to below 2%, and the thrust under the same mass can reach 21.51 kN, representing an increase of 1.03% compared with the square-misaligned secondary design.

To provide a more realistic geometric irregularity spectrum for high-temperature superconducting (HTS) pinning-type maglev systems, the irregularity spectrum of permanent magnet (PM) tracks considering structural periodicity was investigated. To achieve the characterization and inversion of the PM track irregularity spectrum that incorporates structural periodicity, a finite element model of an HTS maglev bridge and its PM track was first built. Moving loads from a maglev train were then applied to the model to identify the most unfavorable loading position, and the displacement at this point was extracted as the dynamic irregularity. Next, by considering the deformation of the PM track caused by bridge creep camber and superimposing the periodic dynamic irregularity results from train loads, a sample of periodic track irregularity was formed. Furthermore, random assembly errors of the PM track were modeled using a white noise filtering method to obtain a sample of random geometric irregularity. This was then superimposed with the periodic irregularity to form the overall PM track irregularity spectrum. The irregularity spectrum was fitted using a 4th-order polynomial and a Lorentzian function, and the fitted spectrum was inversely transformed via the inverse Fourier transform to verify the effectiveness of the fitting method. Finally, the influence of train speed on the fitted irregularity spectrum was analyzed. The results show that train speed mainly affects the PM track irregularity spectrum in the wavelength range of 3–100 m; when the speed approaches the critical resonance speed of the bridge, the amplitude of the inverse-transformed irregularity becomes significantly larger. The irregularity spectrum obtained in this study can be readily applied in the dynamics calculations of HTS maglev vehicles, serving as input for the dynamic analysis and design optimization of HTS maglev trains operating at various speed levels.