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 address the problems of missed detection of distant small vehicle targets, as well as ID switching and jumping during tracking in traffic surveillance scenarios, a small-target detection and tracking algorithm combining improved You Only Look Once version 5 small (YOLOv5s) and improved deep simple online and realtime tracking (Deep-Sort) was proposed. For detection, based on the YOLOv5s baseline network, the convolutional block attention module (CBAM) mechanism was introduced to enhance the feature capture of small targets. The Swin Transformer Block was fused with the cross stage partial (CSP) structure in the backbone network to construct the CSPSTB module and strengthen global information attention. The content-aware reassembly of features (CARAFE) upsampling operator was adopted to reduce feature loss, forming the YOLOv5s-CSC detection network. For tracking, a deep appearance feature extraction network containing a residual squeeze-and-excitation (Res_SE) structure was designed, which was more adaptable to vehicle features during data association. Experimental results on the UA-DETRAC dataset indicate that, compared with the original YOLOv5s model, the improved detection algorithm increases the mean average precision (m_AP)_, mean average precision at an intersection over union (IoU) threshold of 0.50 (m_AP50), and mean average precision at an IoU threshold of 0.75 (mAP75) by 1.5%, 1.5%, and 1.9%, respectively, and the small-target detection accuracy improves by 4.2%. Tracking experiments on the VERI-Wild dataset show that, after combining the improved detector and tracking network, the multi-target tracking accuracy, high-order tracking accuracy, and IDF1 (identity F1) score increase by 9.6%, 3.2%, and 7.7%, respectively. The combination of YOLOv5s-CSC and the improved Deep-Sort effectively overcomes difficulties of tracking failure of distant small vehicle targets, as well as ID switching and jumping during tracking, verifying the superiority of the improved model in tracking accuracy and robustness.

With the national initiative for green transport development, it has become a key research focus to promote green railway engineering through green design and achieve sustainable railway development at the source. To reveal the connotation of green design in railway engineering, first, the relevant definitions of green design were systematically reviewed. A keyword cloud atlas was generated using Python to identify key elements of green design definitions. Based on practical features of green railway engineering, a definition was thus formulated for green design in railway engineering. Then, based on bibliometrics and knowledge mapping, CiteSpace was applied to visualize characteristics of keyword structures and temporal clusters in the research content of green design in railway engineering. On this basis, the fundamental connotation was summarized. Through a “railway engineering-resources & environment” bidirectional coupling, the connotation was reinterpreted from the perspective of compatible symbiosis. With a design criterion that engineering impact intensity must be less than environmental capacity, a “railway engineering-resources & environment” compatible symbiosis framework as well as its characterization model were constructed to quantify the compatibility between engineering impact intensity and environmental capacity. Therefore, green design schemes were allowed to shift from qualitative comparison to quantitative decision-making. Finally, a logical analytical framework was established for green design connotation from four aspects: green design elements, their coupling mechanisms, performance assessment, and optimization/regulation mechanisms, so as to systematically deconstruct the connotation. The results are expected to provide theoretical guidance for construction of green railway engineering.

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 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 problems of premature inward buckling of the inner steel pipe and insufficient confinement to concrete in traditional concrete-filled double-skin composite tubular columns, a novel concrete-filled double-skin composite tubular column with an inner corrugated steel pipe was proposed. By taking the hollow ratio, nominal steel ratio, wall thickness of the corrugated steel pipe, and inner tube configuration as the main parameters, a systematic experimental study on the axial compressive performance of eight concrete-filled short double-skin composite tubular column specimens with inner corrugated steel pipe was conducted. Based on the experimental results, a finite element model was established to further discuss the load-bearing mechanism, confinement effect, and influence rules of key structural parameters of the components under axial loads. The results indicate that all concrete-filled double-skin composite tubular columns with inner corrugated steel pipe exhibit good ductility under axial compression. The failure mode is dominated by local outward buckling of the outer steel pipe, while no obvious instability occurs in the corrugated steel pipe. With an increase in the hollow ratio, the bearing capacity of the components decreases significantly; the nominal steel ratio has a pronounced effect on the bearing capacity, whereas the wall thickness of the corrugated steel pipe has a minor effect on the ultimate bearing capacity. Compared with traditional concrete-filled double-skin composite tubular columns, the peak bearing capacity of the novel components decreases slightly, but the initial stiffness and ductility improve significantly. The strength indices of all specimens are greater than 1.00, reaching a maximum of 1.33, which indicates that a more effective composite effect is formed between the corrugated steel pipe and the concrete. The finite element calculation results further reveal that the corrugated steel pipe provides strong lateral confinement to the sandwiched concrete mainly through the trough regions, while the helical angle has a minor effect on the axial compressive performance, and the waveform parameters have a certain effect on the bearing capacity. The research results provide a reference for the engineering application and design of concrete-filled double-skin composite tubular columns with an inner corrugated steel pipe.

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 address the problem of disconnection between topology and electrical characteristics in the optimization of measurement points of grounding grids and to enhance the accuracy and engineering applicability of fault diagnosis for grounding grids, grounding grids were transformed into an undirected graph model with node-branch relationships. The topological connectivity characteristics of nodes were measured using node degrees, and the electrical connection characteristics of nodes were measured using node sensitivities. A determination model of node composite weight integrating node degree and node sensitivity was constructed. A greedy algorithm based on dynamic tuning of composite weights was adopted to optimize the node weight model, and an optimized layout scheme of measurement points for grounding grids that can cover all branches was selected. Simulation results show that this method can select 25 measurement points from 49 nodes in a 7 × 7 grounding grid, achieving complete electrical observability of all branches of the grounding grid. Under the same number of measurement points, the average error of single-branch corrosion diagnosis is reduced by 15.6% compared with the network topology hierarchical reduction method, and the average error of multi-branch corrosion diagnosis is reduced by 13.4% compared with the network topology hierarchical reduction method. Furthermore, even with fewer measurement points, the multi-branch diagnosis error is still superior to that of the agglomerative hierarchical clustering method, achieving accurate diagnosis of single and multiple branches with different corrosion degrees (mild, moderate, and severe). The proposed method can reduce the on-site testing workload while ensuring the accuracy of corrosion diagnosis, and it has important practical significance for the precise maintenance of grounding grid corrosion.

To investigate the issue that the response spectrum for structures with high damping exceeds that with low damping in the long-period range in code design spectra, strong earthquake records with magnitudes greater than 4.5 in the Yunnan region since 2007 were collected based on the pseudo acceleration response spectrum theory considering the true inertial forces of structures. A classification system based on the site category classification standard, magnitude, epicentral distance, and design earthquake group was established. A differential evolution algorithm with global and neighborhood mutation was employed to calibrate and obtain the average values of the calibration parameters under each category. On this basis, the effects of various factors on the characteristic period, the plateau value of the amplification factor spectrum, and the decay index were obtained, and the recommended parameter values for the Yunnan region were ultimately proposed. The results indicate that both site category and epicentral distance have a positive correlation with the characteristic period $ {T}_{\text{g}} $. The recommended values for design earthquake groups under different site categories proposed based on the calibration results are increased by 0.05 s on average compared with the code recommended values. Epicentral distance and magnitude have a weak effect on the plateau value of the amplification factor spectrum $ {\beta }_{\max } $, and no clear regularity is shown. The calibration result of $ {\beta }_{\max } $is larger than the code value. Considering the statistical results and engineering safety redundancy comprehensively, it is suggested that the value range of $ {\beta }_{\max } $ in the Yunnan region be set to 2.575–2.675. The damping ratio is the most dominant factor affecting the decay index γ. The linear relationship between γ and the damping ratio $ \xi $ quantifies the effect of the damping ratio on the spectral decay segment, providing a basis for reasonably considering the damping effect.

Flight bridge rate is a key indicator for evaluating aviation service quality and airport operational efficiency. To improve the flight bridge rate, an optimized dynamic gate assignment method based on existing operational workflows and towing conditions was proposed. By arranging the full-day gate assignment plan in stages, and comprehensively considering constraints such as parking time limits for towed flights, towing eligibility conditions, and towing gate type restrictions, a gate assignment model taking the improvement of the flight bridge rate as the core objective was constructed. The number of flights assigned to contact gates was optimized by the model based on the towing penalty cost to maximize the overall efficiency. Meanwhile, to address the problem that the traditional pre-flight gate assignment is difficult to adapt to dynamic changes in flight operations, a multi-stage dynamic assignment algorithm based on an improved genetic algorithm was designed. In this algorithm, a continuous assignment mechanism was adopted to lock the completed assignment results, and the gate assignment for newly added flights was continuously optimized. Finally, simulation experiments were carried out using the actual operational data of a busy large-scale airport in Southwest China to verify the effectiveness of the proposed model and method. The results show that compared with the traditional gate assignment model without considering towing, the model considering the towing strategy increases the flight bridge rate by 1.1%; on this basis, compared with the traditional genetic algorithm, the adopted multi-stage dynamic assignment method increases the flight bridge rate by 4.0% and decreases the flight towing frequency by 16.6%. The proposed method can effectively balance the assignment of contact gates and aircraft towing costs, further optimize the flight bridge rate on the premise of controllable towing costs, and provide a feasible optimization method for the improvement of the flight bridge rate and dynamic gate assignment at airports.

To address two challenges in the health monitoring of full-ceramic rolling bearings, namely the difficulty in accurately characterizing the crack propagation mechanism and the limited accuracy of life prediction caused by the scarcity of monitoring data samples under extreme operating conditions, a hybrid network model for high-precision life prediction under small-sample conditions was developed. A two-degree-of-freedom dynamic model was established based on bearing operating characteristics to analyze and describe the nonlinear dynamic behavior of the bearing through vibration responses. Time-domain statistical and frequency-domain energy features were combined to conduct a joint characterization of state information. By considering the characteristic that the crack propagation process of brittle materials is difficult to directly observe, physical constraints governing stable crack propagation were integrated into the physics-informed neural network training, ensuring simulated signal evolution aligned with actual crack propagation trends. A generative adversarial neural network mapped simulated signals to real signals, producing high-fidelity simulated vibration data to expand the training sample space and alleviate small-sample limitations. A random forest regression model was applied for life prediction and identification of critical crack instability states, forming a complete analysis process of residual life assessment for ceramic bearings. Results indicate that the method accurately captures the laws of dynamic evolution from crack initiation to propagation, achieving an average life prediction accuracy of over 99.5%. The simulated signals fused with physical constraints show high consistency with real signals in the energy distribution of key feature frequency bands and peak locations of the envelope spectrum. This method improves the capability of identifying crack propagation trends and enables the recognition of the critical node corresponding to the transition from stable to unstable crack propagation.

To clarify the evolution laws of surrounding-rock temperature field and freezing radius in cold-region tunnels under the combined action of natural wind and train piston wind, and to improve the capability of rapid frost-damage risk assessment, a joint study of numerical simulation and machine learning was conducted using the Guolashan Tunnel as an engineering background. Based on field parameters, a three-dimensional transient heat transfer model consisting of air, primary support, secondary lining, and surrounding rock was established. Non-isothermal flow was used to couple the airflow with the heat transfer process of the lining and surrounding rock, and an equivalent wind speed method was adopted to characterize the effects of train piston wind and residual wind. Seven types of factors, including natural wind speed, natural wind temperature, natural wind direction, tunnel cross-section size, initial rock temperature, train speed, and train operation frequency, were analyzed through the control variable method. The longitudinal and radial temperature distributions and the freezing radius after 90 days were extracted, and random forest, support vector machine, and XGBoost prediction models were established based on 658 sets of orthogonal samples. The results indicate that the temperature-adjustment zone at the tunnel portal expands with the increase of cold-air action time; the longitudinal temperature of the surrounding rock presents two-stage characteristics of rapid rise and stable growth, and the radial temperature gradually approaches the initial rock temperature. Natural wind temperature, natural wind direction, and initial rock temperature are the dominant factors, with sensitivity coefficients of 0.22, 0.21, and 0.21, respectively. The XGBoost model has the optimal prediction accuracy with a root mean square error of 0.118; the predicted freezing radius for the engineering case is 1.85 m, with a relative error of 1.1%. External low-temperature air conditions and the initial thermal state of the surrounding rock are the key factors for frost-damage risk control in cold-region tunnels. The established models can provide a basis for rapid estimation of the freezing radius and optimization of anti-freezing design parameters.

The problem of vibration and noise caused by train operation is increasingly prominent, and it is difficult for traditional tuned mass damper (TMD) to achieve lightweight and broadband vibration reduction for rail. In view of this, inertial amplification mechanism (IAM) was introduced to achieve greater effective working quality of TMD by using inerter, so as to enhance the suppression of rail structure vibration. A new method for solving the complex band characteristics was proposed by using the energy method and the virtual spring method, based on which the complex band analysis model of the rail structure configured with IAM-TMD was established, and the accuracy of the model was verified with the solving results of the finite element method (FEM). On this basis, the influence mechanism of IAM on the vibration reduction effect of traditional rail TMD was investigated by taking the complex band characteristics as the evaluation index, and the modulation effects of IAM mass ratio, lever angle, and damping coefficient on the propagation of vibration wave in the rail structure were analyzed. The results show that the imaginary part of the complex band can describe the attenuation process of wave propagation inside the bandgap well. After the application of the IAM with α = 0.05 and θ = 10°, the original Bragg bandgap under TMD is widened from 925—1260 Hz to 881—1320 Hz, and the imaginary part of the complex band is increased, which implies that the attenuation capability of TMD is enhanced. The vibration reduction effect of IAM-TMD is proportional to the mass ratio and damping coefficient, and inversely proportional to the lever angle. The complex band characteristics are utilized to analyze the IAM, and the research results can provide a new idea for rail vibration reduction.

To address the two types of rail corrugation in small radius curves of the Chongqing metro (short-wavelength corrugation on inner rails in the sections without rail gaps, and long and short-wavelength corrugation on inner rails in the sections with rail gaps), the comparative study on the causes of two types of rail corrugation was conducted based on the theory of wheel-rail frictional coupling vibration. The finite element models of the wheel-rail systems in the section with and without rail gaps in small radius curves were established, and their stabilities were investigated using the complex eigenvalue analysis method. Then, the dynamic response of the wheel-rail system under the effects of rail gap and rail corrugation irregularities was investigated using the transient dynamic analysis method. The results have shown that the wheel-rail system exhibits frictional self-excited vibration in both sections with and without rail gaps on small-radius curves, with main frequencies of 479.26 Hz and 477.65 Hz, respectively, which can induce short-wavelength corrugation from 30 to 40 mm. Rail surface irregularities increase the dynamic response of the wheel-rail system. The induced feedback vibration has a main frequency of 112.79 Hz, thus inducing long-wavelength corrugation from 150 to 160 mm. The feedback vibration induced by short-wavelength corrugation irregularities only serves to increase the depth of the short-wavelength corrugation itself and does not induce corrugation with a new wavelength.

To investigate the stability of the bogie in a straddle-type monorail vehicle, the Hopf bifurcation characteristics of the straddle-type monorail vehicle bogie system were analyzed based on the spatial perturbations of the mechanical properties under the wheel-rail contact relationship. Firstly, a three-degree-of-freedom nonlinear dynamic model of the vehicle bogie, incorporating spatial perturbations, was established. Secondly, the Hurwitz stability criterion was employed to solve for the critical speed of the bogie system, and the type of Hopf bifurcation was identified via the center manifold stability index. The theoretical results were further validated numerically using the MATCONT toolbox. Finally, the influence of different spatial perturbation conditions on the stability of the bogie system was discussed. The research results show that at a motion state of low speeds, the bogie primarily exhibits rolling motion with a frequency of 2.4 Hz; at a motion state of medium and high speeds, the motion is dominated by coupled yawing and rolling, with frequencies ranging from 1.3 Hz to 2.4 Hz. When the speed reaches 163.563 24 km/h, the system undergoes a supercritical Hopf bifurcation, resulting in the emergence of a stable limit cycle; at a speed of 163.563 60 km/h, a saddle-node bifurcation occurs, leading to an unstable limit cycle. Under spatial perturbations, the critical speed of the bogie decreases with increasing radial stiffness of the guiding wheel and radial damping of the stabilizing wheel but increases with greater radial damping of the guiding wheel, radial stiffness of the stabilizing wheel, as well as the radial stiffness and damping of the running wheel. Moreover, changes in the structural parameters of the bogie can induce transitions between supercritical and subcritical Hopf bifurcations. To avoid subcritical Hopf bifurcations that may cause abrupt changes in the system’s motion state, the structural parameters of the bogie should be carefully designed.

To investigate the effects of continuous braking conditions on the maximum temperature and temperature difference of wheel tread and clarify thermal load characteristics of the wheel, continuous braking tests on the super-long large ramp were conducted on a 1∶1 brake test bench, with the friction pair of brake shoe and wheel tread taken as the research object. The distribution pattern of tread temperature during braking was analyzed by changing three key parameters: braking pressure, speed, and duration. Results demonstrate that when the braking speed increases from 40 km/h to 70 km/h, the maximum temperature during the three braking phases (0–1 200 s, 1 200–2 400 s, and 2 400–3 600 s) increases by 97%, 118%, and 86%, respectively, and the maximum temperature difference rises by 113%, 150%, and 128%, respectively. The increase in braking speed exerts a greater influence on temperature difference during the first two stages, which is attributable to the lower temperature of the initial friction surface and the wear-resistant properties of brake shoe contact areas that constrain expansion of contact areas. At a braking speed of 70 km/h, when the braking pressure increases from 3 kN to 7 kN, the maximum tread temperature increases from 321 ℃ to 436 ℃, representing a 36% increase. The increase in the braking pressure enhances the friction power and amplifies the effect of local contact on the friction temperature, which further exacerbates the uneven distribution of tread temperature. Under the braking pressure of 3 kN, augmentation of speed from 40 km/h to 70 km/h increases the maximum tread temperature from 176 ℃ to 328 ℃, representing an 86% increase. Increasing the braking speed can boost braking energy and increase braking power, which significantly expands the high-temperature regions. This study can provide a reference for analyzing the tread braking performance and developing operational strategies of rolling stock under super-long large ramps.

To investigate the thermal characteristics inside the control and protection cabinet of nuclear safety-class instrumentation and control (I&C) systems and the variation patterns of the steady-state temperature (SST) of key chips (CPU and field programmable gate array (FPGA)), experimental studies were conducted on the cabinet under different ambient temperatures. The finite element method was employed to simulate the experimental process, and the accuracy of the numerical model was validated by comparing the experimental results. Furthermore, the SST values of CPU and FPGA under 100 sets of random working conditions were calculated by the finite element model, and the SST values of CPU and FPGA under different working conditions were learned and predicted using four algorithms of multi-output support vector regression (M-SVR), extreme gradient boosting (XGBoost), artificial neural network (ANN), and Bayesian ridge regression (BRR). Results show that when the ambient temperature is 20 ℃, the SST of CPU and FPGA is 37.5 ℃ and 33.5 ℃, respectively. When the ambient temperature is 55 ℃, the SST of the CPU and FPGA rises to 72 ℃ and 68 ℃, respectively. Finite element analysis can well simulate the test phenomenon, and the calculated chip SSTs are in good agreement with the experimental results. All the four algorithm models can be used to predict chip SST, among which the ANN algorithm exhibits the best prediction performance on the test set. It has a mean squared error (MSE) less than 0.15% and an R² value greater than 0.99 and exhibits the strongest generalization ability. In contrast, although the other three models show good prediction performance for samples with high SSTs, the prediction error for samples with low SSTs is large, especially for the XGBoost model, whose prediction error is as high as 3.65 ℃. The research provides a new method for SST prediction of chips in nuclear safety-class control systems.

Morphological filtering (MF) is an effective method for bearing fault diagnosis with the capacity of recovering transient impulse features from noisy vibration signals, in which the choice of shape and length of structural element has an important impact on MF performance. To solve this problem, an enhanced time-varying structural element (ETVSE) based on median filtering was proposed to more accurately match and extract periodic transient features hidden in noisy signals. Moreover, the power spectrum (i.e., the frequency spectrum of autocorrelation signal) was applied to the filtered signal to further enhance fault-related components and eliminate broadband noise pollution. Finally, a bearing fault diagnosis method called enhanced time-varying morphological filtering (ETVMF) was developed, which combined the advantages of ETVSE and power spectrum. The analysis results of simulated data and measured data of two railway axle-box bearing test rigs show that, compared with the compared method, ETVMF demonstrates superior fault feature extraction performance and can accurately identify bearing inner race, outer race, and rolling element faults under complex noise interference, while obtaining higher performance quantification index and lower calculation cost.

To reveal the mechanical properties of glacial tills in the Purang region of Xizang, in-situ direct shear tests with normal pressures from 100 kPa to 400 kPa were carried out on surface glacial tills in a natural state, and laboratory large-scale direct shear tests with normal pressures from 100 kPa to 400 kPa and large-scale triaxial tests with confining pressures from 100 kPa to 400 kPa were carried out on glacial tills with the compaction degree of 96%. The results show that the cohesion of surface glacial tills with a compaction degree of 91.7% is 11.0 kPa, and the internal angle of friction is 41.0°. The cohesion of glacial tills with a compaction degree of 96% is between 9.4 kPa and 11.2 kPa; the internal angle of friction is between 45.3° and 46.7°; the strength parameters obtained from laboratory large-scale triaxial tests are higher than those from large-scale direct shear tests. The peak strengths of glacial tills with a compaction degree of 96% are higher than those in a natural state, but the initial moduli are lower than those in a natural state. The stress–strain curve of glacial tills exhibits softening characteristics under various confining pressures, and the peak strain shows a trend of an increase followed by a decrease with the increase of confining pressures. The modified Duncan-Chang model can well describe the relationship between deviatoric stress and axial strain of glacial tills and reflect the strain softening characteristics of glacial tills in the Purang region.

The fuel flow inside the high-pressure nozzle exhibits significant pressure drops and high flow velocities, leading to a high tendency towards gas-liquid two-phase flow with intense transient heat and a coupling between cavitation flow and thermal effect. Turbulence and cavitation models were corrected to incorporate thermal effects, and a non-isothermal compressible flow model for fuel within the nozzle was established. Simulation research of the transient cavitation flow of diesel in a high-pressure nozzle was conducted. Results show that 1) during the opening stage of the needle valve, cavitation develops rapidly, with its cavitation intensity influenced by the inlet pressure. At 180 MPa, the average cavitation volume fraction inside the orifice increases by approximately 24% compared to that at 60 MPa. Cavitation induces significant fluctuations in the fuel mass flow rate, thereby influencing injection stability. During the closing stage of the needle valve, the orifice is almost blocked by cavitation; the effective flow area is reduced, and the mass flow rate is significantly decreased. 2) The fuel temperature within the nozzle exhibits a non-uniform distribution. Fuel decompression, expansion, and endothermic phase transition reduce the local temperature and form a supercooled region. Temperature rise regions result from viscous friction of fuel caused by velocity gradients between the core orifice region and the near-wall region, with the maximum temperature reaching 410 K. 3) Fuel cavitation and temperature variations interact. Cavitation reduces fuel flow velocity, increasing velocity gradients between fluid layers and amplifying internal friction and kinetic energy losses of fuel, which elevates fuel temperature. The temperature rise subsequently increases saturated vapor pressure, further promoting cavitation development.

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 0.180% and 0.160%, 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 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.

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%; for variable cross-section curved beam, the maximum deflection error between the variable cross-section straight beam degenerated from theoretion degeneration 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 study the propagation characteristics of three-dimensional landslide surges and the mechanism of the surging force on the square pier, based on the general moving objects model (GMO) module within Flow-3D, a three-dimensional numerical model was established to simulate the fluid-solid coupling interaction among the landslide mass, the water body, and the square piers. Firstly, by taking the site area of a continuous rigid frame bridge in a certain reservoir area as the research background, the propagation process of surges triggered by the entry of a potential landslide body into the water was simulated. The propagation characteristics of landslide surges were then explored based on the time domain and frequency domain analyses. Secondly, by taking the main piers and side piers of the bridge as the research objects, the characteristics of surging forces acting on square piers of different sizes were investigated numerically. Finally, a simplified algorithm for the surging force on square piers was proposed based on the Morison equation. The results were also compared with the estimation results obtained by the harmonic superposition method. The research shows that during the propagation of landslide surges, the head wave height decreases along the way; the secondary wave absorbs the high-frequency energy of the head wave, and it increases along the way. The surging force on the square pier increases nonlinearly with the increase of structural size and exhibits strong nonlinear characteristics where the absolute value of the valley is significantly greater than the peak value. Based on numerical simulation, the Morison equation can be applied to effectively calculate the surging force on a square pier and accurately capture its temporal characteristics. However, the evaluation method combining the harmonic superposition method and the Morison equation underestimates the surging force on the square pier.

To accurately quantify and predict the internal pore pressure of tunnel lining concrete at the critical moment of spalling under high fire temperature, fire exposure tests on tunnel lining concrete were conducted. The evolution laws of the transient temperature field and pore pressure of lining concrete specimens during the fire process were obtained. Based on the tests, a “quasi-steady-state” pore pressure inversion model for high-temperature spalling of lining concrete was constructed, using experimental temperature data as the key driver. The reliability of the model was validated by comparing it with experimental results, and the spatial distribution characteristics of pore pressure at the moment of high-temperature spalling were revealed. The results show that for typical tunnel lining concrete specimens with an initial moisture content of 3.50%, at the critical moment of spalling under the HC fire condition, the pore pressure value ranges from 0.79 MPa to 0.96 MPa, with an average value of 0.88 MPa. The pore pressure value predicted by the model ranges from 0.91 MPa to 1.13 MPa, with an average of 0.99 MPa. The peak pore pressure predicted by the model agrees well with the experimental data, with errors ranging from 2.08% to 28.41% and an average error of 15.23%, which is lower than 20%. The pore pressure along the depth direction from the heated surface at the high-temperature spalling moment exhibits a “hump-shaped” spatial distribution, which can be resolved into the thermal cracking zone, the pore pressure concentration zone, and the thermodynamic equilibrium zone.

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.

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 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 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 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.

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.

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.

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.

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.

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.

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.

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 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.

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.

To investigate the influence of rail corrugation coupled with wheel concave wear on the dynamics characteristics of the high-speed train’s wheel-rail system and determine the safety threshold for rail corrugation in high-speed railways, based on vehicle-track coupling dynamics theory and field-measured rail corrugation data of a certain line, a vehicle-track rigid flexible coupling dynamics model of the CRH3 high-speed train was established. Rail corrugation superimposed on the Wuhan–Guangzhou track irregularity spectrum was used as the excitation input.. The influence of rail corrugation with different wavelengths and depths on wheel-rail dynamics characteristics was explored, and the coupling effect of wheel concave wear at different operation mileages with rail corrugation on vehicle subsystem’s vibration acceleration was analyzed. Then, the safety threshold for rail corrugation was proposed. Results show that rail corrugation significantly increases the wheel-rail vertical force. The coupled action of wheel concave wear and rail corrugation further amplifies the wheel-rail force response, with more severe concave wear leading to greater wheel-rail forces. Worn wheels that have traveled 200 000 km show an 10.8% increase in wheel-rail vertical force compared to new wheels. By considering wheel concave wear, for high-speed trains operating at an average speed of 300 km/h, the recommended safety thresholds for rail corrugation of 50 mm, 80 mm, 100 mm, 120 mm, and 150 mm are wave depths of 0.023 mm, 0.036 mm, 0.05 mm, 0.054 mm, and 0.069 mm, respectively. In practical applications, maintenance strategies should be adjusted according to specific operating conditions and track structures, and grinding should be carried out promptly when wave depths exceed the safety thresholds.

Water and mud inrush is one of the common geological disasters in karst tunnels, which poses a severe threat to the safety of tunnel construction and long-term operation. Therefore, ensuring the safety of water-resistant rock mass at the face is the key to the prevention and control of water and mud inrush disasters. To ensure the stability of water-resistant rock mass at the face under the action of strong seepage, a mechanical analysis model of water-resistant rock mass in strong seepage fractures at the tunnel face was constructed. The drag force effect generated by the water flow on the wall of the penetrating fracture was fully considered, and the minimum safe thickness formula of the water-resistant rock mass in the karst tunnel under the action of strong seepage was systematically derived. Parameter sensitivity analysis and engineering examples were employed; the stability of the surrounding rock during tunnel excavation was further investigated by using the finite-difference software FLAC3D, considering penetrating fractures and water-rich karst cavities ahead of the tunnel face; the influence mechanism of key parameters on the stability of the water-resistant rock mass was discussed in depth. The results show that the increase of fracture opening significantly enhances the effect of the drag force. Under the condition of strong seepage, the fracture drag force has a significant adverse effect on the minimum safe thickness of the water-resistant rock mass, and its influence degree increases nonlinearly with the increase of fracture opening. In addition, the influence of fracture at different location distributions on the minimum safe thickness shows significant differences. It is found that there is a critical transition point (height ratio of cantilever beams Ⅰ and Ⅱ = 5.07∶4.93) at which the upper and lower beams and slabs of the fracture are destroyed synchronously, which further reveals the internal relationship between the fracture location and structural instability. The findings of this study can provide a theoretical basis and engineering guidance for designing the thickness of water-resistant rock mass in karst tunnel face, mitigating karst-related disasters (e.g., grouting sealing, fracture reinforcement, and seepage control), selecting monitoring and early-warning indicators, and conducting risk classification during construction.