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.

In view of the complex light environment problems such as sudden light changes, dimness, and glare in highway tunnels, a lane line recognition method, improved Hough & least squares (IHLS), based on embedded artificial intelligence (AI) is proposed. It used the improved Hough transform algorithm to carry out Hough transform for detecting straight lines at lane feature points, and employed the least squares method (LS) for curve fitting to identify curved lane lines. Real-time brightness detection and AI-based enhancement were performed on the captured image by embedding AI vision processing algorithm on the in-vehicle camera. The image was enhanced by the zero-reference deep curve estimation (Zero-DCE) model. The edge detection was performed by the improved Otsu method, and the dynamic region of interest (DROI) was divided by pixel statistics. The image was enhanced and smoothed by guided filtering to improve the accuracy of lane line recognition. The experiment on the proposed method was based on the Liupanshan Tunnel of Qingdao-Lanzhou Expressway (G22). Compared with the LS algorithm, the IHLS algorithm shows a mean-IoU (MIoU) index increased by 4.14%, average precision (AP) increased by 3.08%, and running time (RT) increased by 0.01 s. Compared with Hough transform, the algorithm presents an MIoU index increased by 4.18%, AP increased by 2.88%, and RT increased by 0.01 s. The IHLS algorithm embedded with AI visual processing solves the optical problems such as machine vision overexposure, color imbalance, and distortion, and realizes real-time recognition and tracking of lane lines in complex light environments.

The wagon flow routes serve as the core foundation of traffic assignment in railway network planning and form the basis for designing train formation plans and train timetables. One significant challenge in railway transportation organization is how to quickly develop high-quality wagon flow routing schemes while considering complex constraints such as line capacity, with the aim of minimizing total transportation costs. Given the distinct tree structure of wagon flow routes, all the wagon flow towards the same destination station was considered as a whole, and the concept of in-tree was proposed. By doing so, the flow routing problem could be transformed into determining the in-tree scheme for each destination station (i.e., root node). On this basis, the classic arc-based multi-commodity flow model was reformulated using the in-tree selection variables. Subsequently, a two-stage solution approach was proposed in consideration of the structure of the reformulated model. The first-stage model aimed to generate a pool of promising in-tree schemes by using the column generation algorithm. The second-stage model was intended to select the best in-tree scheme for each root and obtain the wagon flow routes. Finally, by using basic data from the railway network in Southwest China, test instances of varying network scales were constructed to evaluate the algorithm’s performance. The results demonstrate that the proposed method can obtain near-optimal solutions within a short computation time. Compared to CPLEX, the column generation algorithm achieves higher solution efficiency; compared to a simulated annealing algorithm, it delivers better solution quality. The in-tree model exhibits lower model complexity and higher computational efficiency than the traditional arc-based model.

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 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.

To mitigate the deformation and upward arching defects prone to occur in the longitudinally continuous ballastless track structures of high-speed railway under high-temperature conditions, a reflective insulation coating with medium brightness and high reflective properties was formulated by using self-made fluorine-modified black pigments. This coating can effectively control the temperature while avoiding the visual damage caused by conventional white reflective coating with high brightness to people seeing it. The molecular structure of the self-made fluorine-modified black pigment was characterized by infrared spectroscopy. The mechanism underlying the high solar reflectance performance of the self-made black pigment was elucidated by using a UV-VIS-NIR spectrophotometer, with a comparison made against conventional cool pigments. Based on this, a reflective thermal insulation coating with medium brightness was developed, and the properties of the film-formed coating, including temperature control, adhesion, and durability, were tested. Furthermore, the full-scale track slab structures under natural exposure conditions were coated, and long-term temperature monitoring and analysis were conducted to evaluate the actual temperature control effect of the coating. The results show that the self-made fluorine-modified black pigment can effectively improve the solar reflectance performance of the reflective thermal insulation coating with medium brightness through the transparency characteristics of its near-infrared band. The solar reflectivity of the self-made coating can be increased by more than 7.2% compared to the coating with medium brightness by using conventional pigments. The insulation temperature difference under simulated solar radiation can be increased by more than 3 ℃. The coating possesses good uniformity, adhesion, and resistance to ultraviolet-induced aging. Under typical sunny conditions, it can reduce the surface peak temperature of a full-scale track slab structure by more than 10 ℃, the daily temperature difference on the surface by 5–10 ℃, and the longitudinal positive temperature gradient of the track slab by about 50%.

To enhance the industrialization level of the prefabricated bridge pier and develop connection forms compatible with the performance of the ultra-high performance concrete (UHPC) pier, an external prestressed connection joint and its tensioning process were proposed. The feasibility of this configuration and technique was validated through full-scale tests. Combined with finite element analysis, the influence of joint prestress and axial compression ratio on the performance of the UHPC pier was investigated, and a design method for prestressed joints based on the capacity design method was proposed. The research results have shown that the prefabricated pier with the external prestressed connection joint experiences typical bending failure, with the UHPC concrete of the pier body being crushed, but no interfacial separation occurs at the interface between the pier and the cap. The stress variation of the prestressed high-strength reinforcement is basically proportional to the horizontal load of the pier, with the maximum variation amplitude of only 9%, indicating that the connection performance of the external prestressed connection joint used in the specimen has reliable connection performance and good overall structural performance. When the tension force of the high-strength reinforcement in the pier is small, joint opening occurs at the interface between the pier and the cap, reducing the stiffness of the prefabricated bridge pier, but it has little effect on the peak load-bearing capacity of the specimen.

In order to meet the requirements for driving performance of railway bridges, it is necessary to control the smoothness of the bridge alignment. Based on the analysis of driving stability, the sensitive wavelength range of the vehicle body was determined. The amplitude of the completed bridge alignment within the range was adopted as the evaluation criterion. From the perspective of ensuring driving performance, by considering the self-adjustment capability of ballastless tracks and the relationship between the track surface alignment and the completed bridge alignment, the expression of the irregularity limit value for the completed bridge alignment was derived. A seven-span continuous steel truss girder bridge was taken as the research object. The irregularity amplitude of the completed bridge alignment within the sensitive wavelength range of the vehicle body was controlled according to the derived expression. A method for controlling the smoothness of the girder assembly alignment based on the target alignment of the completed bridge was proposed by combining Akima spline curve with the girder assembly curve. The research results show that the sensitive wavelength of the vehicle body is less than 200 m at driving speeds of trains ranging from 250 km/h to 350 km/h. If a seven-span continuous steel truss girder bridge is taken as an example, the irregularity limit values for the completed bridge alignment within the sensitive wavelength ranges of the vehicle body corresponding to speeds of 350 km/h, 300 km/h, and 250 km/h are 24 mm, 26 mm, and 29 mm, respectively. The irregularity amplitude within a 0–200 m wavelength range of the girder assembly alignment can be evaluated and controlled through the proposed method for controlling the smoothness of the girder assembly alignment.

Obtaining the vibrational characteristics of independent substructures from global structures is crucial. The conventional isolated substructure method with time series (SIM-TS) suffers from increased computational errors due to excessively small singular values under noisy conditions. To address this, an improved method named ISIM-TS is proposed, aiming to achieve higher accuracy in substructure modal parameter identification. First, based on SIM-TS, an adaptive truncated singular value decomposition technique was introduced, optimizing the decomposition results by dynamically adjusting the truncation threshold. The ISIM-TS was combined with the covariance-driven stochastic subspace method (SSI-COV) to establish a new substructure modal identification framework, termed ISIM-TS-SSI-COV. Then, the feasibility of the proposed framework was verified via a classical five-degree-of-freedom (5-DOF) numerical simulation. Finally, this method was applied to identify the dynamic characteristics of a substructure in a Tibetan ancient architecture. The numerical results demonstrate that the improved method enhances the identification accuracy of the substructure, particularly reducing the identification error of the second-order frequency by 71.4%, under 1% noise. Furthermore, based on response data acquired under ambient excitation, the proposed method successfully identifies the first two natural frequencies of the substructure as 12.18 Hz and 13.31 Hz, respectively.

The support structure of wheels is an important component of post-treatment reaction vessels. To improve the safety strength of the reaction vessels, the support system adopts a statically indeterminate structure. In view of the strength of supporting rollers and load-bearing characteristics of the system, based on the energy method, Lagrange multipliers were introduced and the law of energy conservation was combined to calculate the normal forces on each roller, thus solving the bending stress and contact stress. A simple 3D model was built, and by adopting finite element software, the stress distribution and variation laws of each roller were analyzed, with the results verified via experiments. The load distribution factor was defined, and the influence laws of manufacturing errors on the load distribution factor were analyzed by utilizing SPSSAU. The results show that the maximum bending stress of the roller is 42 MPa, which is much smaller than the yield strength of the material. The maximum error between the finite element simulation results and theoretical results is about 8%, and the accuracy of the proposed method was verified by strain experiments on rollers. The load distribution factor negatively correlates with the curvature radius of the roller surface, and positively correlates with the curvature radius of the wheel surface.

In view of the problems of low efficiency and high cost associated with current three-dimensional (3D) printing methods for fabricating physical terrain models, a rapid printing method for terrain models based on improved K-dimensional (KD) tree spatial segmentation was proposed, aiming to enhance printing efficiency and reduce material consumption. First, the correlation between digital terrain model features and 3D printing parameters was analyzed to establish a rule set of spatial segmentation constraints. Subsequently, an improved KD tree model integrating dimension adaptation and size constraints was constructed, overcoming the rigid limitations of positions and dimensions in traditional segmentation and achieving refined segmentation for the terrain model and effective removal of underground sections. Building upon this foundation, a rapid spatial segmentation algorithm incorporating a greedy strategy was designed. This algorithm maximized the hollowed-out volume of the base by pursuing locally optimal segments. Micro terrain areas were integrated by means of regional clustering to optimize the sub-block segmentation results. For each terrain unit after segmentation, a rapid prototyping method based on block-based parallel and inverted printing was proposed. Fine support structures at four corners prevented model distortion while enabling substantial base hollowing and reducing material consumption and printing time. Finally, an experimental environment was established; case experiments and analysis were carried out; five typical disaster terrain data, including earthquakes, wildfires, floods, landslides, and debris flows, were selected for printing validation under conditions of varying resolutions and spatial scales. Research results demonstrate that the proposed method effectively overcomes the rigid limitations of traditional segmentation and the problem of model sagging distortion in fused deposition modeling. Across cases of the five disaster types, the approach achieves an average reduction of 17.69% in 3D printing time and 28.98% in material consumption. This facilitates rapid and low-cost physical terrain model printing with high applicability across diverse terrains.

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.

Gas migration is prevalent in unsaturated loess foundations. Research into gas migration laws and catastrophe driving mechanisms holds great significance for urban construction, the evaluation of infrastructure service safety, and the interpretation of the loess catastrophe issue in the Loess Plateau. Therefore, by considering the transverse isotropy of loess foundations, an improved triaxial apparatus for unsaturated loess was used to conduct gas permeability tests on undisturbed soil samples (with different humidity and stress levels) and remolded soil samples (with various dry densities). The gas migration characteristics and gas catastrophe driving mechanism within transversely isotropic unsaturated loess were summarized, and a corresponding gas permeability coefficient model was proposed. The results indicate that with increases in density, moisture content, and stress level, both gas flow rate and gas permeability coefficient in transversely isotropic unsaturated loess exhibit a distinct trend of initial decrease followed by stabilization. Specifically, when the dry density is less than or equal to 1.51 g/cm³; the moisture content is less than or equal to 12.5%, and the vertical stress is less than or equal to 100 kPa, the observed decrease in gas permeability coefficient is less than 30%. Conversely, beyond these thresholds, the decay accelerates. Fundamentally, these factors induce compressed internal air pore volume, reduced pore connectivity, and increased tortuosity of gas flow paths, ultimately diminishing the gas permeability performance. Under the influence of density, moisture content, and stress level, the gas migration within transversely isotropic unsaturated loess collectively demonstrates a “suppression, pressurization, and driving” catastrophe mechanism. The research findings can not only improve the accuracy of gas permeability calculation in unsaturated loess and enrich the theory of gas leakage prevention and control but also offer valuable reference for the prevention and control of loess foundation catastrophe induced by pressurized gas.

As defects such as pitting usually occur on the wheel tread, the measured wheel out-of-roundness (OOR) signals often contain high-frequency noise interference, and sometimes the signals are discontinuous at the start and end points due to objective factors. Wheel OOR is an important wheel-rail interface excitation in the vehicle-track coupled dynamics model, exerting significant effects on the simulation of dynamic wheel-rail interaction and wheel OOR wear prediction. Selecting the suitable smoothing method is key to ensuring the accuracy of the simulation results. The smoothing effects of four commonly adopted methods based on the EN 15610 standard, Fourier series, moving average, and morphological filtering on processing wheel OOR signals were investigated, and the applicability of the four methods in predicting polygonal wear was discussed. The results indicate that the two methods of Fourier series and moving average can achieve sound smoothing and de-noising effect, preserve the waveform characteristics of original signals, and ensure continuity and differentiability at the start and end points of wheel OOR data when processing measured wheel OOR signals. Additionally, the two methods are also suitable for application in polygonal wear prediction. When the two methods are employed, the order of the Fourier series should be greater than 60 and the smoothing window length of moving average should be about 17 mm.

In high-pressure common rail systems under multiple injections, the pressure waves induced by the pilot injection cause fluctuations in the main injection quantity, thereby reducing in-cylinder combustion efficiency and increasing pollutant emissions. A data-driven prediction model for the main injection quantity based on Gaussian process regression (GPR) was proposed to achieve the accurate control of injection quantity under multiple injections. First, D-optimal design and a second-order response surface method were employed to build a response surface model for the main injection quantity by utilizing rail pressure, pilot-injection pulse width, pilot-main injection interval, and main-injection pulse width as factors. Analysis of variance indicates that the four operating parameters all have extremely significant effects on the main injection quantity. Then, based on a self-developed multi-physics coupled digital simulation platform, a dataset containing 528 operating conditions was constructed, and the model was trained. On this basis, several combinations of mean functions (zero, constant, linear, and quadratic polynomials) and different kernel functions (Seiso, Rqard, and Matérn) were systematically compared, and the linear mean function combined with the rational quadratic kernel function was identified as the optimal configuration. Results show that in test conditions, the mean absolute percentage error (MAPE) of main injection quantity predicted by the GPR-based model is 0.347% and the coefficient of determination R² is 0.9996, with predictions at different main-pulse widths and pilot-main intervals clustered closely around the regression line. In non-test conditions, the model can still accurately reproduce the fluctuation law of the main injection quantity with varying pilot-main intervals, and features lower error and higher consistency than BP, GR, and SVR models. The proposed GPR-based data-driven model under multiple injections is proved to have both high prediction accuracy and sound generalization capability, providing model support for the precise control of high-pressure common rail systems under multiple injections.

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 6 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.

An online non-parametric model for ship motion applicable to various maneuvering conditions was developed to enhance the accuracy of ship motion identification modeling and the autonomy and safety of ships during navigation. Firstly, given the complexity of ship navigation characteristics in different maneuvering conditions and challenges of online non-parametric identification, an adaptively updated ship motion non-parametric identification method was proposed by combining the sliding time window and relevance vector machine (RVM). Secondly, the effectiveness of offline non-parametric identification models based on RVM was validated via two different training sample selection schemes, with the importance of training sample quality emphasized. Finally, based on the proposed identification method and adaptive non-parametric model updating rule, online non-parametric identification for the three-degree-of-freedom ship motion states, course, and motion trajectory was conducted, and the identification results of the proposed scheme were compared with those of the non-adaptive identification scheme. The experimental results show that the proposed scheme can adaptively update the non-parametric model according to maneuvering condition changes. The mean absolute error (MAE) and root mean square error (RMSE) of the proposed scheme’s identification results are less than 0.11 and 0.18 respectively, while the MAE and RMSE of the non-adaptive method’s identification results are below 1.43 and 2.10 respectively. This fully validates the proposed scheme’s significant advantages in generalization, demonstrating higher identification accuracy and further confirming its applicability in various maneuvering conditions.

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⁻¹, 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.

Variable marking intervention in expressway weaving sections based on the cellular automaton was proposed by combining the advantage that variable markings can flexibly change the marking form according to the needs of traffic scenarios and provide more marking control strategies to solve the problems of fixed marking control in the weaving sections of urban expressways, with the intervention effect evaluated. First, the cellular automaton model was built based on the three-phase traffic flow theory to provide a basis for fuzzy controller building. Second, the strategy library of active variable marking intervention was generated, and the fuzzy controller was constructed to realize the full-time simulation of weaving section scenarios under variable marking control. By selecting the coil data of weaving sections and typical traffic flow data during peak periods in Shanghai as the traffic flow input for full-time simulation, the output was obtained for the marking control scheme. Finally, the intervention effect was evaluated in terms of operation efficiency, potential accident risk and pollutant emission. The results show that the average delays of the scenarios of real working conditions and designed working conditions are significantly reduced under variable marking intervention compared with ordinary markings, with the average delay of the designed working conditions decreasing from 71 to 48 s. The number of hazardous scenarios under variable marking intervention in real working conditions is reduced by 23.4% compared with ordinary markings. The mean values of several important pollutants emitted by the vehicles are significantly reduced.

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 prevalent issues of low effective throughput and limited covertness in high-speed rail (HSR) wireless communication systems, an optimization problem was formulated to maximize the system’s effective throughput, subject to constraints on the covert requirement, transmit power of the maximum artificial noise (AN), and the unit modulus of the intelligent reflecting surface (IRS) phase shifts, and a beamforming method for covert HSR wireless communications based on IRS assistance and AN enhancement was designed. An alternating optimization strategy was adopted, decomposing the coupled optimization variables into three subproblems, including base station beamforming, IRS phase shift optimization, and AN transmit power optimization. The covert requirement constraint was mapped onto a complex circle manifold using the quadratic transform method from fractional programming. The conjugate gradient (CG) algorithm was employed to optimize the IRS phase shifts. The Dinkelbach algorithm was used to design the AN transmit power, and these steps were iterated alternately. Simulation results demonstrate that the proposed algorithm achieves a lower computational complexity. Under high-speed scenarios, it enhances the system’s effective throughput by 27.31% and improves the covert transmission performance, which is important for enhancing the security of information transmission in HSR wireless communication systems.

Magnetic fluid vibration energy harvesters demonstrate distinct technical advantages in low-frequency vibration environments and broad application prospects in fields such as mechanical vibration monitoring, micro-nano sensors, and power supply for wearable devices. With the increasing energy demand and the growing prominence of environmental issues, the development of efficient and reliable vibration energy harvesting technologies has become a current research hotspot. By applying magnetic fluids to vibration energy harvesters, the frequency response threshold of the energy harvesters can be reduced, and their energy harvesting efficiency can be improved. This innovative design broadens the application scope of vibration energy harvesters and provides a stable energy source for microelectronic devices, holding significant theoretical and practical value. This paper reviewed the current research status of magnetic fluid vibration energy harvesters in China and abroad, elaborated on the latest research progress of electromagnetic and triboelectric vibration energy harvesters, and on this basis, analyzes the influence of the performance of magnetic fluid materials and wall surface characteristics on the electrical output performance of magnetic fluid vibration energy harvesters. The surface roughness and hydrophobicity of the wall material can also significantly affect the output performance of triboelectric energy harvesters. Therefore, how to optimize the performance of magnetic fluid materials and wall surface characteristics to improve the output performance of energy harvesters, and design efficient energy management systems to achieve stable energy output and effective utilization, are important research directions for the future. The future development trends of magnetic fluid vibration energy harvesters were prospected, so as to provide references for related research.

To investigate the mechanical meso-mechanism and macroscopic response of coarse granular materials in rockfill dams, and to overcome the limitations of traditional continuum-based methods in simulating force chain evolution and particle breakage, a continuous-discontinuous deformation analysis method suitable for triaxial tests on coarse granular materials was developed. This method, based on the traditional discontinuous deformation analysis (DDA) framework, introduced a hybrid displacement mode to differentiate the mechanical responses of various blocks. Critical damping was employed to accelerate computational convergence, and a continuous-discontinuous simulation technique was proposed to characterize particle breakage. Through conventional triaxial numerical simulations, the deformation evolution, force chain development, particle breakage, and shear band formation during loading were analyzed, with particular emphasis on the effects of size and end friction. The results indicate that the simulation outcomes agree well with experimental data, reflecting both the macroscopic mechanical response and meso-mechanisms of coarse granular materials. The size effect leads to a 21.3% increase in peak stress under 0.4 MPa confining pressure, whereas its influence becomes negligible at 3.0 MPa. Under 3.0 MPa confining pressure, end friction contributes to an approximately 7.4% increase in peak stress. This study provides an effective numerical tool for further understanding the mechanical properties of coarse granular materials.

To investigate the mechanical characteristics of large-diameter shield tunnel segment structures under ultimate loads, a multifunctional shield tunnel structure loading device was used to conduct a prototype loading failure test on the shield tunnel segment structure of the Sutong gas-insulated metal-enclosed transmission line (GIL) utility tunnel project. The mechanical response laws of deformation, internal force, joint deformation, bolt and steel bar strain of the segment structure under ultimate load were analyzed. Based on the crack morphology, the failure characteristics and mechanisms of the segment structure were revealed. The results show that the deformation of the segment structure presents a horizontal duck egg shape, the bending moment presents a butterfly shape, and the axial force presents a circular shape. The maximum single point change rate is 10.3‰, the maximum positive bending moment is 3896 kN•m, and the maximum axial force is 17099.28 kN. The maximum bolt strain is 1871 με, far less than the yield strain, and the maximum steel bar strain is 2213 με, exceeding its yield strain. The safety margin for the deformation indicator of the segment structure is between 0.92 and 1.72, while for the strength indicator, it is between 0.10 and 0.16. The strength indicator reaches the ultimate failure value before the deformation indicator. Reinforcement yielding or the main crack penetration is recommended as the judgment criterion of the ultimate limit state for the normal serviceability of the segment structure. Cracks of the segment structure first appear in the middle of the segment B3. When the load is 1778.4 kN, multiple cracks penetrate through the inner and outer arc surfaces of the arch crown and arch bottom, with the maximum widths of the cracks on the inner and outer arc surfaces reaching 4.5 mm and 11.5 mm, respectively. The steel bar of the segment B3 reaches the yield condition, and the segment structure is damaged due to local instability.

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.

To investigate clause redundancy in clause sets with equality, a determination method for clause redundancy, namely equality implication modulo resolution (EIMR) principle, was proposed. First, the need for handling redundant clauses during the simplification process in a first-order logic theorem prover was analyzed, and the limitations of implication modulo resolution principle in handling clause sets with equality were identified. By integrating flattening and resolution methods, the EIMR principle applicable to clause sets with equality was defined. The reliability of the principle was proven, and the specific role of the principle in the determination of redundant clauses was clarified. Subsequently, on the basis of EIMR, the clause elimination methods from propositional logic and clause sets without equality were extended to clause sets with equality. Asymmetric tautologies and subsumption clauses of equality resolution were defined, and the effectiveness of these methods was demonstrated. Finally, the reliability of predicate elimination preprocessing methods in mainstream first-order theorem provers was validated using the EIMR principle. The results indicate that EIMR provides a theoretical basis for clause redundancy studies in clause sets with equality and extends the applicable scope of existing clause elimination methods.

To clarify the seismic behavior of earthen-stone masonry walls in traditional Tibetan dwellings in Western Sichuan, four earthen-stone masonry wall specimens were designed, fabricated, and used for conducting quasi-static loading tests. Timber wall reinforcement installation, wall tapering, and wall window openings were adopted as the main parameters to study their influence mechanisms on the seismic behavior of earthen-stone masonry walls. Through the tests, the horizontal load–displacement curves of the earthen-stone masonry walls were obtained, and key seismic performance indicators including bearing capacity, deformation capacity, stiffness, ductility, and energy dissipation capacity were analyzed. The influence of wall openings and timber wall reinforcement installation on the failure mode of the wall was discussed, and a comparative analysis of the shear strength between the earthen-stone masonry walls in Tibetan dwellings and ordinary brick masonry walls was conducted. The research results indicate that the earthen-stone masonry walls in Tibetan dwellings in Western Sichuan generally exhibit good seismic behavior and deformation capacity. In this test, the average shear strength per unit area of each wall component reaches 0.16 N/mm², and the ultimate deformation capacity is in the range of 2.4%–3.0%, with its deformability showing obvious advantages compared with ordinary brick masonry walls. Both window openings and timber wall reinforcement installation affect the failure morphology and failure mode of the walls. Compared with walls without timber wall reinforcement, the shear strength and energy dissipation capacity of walls equipped with timber wall reinforcement are increased by approximately 27% and 37%, respectively. Meanwhile, the number and width of shear cracks are significantly reduced.

Mitigating axle load transfer by optimizing structural parameters of locomotives is a primary strategy for enhancing adhesion utilization. To address the unclear mechanism by which the traction rod of a locomotive affects axle load transfer, a theoretical calculation model for axle load transfer given the rotation of the traction rod was established based on quasi-static equilibrium. The influence of the traction rod parameters on axle load transfer was explored based on the Sobol sensitivity analysis. Further analysis investigated the influence of traction force magnitude, stiffness of rubber sleeves, and position of the traction rod on axle load transfer. The results show that when the rotation of the traction rod is considered, the calculation results of the theoretical model are closer to those of the Simpack model, and the theoretical model exhibits significantly higher computational efficiency than the dynamics model. The initial tilt angle of the traction rod has a greater effect on axle load transfer than other traction rod parameters, and the rotation of the traction rod causes the load on each axle to vary nonlinearly with the traction force. As the radial stiffness of rubber sleeves of the traction rod exceeds 160 MN/m, the change in the locomotive’s axle load transfer tends to be gentle. As the deflection stiffness of rubber sleeves of the traction rod increases from 20 N m/rad to 500 N m/rad, the locomotive’s axle load transfer increases by 25.7%. As the height between the end of the traction rod frame and the rail surface increases from 0.05 m to 0.8 m, the locomotive’s axle load transfer increases by 84.3%. As the longitudinal distance between the end of the traction rod frame and the frame centroid increases from 0.5 m to 3.5 m, the locomotive’s axle load transfer decreases by 30.4%. The rotation angle of the traction rod approaches 0 when the initial tilt angle of the traction rod is around 11°. The axle load transfer of the second and third wheelsets approaches 0 when the initial tilt angle of the traction rod is between 13° and 14°.

To reduce the structural and ground safety risks caused by the high-speed air–water mixture during geyser events in baffle-drop shafts, a numerical simulation was conducted to investigate the influence of void fraction and connecting pipe diameter on shaft pressure and geyser intensity. The variation patterns of impact loads on the baffles at the shaft bottom were analyzed, proposing the installation of a throttling orifice at the shaft midpoint to control the geyser intensity. The results show that the pressure in the connecting pipe first reduces and then increases with rising void fraction, reaching a minimum within the range of 0.2–0.4. Among the three diameter ratios considered, the geyser intensity reaches its maximum when the diameter of the connecting pipe is half that of the shaft. The impact load on the baffles decreases continuously from bottom to top, and for any given baffle, the impact load near the partition wall and shaft wall is greater than that at the baffle’s edge. Installing a throttling orifice at the shaft midpoint can effectively control the geyser intensity, and the impact load on the throttling orifice is 10 times greater than that on the bottom baffle. These findings provide a reference for the safe operation of urban deep tunnel drainage systems.

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

Accurate and uninterrupted position information is crucial for ensuring the safe and efficient operation of rail transit trains. However, realizing seamless and precise positioning still poses a significant challenge for current train positioning systems operating in complex environments such as tunnels, elevated tracks, urban canyons, and suburban areas. A resilient positioning, navigation, and timing (PNT) system can produce continuous, reliable, and robust position information by integrating diverse PNT information sources. It can withstand hazards, adapt to risks, and counteract interference, offering a viable solution to the aforementioned challenges and demonstrating significant potential in fields such as military defense and aerospace. To promote the application and development of this technology in the rail transit sector, the navigation, positioning, and timing requirements of users of the rail transit industry were analyzed. According to the existing navigation and positioning capabilities of rail transit systems, the concept and framework of a resilient PNT system tailored for rail transit was proposed. Given the unique characteristics of rail transit PNT, the fundamental characteristics and evaluation metrics of the resilient PNT system of rail transit were summarized, and the relationship between resilience and accuracy, integrity, continuity, availability, and other indicators was elaborated. On the basis of multi-source PNT sensors (including global navigation satellite system (GNSS), responders, 5G-new radio (5G-R), etc.), the key technologies of the resilient PNT technology system and information fusion for rail transit were discussed. In conclusion, deep fusion of multi-source information and resilient fusion architecture are important research directions for achieving continuous seamless positioning in future rail transit.

The conservation of ancient stone arch bridges is severely hindered by drawing deficiency, difficult on-site survey, and structural deterioration. These obstacles make it difficult to acquire the geometric parameters required for refined mechanical models and to reproduce the real damage state of individual blocks. As a result, refined mechanical models can hardly be established effectively. To solve the problem, a finite-element (FE) modeling strategy of ancient stone arch bridges based on masonry structure gap image recognition is proposed. First, a dataset with a large number of labeled contours of blocks in stone arch bridges was constructed, and a trained YOLOv8 convolutional neural network was used for instance segmentation of the block contours on the bridge images. Second, the recognition results were post-processed with the Douglas–Peucker algorithm, and key geometric information of individual blocks was extracted. Finally, a parametric modeling procedure was developed: an ABAQUS parametric modeling script was developed to automatically generate a separate FE model that faithfully replicates the actual masonry structure, with contact interfaces defined between blocks for subsequent FE simulation analysis. The results show that under self-weight and deck loads, the peak principal stress in the arch rib predicted by the separate FE model is about 1.2 times that given by a conventional monolithic FE model, and conspicuous stress concentrations appear at masonry defects. The separate model can more accurately reproduce the block distribution and local defects of the actual bridge. It has significant advantages for revealing the damage mechanism of the masonry structure of ancient bridges, and provides a new perspective and method for the mechanical simulation study of ancient bridge protection.

To enhance the accuracy and efficiency of crack detection of ancient bridges and address the issues of information loss and secondary damage caused by traditional sensor detection methods, a crack identification and measurement method was proposed based on an improved You Only Look Once 11 (YOLO11) and SegFormer. First, to overcome the limitations of the YOLO11 model, including its large parameter size and restricted inference speed, the You Only Look Once-crack detect (YOLO-CD) object detection model was introduced. The StarNet lightweight backbone network was employed to reduce computational costs. The HSANet neck network was integrated to enhance the ability to preserve the crack edge detail, and an optimized spatial context detection (OSCD) head was designed to improve multi-scale detection efficiency. Second, an enhanced SegFormer-HF semantic segmentation model was proposed, which incorporated a feature fusion module (FFM) and a high-low frequency decomposition block (HLFDB) to mitigate information loss during sampling and improve semantic consistency in crack segmentation. Finally, a joint detection-segmentation framework was developed, combining a skeleton line algorithm to achieve automatic calculations of crack length and width. Based on the experiments conducted on the crack dataset of ancient bridges, the results have demonstrated that the YOLO-CD model achieves F1 score, mAP50, and mAP50-95 values of 67.8%, 71.5%, and 46.4%, respectively, while reducing floating-point operations (GFLOPs) by 47.6% compared to YOLO11. The SegFormer-HF model achieves superior performance with F1-score, mIoU, and mPA of 91.50%, 90.51%, and 85.15%, respectively, outperforming existing mainstream models. The results validate that the proposed method achieves higher efficiency and compact model size while balancing detection speed and accuracy, which is suitable for deployment on mobile devices such as cameras and drones.

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 enhance the economic efficiency of the traction power supply system of high-speed maglev, an optimization design method integrating power supply partitions and stator segment length was developed using the improved genetic algorithm. Firstly, a mathematical model of the traction system was established through analysis of equivalent circuits under dual-feeding mode. The effective range of power supply partitions was determined to be 20–40 km through comprehensive consideration of tracking intervals and traction performance constraints. Then, the design length of the stator segment was 600–2 000 m according to step-switching control and traction performance constraints. On this basis, the dynamically-constrained adaptive genetic algorithm was employed to optimize the design of the power supply partitions and stator segment length, so as to minimize the overall economic cost. Finally, the Shanghai–Hangzhou maglev planning line and the Shanghai maglev demonstration line were selected as validation subjects. Through hardware-in-the-loop simulations, dynamic train operation data was acquired to compare the comprehensive economic cost of the traction system before and after optimization. Results show that for the Shanghai–Hangzhou line, the traditional design scheme requires seven 27 km power supply partitions of equal length. In contrast, the optimized scheme uses six differentiated partitions, among which the partition at the ends is 20 km, and the central partition is about 37 km. This reduces the comprehensive economic cost by 14.25%. For the Shanghai maglev demonstration line, the existing scheme uses 25 stator segments with a length of about 1 200 m each. The optimized scheme produces 26 unequal-length segments, forming a current-matched layout with shorter segments for higher current and longer segments for lower current, which reduces the comprehensive economic cost by 19.1%.

Bus stops play a role in the connection and transfer in the travel chain of residents, and the density of slow-moving heterogeneous groups in their areas is high, thus increasing the possibility of traffic conflicts among them. Existing studies focus on traffic conflicts in bus stop areas, but the traffic conflict causation of slow-moving heterogeneous groups in bus stop areas and the heterogeneity among the factors are not explored. By taking four types of bus stops in Kunming as the research object, data of 20 bus stops from December 2022 to March 2023 was collected, and the movement characteristics of slow-moving heterogeneous groups were analyzed. The severity of conflicts was determined based on the Dutch objective conflict technique for operation and research (DOCTOR) method, and a random parameter Logit model was constructed in consideration of the mean and variance heterogeneity. The results show that in random parameter distributions, the lateral conflict and non-motorized lane width for pedestrians obey normal distributions with means of 0.455 and −0.541 and variances of 0.872² and 1.214², respectively. The yielding and high speed of cyclists obey normal distributions with means of −0.399 and 0.745 and variances of 1.274² and 1.043², respectively. In mean heterogeneity, there is mean heterogeneity for lateral conflicts with respect to the high speed of pedestrians and for non-motorized lane width at island linear bus stops, and there is mean heterogeneity for yielding of cyclists with respect to riding on sidewalks and for the high speed of cyclists with respect to the cyclist density. In variance heterogeneity, there is variance heterogeneity for the parameter of non-motorized lane width among the elderly and for the parameter of the high speed among female cyclists. The average marginal effect coefficients were further calculated to quantify the extent to which the factors contributed to the severity of traffic conflicts. After analysis, the probability of a serious traffic conflict is the highest for dismounted passengers in the pedestrian group and for reverse cyclists in the cyclist group.

As demands for manufacturing quality and production efficiency continue to rise in modern industry, tool wear has emerged as a critical constraint affecting surface roughness. Traditional tool condition monitoring and process parameter optimization methods are often based on empirical models or static optimization strategies, limiting their adaptability to complex, dynamically changing, multivariable environments. In response, this study proposes an innovative approach integrating multi-scale distribution ratio (MSDR) with Bayesian multi-armed bandit (BMAB) for process parameter online optimization, incorporating real-time tool condition data into the optimization framework. Additionally, by combining Bayesian optimization and multi-armed bandit strategies, this method enables real-time adjustments to process parameters in dynamic manufacturing environments, effectively balancing exploration and exploitation to maximize machining efficiency. Compared to mainstream methods, MSDR demonstrates exceptional precision and stability in tool condition monitoring, achieving MAE, SMER, and RMSE values of 0.145, 0.258, and 0.194, respectively. BMAB also performs exceptionally in optimizing cutting efficiency and computational effectiveness, achieving 2305 mm³/min and a runtime of 2.92 seconds, respectively. Therefore, tool state-aware online optimization of process parameters presents a novel and promising technical pathway for high-precision manufacturing.

As a strategic direction for future high-speed land transportation, the spatial alignment design of high-speed maglev railways has a decisive impact on system performance and safety. The latest research advances in spatial alignment design of high-speed maglev railways were reviewed. First, the development history of high-speed maglev lines was summarized, including Japan’s maglev test lines, Germany’s Transrapid system, China’s high-speed maglev engineering practices (e.g., test lines at Jiading Campus of Tongji University, Qingdao Sifang Company, Shanghai Airport, and Jiuli Campus of Southwest Jiaotong University), as well as ongoing and planned lines. Subsequently, the influence of spatial alignment of high-speed maglev railways on train stability was analyzed from three perspectives: the coupling effects of spatial alignment on levitation and guidance, the dynamic response mechanisms governed by alignment parameters, and the aerodynamic constraints on alignment configurations. Furthermore, the definition and composition of spatial alignment design were systematically elaborated, covering calculation and selection criteria for horizontal and vertical alignment parameters, combined horizontal and vertical alignment optimization, and turnout alignment studies. Current research bottlenecks were identified, such as inefficiencies in multi-physics coupling modeling and simulation efficiency, insufficient correlation between alignment parameter standards and dynamic performance, limitations in test line design theories and scenario coverage, challenges in global optimization and safety threshold quantification, low intelligence in alignment selection, difficulties in coordinating complex coupling constraints, immature multi-objective optimization methods for alignment selection and design, and inadequate integration of environmental impact assessment with alignment design. Finally, seven directions for in-depth studies were pointed out to advance the innovation and refinement of spatial alignment design theories for high-speed maglev railways.

Freeze-thaw cycles are among the primary factors affecting the limestone cultural relics in northern China. These cycles often result in various forms of surface weathering, seriously threatening the long-term preservation of these cultural relics. Water immersion freeze-thaw simulation weathering experiments were conducted on fresh limestone. The development patterns of physical and mechanical property indicators were obtained by utilizing various characterization techniques. By examining variations in pore structure, the freeze-thaw damage mechanism of limestone was quantitatively revealed from both macro and micro scales, and a comprehensive evaluation of weathered limestone was performed using an entropy weight-linear weighting method. The results have shown that after 50 freeze-thaw cycles, the P-wave velocity and surface hardness significantly decrease, with a loss rate of over 10%. The capillary water absorption coefficient increases by more than one time; The uniaxial compressive strength decay rate was 30.6%. As the number of cycles increases, the structural integrity of the compressed limestone becomes worse. The pores of limestone are primarily composed of mesopores (0.1-1000 μm). Freeze-thaw cycles lead to an increase in both the number and volume of pores, accompanied by particle wear and the expansion of cracks. The mechanical-property half-life is a key parameter for evaluating limestone’s freeze-thaw resistance. A multivariate regression model based on non-destructive measurements can effectively predict the variation in uniaxial compressive strength. The capillary water absorption coefficient exhibits the greatest sensitivity to weathering damage. The introduction of an integrity index enables a multidimensional and quantitative assessment of the weathering severity of building limestone. The research findings provide a theoretical basis and practical guidance for the scientific understanding of limestone materials and the assessment of the current state of cultural relics’ weathering.

The large eddy simulation (LES) was employed to make a transient simulation of the flow field within the grid flocculation tank to investigate the evolutionary characteristics of the jet vortex flow structure of flow field within the grid flocculation tank. The grid flow field was analyzed from both two-dimensional and three-dimensional perspectives. The results indicate that a jet vortex flow field is formed immediately behind mesh holes as fluid flows through a grid plate. Due to shear, entrainment, and mixing between jet and background fluid, a backflow vortex zone is formed in the region behind the grid, accompanied by a continuously developing vortex ring structure along the side wall. The vortex ring structure causes varying degrees of deformation and displacement at the front of the jet, while also suppressing its forward movement. The vortices are mainly located within the boundary layer of the jet, with rapid changes occurring in their structure at its forefront. This area exhibits both maximum size and intensity. The most significant variations in vortex structure intensity are observed near the side wall, where the vortex structures of each jet display mirror symmetry about its axis. Additionally, the front of the three-dimensional vortex structure resembles a coronal formation. As the jet develops forward, the coronal structure will extend and swell to become larger and then will eventually discrete and detach. The distribution of vortex structure at each moment exhibits mirror symmetry with respect to the bisector of the flow field, while the variation process of the flow field morphology demonstrates a trend from the side wall towards the center of the flow field.

Due to their exceptional wave manipulation characteristics, acoustic metastructures have attracted substantial attention in vehicle noise, vibration, and harshness (NVH). However, the further development and application of passive acoustic metastructures are limited by the narrow and non-tunable low-frequency bandgaps and bandwidth. To address this challenge, an electrically controlled acoustic metastructure was proposed to enable flexible bandgap tuning, and the corresponding electrical twin theory was established. According to the classical electromechanical analogy, a two-dimensional electrical twin circuit for a Kirchhoff-Love thin plate was established by the finite difference method. Then, an inductance-capacitance-resistance (LCR) resonant circuit was connected in series to form the twin circuit of a metastructure unit, with a tunable capacitor introduced to achieve electrical bandgap tuning. Finally, a spiral-shaped electrically controlled metastructure was derived from the twin circuit and verified through simulations and experiments. The results confirm that the twin circuit constitutes an exact electrical-domain mapping of the metastructure. The equivalent stiffness of the metastructure can be adjusted by the electrical control, thereby facilitating bandgap tuning. The resulting tuning law can be efficiently predicted and analyzed by the twin circuit. The designed spiral-shaped electrically controlled metastructure exhibits a significant order-tracking noise reduction effect for electric seats, with an average sound pressure level reduction of approximately 7.4 dB(A) in the wide frequency range of 200–460 Hz. The proposed twin circuit contributes to the electromechanical integrated design of electrically controlled metastructures, and it provides a theoretical paradigm for the study of different types of electrically controlled metastructures.

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 address the inadequate anti-roll stiffness of the axle box in-board bogies of high-speed electric multiple units (EMUs), a primary suspension configuration was proposed to replace the traditional hydraulic damper with hydraulic interconnected units. The configuration could increase the anti-roll stiffness without increasing the vertical stiffness. Firstly, the equilibrium equations of oil pressure, flow rate, and output force were derived. A nonlinear dynamic model of the vehicle system was established using SIMPACK, and a simulation model of the hydraulic interconnected units was created in MATLAB/Simulink to facilitate co-simulation of the vehicle-hydraulic interconnected unit coupling system. Subsequently, the accuracy of the simulation model was validated based on the quasi-static characteristic test of the hydraulic interconnected units and the dynamic tests of the roller rig of the entire vehicle. The simulation analysis was conducted to ascertain the impact of pivotal parameters associated with the hydraulic interconnected units on the roll angle of the car body, derailment coefficient, and riding index for various operation conditions of vehicles. Finally, the field dynamic tests were conducted to verify the improvement in the dynamic performance of vehicles during curve negotiation. The results have shown that the roll stiffness of the interconnection unit is significantly greater than that of the traditional hydraulic dampers. The roll angle of the car body can be reduced by more than 0.5°, which is conducive to narrowing the dynamic limit and ensuring overturning safety. The field test results demonstrate that the dynamic indexes of hydraulic interconnected units are comparable to those of traditional oil pressure dampers. It is viable to address the issue of inadequate anti-roll capability of axle box in-board bogies by adopting hydraulic interconnected units.

To investigate the influence of the dynamic braking process of high-speed trains on the longitudinal force at the pier tops of simply supported beam bridges, the rail-level braking force time-history curve was first calculated and obtained via multibody system dynamics simulation. Longitudinal resistance tests were then conducted on WJ-8 type low-resistance fasteners to reveal the law governing the influence of loading frequency and vertical load on the longitudinal resistance properties of the fasteners. Finally, a finite element model for longitudinal track–bridge interaction in multi-span simply-supported girder bridges was established. In this model, the wheel’s vertical and longitudinal forces were applied as moving concentrated loads on the rail, taking into account the uneven distribution of dynamic vertical force among the fasteners and their corresponding vertical-load-dependent longitudinal resistances. The influence of braking stop position and number of spans on the dynamic response of the track–bridge system was analyzed using the dynamic time-history method, and the results were compared with those from static analysis. The findings indicate that the longitudinal resistance of the fasteners is not significantly influenced by the loading frequency but is sensitive to the vertical load they carry. The longitudinal forces in the rail and at the pier tops are maximized when the train stops braking at the abutment of the final span. While these forces increase with the number of spans, they stabilize beyond eight spans. A discrepancy is observed between the dynamic and static analysis results for the maximum rail stress and displacement, yielding a dynamic amplification factor of approximately 1.05. Furthermore, the dynamic amplification factor is about 1.07 for the pier experiencing the greatest braking force, but can reach up to 1.93 for piers subjected to smaller forces.

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.

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.

Micro-pressure waves are generated and noise is induced when the initial compression wave generated during the entry of a high-speed metro train into a tunnel propagates to the tunnel exit. In some cases, sonic booms may also occur, resulting in serious environmental problems for residents. To effectively control the micro-pressure wave noise at tunnel exits, numerical simulation studies on the acoustic characteristics of micro-pressure wave noise were conducted, and an acoustic suppression structure targeting low-frequency micro-pressure wave noise was proposed. Firstly, large eddy simulation (LES) was employed to obtain near-field unsteady flow field data at the tunnel exit, using the Ffowcs Williams-Hawkings (FW-H) acoustic analogy to predict the type of micro-pressure wave noise sources. Secondly, based on the unsteady flow field data, the acoustic finite element method (AFEM) was utilized to compute the far-field radiation of micro-pressure wave noise and analyze the mitigating effect of acoustic structures of the tunnel exit on micro-pressure wave noise. Finally, the accuracy of the numerical methods was validated through a moving model test. The results indicate that at a train speed of 160 km/h, dipole noise predominates in the micro-pressure wave noise at the tunnel exit. Dipole noise radiates outward in a semi-ellipsoidal shape, with its energy mainly concentrated below 20 Hz and a peak frequency being 4 Hz. The attenuation of dipole noise in the tunnel exit direction follows an exponential decay law. Adding acoustic structures at the tunnel exit significantly reduces micro-pressure wave noise. Specifically, the sound pressure levels (SPLs) outside the tunnel exit across various longitudinal planes decrease by approximately 3 dB. At the designated measurement points, located at 20 m and 50 m, the SPLs are reduced by 3.54 dB and 2.62 dB, respectively.

To address the tendency of spectral segmentation boundaries concentrating on local narrow bands when the empirical Fourier decomposition (EFD) method was applied to bearing fault signals, an order statistics filter (OSF) was used to simplify the frequency spectrum of the acquired bearing vibration signal, and then averaging and sliding processing and pre-segmentation were performed. To address the potential problem of excessive decomposition, a boundary fusion algorithm based on the frequency-domain squared Gini index (FDSGI) was proposed to adaptively determine segmentation boundaries and decomposition modes. The envelope spectrum harmonic significance (ESHS) indicator was used to select the optimal components. Further, bearing fault diagnosis was enabled through envelope spectrum analysis of the optimal components. The comparative test of bearing fault simulation signals and experimental signals demonstrates that empirical Fourier decomposition based on spectrum reconstruction (SREFD) outperforms EFD and empirical wavelet transform (EWT) in terms of spectral segmentation accuracy. The processed signals allow for clearer observation of bearing fault characteristic frequencies and their harmonics, which validates the effectiveness and robustness of the proposed method.

Currently, most Min-Zhe timber arch lounge bridges suffer from the lack of detailed blueprint documentation, leading to unsatisfactory preservation effects and insufficient research on fire spread patterns and disaster prevention. To solve these problems, a digital reconstruction technology based on three-dimensional scanning and BIM parameterization was proposed to construct the digital twins of timber arch lounge bridges, and a BIM-fire dynamics simulator (FDS) was used to analyze the fire spread patterns and fire prevention strategies of such bridges. Firstly, the original point cloud model of Helong Bridge was obtained through on-site three-dimensional scanning, and after registration, denoising, and thinning processes, a BIM parametric digital twin was established to calculate its fire load density. Secondly, the IFC format was adopted to realize the interaction between BIM and FDS, and the fire digital twin of the timber arch lounge bridge was established. Simulation analysis was conducted through parameters such as heat release rate (HRR), fire spread phenomenon, visibility, temperature, and harmful gas concentration, and the fire spread patterns were derived by simulating and analyzing multiple typical fire source scenarios in FDS. Finally, fire prevention optimization strategies such as material flame-retardant treatment, bridge deck non-combustible transformation, and sprinkler system layout were discussed. The research results indicate that the fire load density of the timber arch lounge bridge is as high as 4 017.764 MJ/m², far exceeding that of typical Chinese and foreign buildings, thus posing an extremely high fire risk. Among multiple typical fire source scenarios, excluding HRR mutation values, the HRR peaks of the arch structure and bridge bottom working conditions are stable at 100 MW and 95 MW, respectively. The HRR peaks of the bridge center and bridge head working conditions are stable at 88 MW and 70 MW, respectively. The HRR of the bridge side bottom and bridge top working conditions does not reach the peak within 1 000 seconds, with maximum values of 55 MW and 22 MW. Therefore, the fire risk of ignition under the bridge is the highest, followed by ignition on the bridge deck, while the fire risks of roof ignition and ignition at the bridge side bottom are relatively low. Through fire simulation and quantitative analysis of multiple fire parameters, it is confirmed that the three fire prevention measures can delay the fire spread of timber arch lounge bridges, and the upper and lower fire compartments, wood flame retardancy, and sprinkler systems reduce the HRR peak by 23 MW, 39 MW, and 63 MW, respectively. The research results can serve as the basis for information storage, quantitative analysis of fire spread, and preventive protection of timber arch lounge bridges and provide technical support for the long-term safe operation and maintenance of cultural heritage buildings.

Due to the unique structural form of stone masonry walls in traditional Tibetan architecture, the complexity of the material composition, and the interference of environmental factors, the accurate detection of hidden damage in the wall is extremely challenging. To address the limitations of traditional methods in target signal identification, experimental data obtained from ground-penetrating radar (GPR) testing of Tibetan stone masonry walls were used to verify the reliability of the numerical simulation results. Then, the propagation characteristics of the effective wave were systematically analyzed, with the focus on the effects of different GPR antenna center frequencies, GPR spacing from the wall, and crack width on the echo characteristics. Finally, the successive variational mode decomposition (SVMD) method was applied for signal decomposition and reconstruction. Its stability, applicability in target signal identification, and its advantages over existing techniques were evaluated across varying noise levels and crack widths. The results have shown that when the SVMD method is applied to the noise reduction of GPR signals in masonry walls of traditional Tibetan architecture under specific conditions, it improves the signal-to-noise ratio by 58.36% and 18.67% compared to the empirical mode decomposition (EMD) and variational mode decomposition (VMD) methods, respectively. It can effectively separate the target signals, background wall signals, and noise signals, providing reliable technical support for extracting damage characteristics in masonry walls of traditional Tibetan architecture.

To investigate the complex nonlinear behavior of parabolic two-hinged arches subjected to a midspan concentrated force, a theoretical method was proposed to reveal its rule. Based on the nonlinear strain–displacement relationship of arches in the Cartesian right-angled coordinate system, nonlinear equilibrium differential equations of parabolic two-hinged arches subjected to a midspan concentrated force were derived, as well as the corresponding high-precision approximate analytical solutions of these nonlinear equations. The common rules of complex nonlinear behavior of parabolic two-hinged arches subjected to a midspan concentrated force were investigated by the limitation analysis of these high-precision approximate analytical solutions in discontinuous points: 1) If and only if the modified slenderness ratio is greater than or equal to the limit-pattern critical slenderness ratio, limit-pattern nonlinear behavior occurs in parabolic two-hinged arches subjected to a midspan concentrated force. Moreover, multiple extreme points appear on the limit-pattern nonlinear equilibrium path, and the number of extreme points is positively correlated with the parameter k. 2) When limit-pattern nonlinear behavior occurs in parabolic two-hinged arches subjected to a midspan concentrated force, the limit-pattern nonlinear equilibrium path passes through specific points. The coordinates of these points are fixed and do not change with variations in the modified slenderness ratio. 3) If and only if the modified slenderness ratio is greater than or equal to the bifurcation-pattern critical slenderness ratio, bifurcation-pattern nonlinear behavior occurs in parabolic two-hinged arches subjected to a midspan concentrated force. This bifurcation-pattern nonlinear behavior exhibits multiple equilibrium paths. Comparisons against nonlinear finite element results demonstrate that the proposed approximate analytical solutions of nonlinear equilibrium of parabolic two-hinged arches subjected to a vertical midspan concentrated force have sufficient accuracy, and the rules of complex nonlinear behavior of parabolic two-hinged arches subjected to a midspan concentrated force agree well with nonlinear finite element results. The maximum relative error is 9.05%, which meets the needs of engineering accuracy.

To address the issue that the asymmetric basic type calculation model, which the intersection method relies on in highway alignment design, fails to perform calculations when turning curves include incomplete transition curves, the asymmetric basic type calculation model was used as the foundation. By analyzing the causes of the model’s failure in solving incomplete transition curve scenarios, the structure and solution logic of the calculation model were optimized and improved, and an asymmetric general type calculation model was further proposed. This new model introduced a novel definition of transition curve direction. It classified transition curves into two categories, positive and negative, by judging the relationship between the curvature change trend of the transition curve and the route’s traveling direction. Then, based on the positional order of the transition curve within a single curve, a special local coordinate system was established. Through geometric derivation, the tangential growth value and curve offset value of the incomplete transition curve were obtained, enabling the subsequent use of the asymmetric basic type calculation model for further solution. The research has shown that the asymmetric general type calculation model eliminates the restrictions of the asymmetric basic type model on alignment combination types, allowing the curvature radii at the start and end points of transition curves to be arbitrary values. By comparing the calculation results of the same complex curve segment with those obtained using the traditional element method, the differences in the calculated mileage values and coordinates of the control stakes are both less than 1 mm, which meets the engineering accuracy requirements.

To ensure the safe and efficient operation of full-face tunnel boring machines (TBMs) in complex terrains, it is essential to clarify the load characteristics of cutters in the multi-cutter collaborative rock-breaking condition and to analyze the performance of cutter profiles in different geological strata. Therefore, a numerical discrete element model based on the particle-flow method for the multi-cutter collaborative rock-breaking condition was established. The load characteristics of flat-tipped and circle-tipped cutters under varying rock strength and rotational speeds of cutterheads were investigated. Additionally, multi-cutter rock-breaking experiments were conducted to verify the accuracy of the numerical analysis results. The findings indicate that under a given penetration depth, the circle-tipped cutter exhibits a normal total thrust that is 23%−50% lower than that of the flat-tipped cutter, along with a reduction in rock-breaking volume and specific energy by 10%−20%. The load of cutters at different installation radii varies. The innermost and outermost cutters only collaborate in rock breaking with adjacent single-sided cutters, so the cutting force is approximately 30% higher than that of the adjacent cutter. Consequently, the mean and the standard deviation of cutting forces show a “W”-shaped distribution, with higher values at both ends and lower values in the middle as the installation radius increases. The mean and standard deviation of the normal forces for both cutter profiles are positively correlated. However, at the same level of normal thrust, the flat-tipped cutter exhibits a 37%−50% lower standard deviation of normal force, which means the circle-tipped cutter may lead to more severe vibrations. Additionally, the cutting forces for both types of cutters increase with an elevation in the rotational speed of the cutterhead. The flat-tipped cutter exhibits greater sensitivity to variations in the rotational speed.

To investigate the influence of ground motion uncertainty on the seismic demand and vulnerability of bridge structures and to clarify the propagation of this uncertainty in seismic vulnerability analysis, a quantitative method based on the Bootstrap method was proposed for assessing the uncertainty in the seismic vulnerability of bridges. Firstly, the relationship between the ground motion intensity index and the seismic demand of bridge structures was determined through probabilistic seismic demand analysis. Secondly, by considering the influence of ground motion sample size on the seismic demand model and vulnerability of bridge structures, the Bootstrap method was used to simulate the uncertainties in both probabilistic seismic demand model parameters and vulnerability curves. Finally, by taking a three-span simply supported beam bridge as an example, seismic vulnerability analyses were conducted using 50, 100, and 300 seismic records to quantify the variability of probabilistic seismic demand models and vulnerability under different ground motion samples. The results indicate that the seismic demand and vulnerability of bridge structures are subject to significant uncertainties under the ground motion. When 100 seismic records are used, the variability in failure probability of the bridge under various damage states exceeds 10%, and that under severe damage states reaches up to 30%. In seismic vulnerability analysis of bridges, it is advisable to represent the failure probability of bridge structures under different ground motion intensities as interval random variables to account for variability in seismic vulnerability due to seismic record samples. The Bootstrap method can effectively simulate the uncertainty in the seismic demand and vulnerability of bridge structures, providing an effective approach for statistical uncertainty simulation and seismic vulnerability analysis of probabilistic seismic demand models of bridge structures under small sample sizes.

To enhance the response efficiency of cross-regional emergency rescue under major natural disasters, considering differential disaster severity in affected areas, the optimization of cross-regional emergency supplies dispatching with combined transport was conducted. Firstly, a differentiated disaster classification strategy and a comprehensive evaluation system were proposed. The CRITIC-TOPSIS method was employed to determine the risk level of each region. Then, a bi-level programming model was developed, in which the upper level minimizes the total emergency response time and the lower level maximizes fairness. The upper level incorporated the Beetle Antennae Search to improve the Particle Swarm Optimization algorithm for finding solutions, thereby determining the shortest time and the volume of supplies transported from supply points to distribution centers. This provides basic data and time constraints for the lower level. The lower level uses the NSGA-III to solve the supplies allocation problem, where its results influence the distribution of supplies to affected areas in the upper-level model. This interdependence may lead to adjustments in the upper-level transportation scheme, further optimizing the overall objective. Finanly, taking 5•12 Wenchuan Earthquake as a case study for the simulation, the results indicate that, in terms of the total emergency response time, the scheme considering disaster severity classification is 2.53% shorter than that without considering disaster severity classification. Regarding fairness, the scheme under disaster severity classification shows a positive correlation between the satisfaction rate of emergency supplies demands and the disaster severity level at different disaster-affected points, thereby better reflecting the differentiated strategies based on disaster severity levels and the fairness of emergency supplies dispatch.

In order to reveal the air pressure variation law and the subsidence mechanism in covered karst soil cave induced by precipitation, according to the theory of short gas pipe submerged flow, calculation methods of gas seepage flow, air pressure, and stability coefficient in ellipsoid cave were obtained. MATLAB program was compiled based on finite difference numerical solutions. The feasibility of calculation methods was verified through indoor model tests of subsidence induced by precipitation in a karst soil cave. The example analysis has shown that the gas state parameters (flow and pressure) and stability coefficient of the cave evolved from the initial state to drastic variations in the early stage of precipitation, then shifted to gradual changes in the later stage, and finally returned to the initial state. The maximum peak flow of soil cave induced by precipitation is positively correlated with the length of the semi-minor axis b of the ellipsoid cave, and negatively correlated with the ratio of semi-major axis and semi-minor axis $ a / b $, and arch height. The minimum peak air pressure is positively correlated with $ a / b $, $ b $, and arch height. The arrival time of the minimum peak air pressure is positively correlated with arch height, and negatively correlated with $ a / b $, while the effect of $ b $ is negligible. The minimum peak stability coefficient of soil cave induced by precipitation is positively correlated with $ a / b $ and arch height and negatively correlated with $ b $. The arrival time of the minimum peak stability coefficient is positively correlated with arch height, and negatively correlated with $ a / b $, while the effect of $ b $is negligible.

For the purpose of improving the conveying efficiency of the vacuum pneumatic slagging system of the shaft boring machine (SBM) and addressing low conveying efficiency caused by the mismatch between the parameters of the slagging system and the rock slag, the effect of conveying system parameters on slagging efficiency was investigated based on single factor analysis method and orthogonal test method. Firstly, a parameter and pressure loss calculation model for the vacuum pneumatic slagging system was constructed based on fluid mechanics to determine the key parameters of the system. Then, the Fluent software was used to simulate the process of vacuum pneumatic slagging, and the outlet velocity of rock slag and the average gas pressure drop were taken as the consideration index of slag conveying efficiency. The single factor analysis method was used to study the influence of four factors, including inner diameter of pipe, gas velocity, rock slag particle size, and rock slag density, on the conveying efficiency. The multi-factor analysis was carried out based on the orthogonal test method, and the non-dominated sorting genetic algorithm was applied to obtain the Pareto frontier solution set. Finally, the slag conveying efficiency test of the vacuum pneumatic slagging system was carried out. The results show that the influence of gas velocity and rock slag particle size on the outlet velocity of rock slag is the most significant, and the influence of inner diameter of pipe and gas velocity on the average gas pressure drop is the most significant. In addition, the average gas pressure drop and the outlet velocity of rock slag cannot reach the optimum simultaneously. When the minimum value of the outlet velocity of rock slag is selected as the best economic conveying point, the optimal combination of conveying parameters is as follows: rock slag particle size of 10 mm, inner diameter of pipe of 150 mm, gas velocity of 40 m/s. The research results can provide a reference for the construction application of the vacuum pneumatic slagging system of SBM.

To construct a monitoring system of preventive protection for ancient masonry arch bridges, a monitoring method for risk identification was investigated. Three indicators, which were damage assessment grade, Von Mises stress, and component importance, were used to quantify the most severe damage, unfavorable stress, and critical components. The monitoring target values were solved for the 64 components of the Lugou Bridge based on the loss matrix, force matrix, and importance matrix, and a sensor placement scheme was made accordingly. The results have shown that the method can identify high-value components for monitoring and capture the seasonal fluctuation patterns and cumulative damage risks of Lugou Bridge. Except for the settlement, monitoring data exhibits significant seasonal fluctuation patterns, with peaks in June to July and troughs in January each year. The ratio of winter to summer peak values is 1.577 for strain sensors, 0.849 for displacement sensors at the seventh pier from the east, 1.206 for displacement sensors at the ninth pier from the east, and 1.549 for transverse inclination sensors. The average seasonal fluctuation ratio ranges from 20% to 60%. The settlement of the fifth pier from the East is 1.156 times that of the ninth pier from the East. Sensors near the central arch bridge or located in severely damaged areas have higher peak values among the same type of sensors. The study provides a scientific basis for the monitoring of preventive conservation of ancient masonry arch bridges.

To achieve digital modeling and performance evaluation of ancient stone arch bridges, this study researches the reverse modeling method based on Unmanned Aerial Vehicle (UAV) oblique photography and image contour extraction technology. Firstly, a UAV is used to collect multi-view sequence images of the stone arch bridge. Secondly, the Structure from Motion (SfM) and Multi-View Stereo (MVS) algorithms are used to construct three-dimensional (3D) model of stone arch bridges. Then, based on the characteristics of color difference between stone blocks and mortar as well as the geometric regularity of stone blocks, strategies of color difference enhancement and small-area impurity filtering are proposed to improve the Canny edge detection. Cyclic quadrilateral recognition and shape optimization are introduced to improve the polygon approximation algorithm, so as to realize the automatic identification of surface contours. Subsequently, the real scale is calibrated based on ground control points, and the finite element model is generated through parametric modeling using the extracted contour coordinates. Finally, the proposed method is applied to model Toulong Bridge and analyze its performance, which is compared with experimental results. The study shows that no obvious diseases are detected on the surface of the 3D real-scene model of Toulong Bridge, with a maximum dimensional error of 0.8%; the maximum calculation error of the deflection is 2.1% by the finite element model. These indicate that the method can accurately reflect the geometric shape and mechanical properties of ancient stone arch bridges, providing technical support for their digital protection and performance evaluation.

The welded frame-type bogie is a newly developed product in recent years, and its operational safety and reliability are crucial. A fatigue reliability assessment of the welded frame-type bogie frames was carried out. A fatigue life assessment procedure for welded structures was proposed based on the equivalent structural stress (ESS) method and the main S-N curve model, and a formula for determining the stress state of welded structures under multiple loads was derived. According to the BS EN15085-3:2007 standard for the design of welded structures in railway vehicles, combined with finite element model simulations and fatigue test data, the stress state and fatigue life of the bogie frame weld joints were comprehensively analyzed. A finite element model including weld details was established to simulate the stress state under actual operating conditions. Fatigue life simulations were performed using the load spectrum provided by the fatigue test outline, and the stress state level of the weld joints was determined according to the standards to assess the quality grade and inspection grade of the welds. Fatigue tests of the bogie frames were conducted according to the EN13749:2011 standard. The results show that the ESS method, combined with the BS EN15085 standard, can accurately predict the fatigue life of weld joints. The total damage of key welds in the bogie frames is less than 1, meeting the design requirements for fatigue life. After fatigue tests, no cracks are detected by magnetic particle inspection, meeting the fatigue strength requirements. The maximum stress factor of the frame welds calculated by ESS is 0.939. The stress state level of each key weld is clarified based on the stress factor values, providing a basis for optimizing the quality and inspection grade of the welds.

To investigate the dynamic performance of prefabricated slab tracks (PSTs) applied in metro turnout areas, an analysis was conducted based on the interlayer contact relationship between the slab and the pad considering the constraint effect, as well as the multi-point contact theory in turnout areas. By taking a typical PST as an example, the safety performance in terms of concrete strength and ultimate bending moment capacity under train load was verified. A coupled vehicle–turnout–tunnel dynamic model was established, and a self-developed co-simulation program was used to study the system dynamic responses and vibration reduction effects during train passage through the metro turnout areas under different slab thicknesses and pad stiffnesses. The results show that under the load condition of metro type-A trains, the maximum tensile stresses in the track slab and self-compacting concrete layer are 2.48 MPa and 1.89 MPa, respectively. The cross-section bending moment capacities of longitudinal and transverse reinforcement in turnout areas are significantly greater than the lateral and longitudinal load moments. When the train speed is 55 km/h and the slab thickness increases from 180 mm to 300 mm, the insertion losses are 8.1 dB, 9.3 dB, 10.0 dB, and 10.7 dB, and the dynamic responses all meet the safety requirements. When the slab thickness is 260 mm and the pad stiffness increases from 0.01 N/mm³ to 0.04 N/mm³, the insertion losses are 15.0 dB, 10.0 dB, 8.0 dB, and 5.2 dB, respectively. At a stiffness of 0.01 N/mm³, the vertical displacements of the switch rail and nose rail are 4.1 mm and 5.2 mm, respectively. Considering the safety performance, economic benefits, and vibration reduction effects comprehensively, it is recommended that the slab thickness of the PST is between 220 mm to 260 mm, and the pad stiffness range from 0.019 to 0.030 N/mm³.

To study the self-sensing performance of ultra-high performance concrete (UHPC) mixed with steel fibers and multi-walled carbon nanotubes (MWCNTs) under different cyclic stress amplitudes, experimental studies were conducted on UHPC specimens with a steel fiber volume content of 2% and varying MWCNT contents. The results show that the initial resistivity of UHPC increases first and then decreases with the increase in MWCNT content, and the addition of 0.15% MWCNTs improves the conductivity of UHPC. When the MWCNT content is 0.15%, the sample exhibits optimal repeatability, with a repeatability coefficient of 0.019, and the linearity change of alternating current (AC) resistance presents a strong linear relationship with stress, with a linearity of 0.97. The stress sensitivity and strain sensitivity of the samples UHPC0 and UHPC0.05 first increase and then decrease with the increase in stress, while the stress sensitivity and strain sensitivity of samples UHPC0.1 and UHPC0.15 show a gradually decreasing trend. The maximum strain sensitivity and stress sensitivity of UHPC0.15 are 71.6% and 0.16%/MPa under different cyclic stress amplitudes, both appearing at a stress of 10 MPa. When the content of MWCNTs is 0.15%, UHPC exhibits the best self-sensing performance.

To investigate the influence of the axial compression ratio on the hysteretic properties of the steel shell-concrete composite pylon, based on the composite pylon structure without longitudinal rebars, three hysteretic specimens were designed with the axial compression ratio as the research parameter. Through testing, the hysteresis curves, failure characteristics, and strain development of each specimen were obtained, and the mechanical behavior under large eccentric failure was analyzed. A finite element model was then established using ABAQUS for further analysis, and the boundary failure conditions of the pylon section were determined. Then, calculation formulas for the axial compression and bending moment of the section under boundary failure were proposed, and the effect of the steel ratio and concrete strength on the axial compression ratio under boundary failure was discussed. The research results indicate that under large eccentric failure, the section stiffness, peak bearing capacity, and energy dissipation capacity increase with the axial compression ratio. When the axial compression ratio increases from 0.056 to 0.166, the stiffness and the flexural capacity of the specimen improve by 20%. The boundary failure condition of the composite pylon section is defined by the yielding of the tensile-side steel shell and crushing of the compressive-side concrete. Under boundary failure, the section achieves its highest flexural capacity and stiffness. The proposed calculation formulas provide an accurate assessment of the axial compression ratio and flexural capacity under boundary failure. Both an increase in steel ratio and concrete strength lead to a reduction in the axial compression ratio at boundary failure. The axial compression ratio under boundary failure in the composite pylon section falls within the range of 0.44–0.56, making it well-suited for long-span suspension bridge towers with higher axial compression ratios.

A convolutional-bidirectional long short-term memory neural network-attention mechanism (CNN-BiLSTM-AM) prediction model optimized by the northern goshawk optimization (NGO) algorithm for landslide displacement was proposed to address challenges that a single prediction model fails to effectively extract complex sequence features and that manual parameter tuning tends to fall into local optima in current landslide displacement prediction research. Firstly, according to the factors affecting the landslide, the multivariate empirical mode decomposition (MEMD) algorithm was used to decompose various landslide displacement data into trend and periodic components. The trend components were predicted using the autoregressive integrated moving average (ARIMA) method. For the periodic components, influencing factors were identified through the gray correlation degree, and a CNN-BiLSTM-AM combined model was constructed for prediction. The optimal hyperparameters of this model were obtained through NGO. Then, by considering the lag of the periodic components, the Spearman correlation coefficient was used to select the optimal lagged displacement to further enhance the model’s predictive performance. Finally, the model was validated using monitoring data of the Tuojiashan Landslide in Weiyuan, Gansu Province. The results show that the RMSE and MAE of the total displacement prediction of the Tuojiashan landslide are as low as 0.22 mm and 0.37 mm, respectively, showing the prediction accuracy of the correction, while the R² reaches 0.98, which fully verifies the validity and reliability of the proposed model in landslide displacement prediction.

To investigate the compression performance of cold-formed thin-walled steel T-shaped composite edge columns with web stiffeners, axial and eccentric compression tests were conducted on eight groups of specimens. The influence of “V”-shaped longitudinal stiffening ribs on the failure modes and bearing capacity of the components were revealed through finite element model validation and parameter analysis, and an improved calculation method for bearing capacity was proposed. The results indicate that under axial compression, local buckling first appears in the web of the T-shaped composite edge column without stiffening ribs, ultimately leading to overall crushing failure. After adding “V”-shaped stiffening ribs, the stiffness of the single-limb C-shaped steel web is enhanced; the local buckling mode of the T-shaped composite edge column is improved, and the bearing capacity increases by approximately 15%. As the eccentricity increases, the failure modes of the specimens remain similar, and the ultimate bearing capacity shows a decreasing trend. The bearing capacities under axial and eccentric compression predicted by the effective width method are conservative. Both the finite element results and the test results are greater than the calculated results, with the average ratios being 1.238 and 1.143, respectively. After modification, the ratio of the results predicted by the effective width method to the simulated values ranges from 1.000 to 1.074, indicating high prediction accuracy.

To study the effect of cable breakage on the impact response of concrete-filled steel tube arch bridges and the difference in safety factor requirements between carbon fiber reinforced polymer (CFRP) cables and steel cables, the dynamic response of a railway bridge under accidental cable breakage was analyzed. A spatial finite element model was established by ANSYS. The force characteristic variations of the residual structure of the arch bridge under five cable breakage conditions were studied based on the equivalent unloading method. The impact sensitivity of the structure after cable breakage was evaluated by dynamic amplification factor (D_DAF) and demand capacity ratio (D_DCR). The effects of different cable materials, namely steel cables and carbon cables, on the dynamic response of the arch bridge were compared. The results show that the dynamic response of the main girder and the stress of the arch rib are greatly affected by the position and number of cable breakages. The redistribution ratio of the cable force is inversely proportional to the distance from the broken cable area and the cable length and directly proportional to the number of failed cables. The D_DAF of the arch bridge with carbon cables is higher than that of the arch bridge with steel cables, ranging from 1.19 to 1.43. The D_DCR of the remaining cable after cable breakage does not exceed 1, indicating large redundancy. Compared with bridges with steel cables, arch bridges with carbon cables require smaller safety factors under cable breakage conditions, ranging from 1.0 to 1.5.

To realize the requirements of minor post-earthquake damage, rapid repair, and functional recovery of reinforced concrete frame structures, three 1/2 scaled concrete frames were designed. One was an ordinary reinforced concrete frame, and two were concrete frames reinforced with high-strength steel bars (HG bars). Quasi-static tests were carried out to study the failure modes of the frames under cyclic loading. The effects of beams and columns with HG bars on seismic performance indexes including hysteretic curves, skeleton curves, residual deformation, repairability, and self-centering ability, were discussed. The results show that the use of HG bars in beams and columns effectively improves the overall bearing capacity and deformation capacity of the frame. Compared with the ordinary reinforced concrete frame, specimens NHGS2.5A15 and HGHGS2.5A15 show good displacement hardening effects. Their ultimate bearing capacities increase by 23% and 57%, respectively, and the displacement corresponding to ultimate load increases by 50% and 60%, respectively. These specimens have smaller residual deformations and higher reparability, and they demonstrate good self-centering capability and repairability performance.

The cyclic dynamic stress generated during train operation presents a significant challenge to the dynamic strength of subgrade fill materials. Existing research has mostly simulated train loads using continuous loading methods, which fails to fully reflect the intermittency of these loads. To investigate the differences in dynamic strength of loess subgrade under continuous and intermittent loading, a series of consolidated undrained tests under continuous and intermittent loading conditions were conducted using a GDS dynamic triaxial apparatus. The influences of confining pressure and dynamic stress amplitude on the dynamic strength of the soil were examined. The effects of different loading methods on the dynamic strength and strength parameters of the subgrade loess were compared. The experimental results indicate that the dynamic strength of the loess subgrade increases with higher confining pressure, but the growth rate diminishes gradually. Both dynamic cohesion (c_d) and dynamic friction angle ($ {\varphi _{\text{d}}} $) decrease with the increase in the failure cycles (lg N_f), showing an overall linear relationship. Under intermittent loading, the soil exhibits a marked increase in c_d and$ {\varphi _{\text{d}}} $compared to continuous loading, with c_d increasing by 2.18%–5.09% and $ {\varphi _{\text{d}}} $ by 4.03%–13.78%. By normalizing the dynamic strength using the static triaxial shear strength, an empirical formula for the dynamic strength of the loess subgrade based on static strength is proposed, which provides a critical basis for assessing the stability of the subgrade under dynamic loads.

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

To study the problem of rail corrugation-induced clip fracture in metro sections with double-layer nonlinear vibration damping fasteners, by taking the typical GJ-Ⅲ type fastener as the research object, field investigation and numerical simulation were combined to analyze the causes and influencing factors of fastener clip fracture in this section. Firstly, a finite element model of the wheel–rail–fastener system incorporating rail corrugation was constructed. Subsequently, the instantaneous dynamic analysis method was employed to investigate the causes of fastener clip failure in the rail corrugation section from the perspective of resonance response. Then, based on cumulative fatigue damage theory, the fatigue life of the fastener clips on both sides of the low rail was compared under conditions with and without rail corrugation from the perspective of fatigue characteristics. Finally, a parametric analysis was conducted to explore the influence of external rail corrugation excitation and internal characteristics of fastening components on the fatigue life of the fastener clip. The results show that the high-frequency excitation induced by rail corrugation leads to the resonance in the GJ-III type fastener clip, which is the main cause of the clip fracture. Rail corrugation aggravates the vibration responses of the wheel–rail system, reduces the clip’s service life, and has a more serious impact on the outer clip of the low rail. It cuts the fatigue life to 2.18 × 10⁵ cycles, which is only 4.36% of the design life. In terms of external excitation from rail corrugation, reducing the corrugation depth and increasing the corrugation wavelength can extend the fatigue life of the clip; moreover, when the corrugation wavelength exceeds 40 mm, the fatigue life improves significantly. In terms of the internal characteristics of fastener components, reducing the elastic modulus of the clip, increasing the Poisson’s ratio of both the clip and the rubber pad, and increasing the rubber pad’s elastic modulus can reduce the fatigue damage of the clip to some extent, thereby mitigating clip fracture in the rail corrugation section.

To develop an optimal sensor placement method for ancient stone arch bridges, by taking the Beijing Lugou Bridge, a national key cultural relics protection unit, as an example, a sensor optimization model considering initial damage and random material parameters was established. A fitness function design and solution method considering complex monitoring targets was proposed, along with a meta-genetic algorithm based on the concept of meta-learning for solving the sensor placement optimization problem. The proposed method was compared with two optimization methods based on conventional genetic algorithms, achieving optimal sensor placement for ancient stone arch bridges. The results show that the proposed method offers better parameter identification capability, damage sensitivity, and information redundancy level. When the noise level is within 5%, the sensor placement scheme given by the meta-genetic algorithm can successfully detect the damage, while the other two methods achieve only a 60.0% success rate. When the noise level reaches 10%, the meta-genetic algorithm can detect 60.0% of the damage, while the other two methods fail to detect damage effectively.

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.

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.

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 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.

As one of the important contents of health monitoring of concrete structure, crack detection reflects the stress and damage state of the structure, and the detection and evaluation is the core technology to ensure structure safety for service. The traditional detection methods have limited coverage in time and space and are greatly affected by environmental and altitude factors, so the detection efficiency and accuracy are relatively low. Additionally, they are dependent on subjective judgment, which is easy to cause missed detection and false detection. The detection method based on computer vision is equipped with digital imaging equipment for data acquisition, input, and image processing to automatically analyze and identify the concrete surface, which has the advantages of high efficiency, accuracy, and objectivity and is widely used in the field of intelligent crack detection of concrete structures. The principle, method, and application of concrete crack detection based on computer vision were described in detail from four aspects: image acquisition, image processing, recognition algorithm, and structure evaluation. Besides, the application of crack image acquisition equipment and various image preprocessing methods in digital imaging technology was reviewed comprehensively, and the advantages, disadvantages, and applicability of different recognition algorithms were analyzed. At the same time, the shortcomings of current research were summarized, and the challenges and problems faced by the application of computer vision technology for equipment intelligence and lightweight network were analyzed. Then the corresponding solutions were proposed. Prospects are also presented from the aspects of multi-source data fusion and utilization, lightweight intelligent equipment, digital imaging and crack mapping, and high-efficiency and real-time structure evaluation.