To meet the requirements for long endurance and high autonomy of small unmanned carrier vehicles (unmanned aerial vehicles, unmanned ground vehicles, and unmanned surface vehicles), distributed energy harvesting technology has become a crucial approach to overcoming energy supply bottlenecks. First, the basic principles of distributed energy harvesting technologies were reviewed, mainly covering the conversion mechanisms and key material advances of ambient energy sources such as solar, wind, vibration, and wave energy. Then, the structural integration and application characteristics of photovoltaic, electromagnetic, piezoelectric, and triboelectric harvesting technologies in typical scenarios involving unmanned aerial vehicles, unmanned ground vehicles, and unmanned surface vehicles were deeply analyzed. The research status of multi-source hybrid harvesting and self-powered systems was summarized, and key challenges, such as great conversion efficiency fluctuations due to environmental conditions, low system integration, and the lack of unified evaluation standards, were highlighted. Finally, the technological evolution trends centering on multi-source fusion and intelligent scheduling were discussed, and a design paradigm based on the “intelligent energy internet” was proposed, outlining the future development direction of converting discrete ambient energy into a stable supply through cross-platform collaboration and data-driven optimization.

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

To address the issues of excessive deformation and prestress loss caused by stress concentration at the external anchor head of traditional prestressed anchor cables in fragmented rock slope reinforcement, an improved self-locking prestressed anchor cable was developed by innovating the clip structure of the self-locking device to enhance anchoring performance. Laboratory tensioning and locking tests were conducted to verify the mechanical locking effect of the improved anchor cable. Subsequently, a typical fragmented rock slope project in Zhangjiajie, Hunan Province, was selected for in-situ tensioning and locking tests. Distributed optical fiber sensing testing technology was employed to monitor the entire tensioning and locking process along the full length of the grout for three improved self-locking tension-type prestressed anchor cables. The axial strain distribution patterns of the grout at various stages were obtained, and the shear stress distribution was derived. Simultaneously, the strain of the steel pipe within the self-locking device was tested and analyzed. The results indicate that during the tensioning process, the inner anchorage section exhibits the typical mechanical characteristics of a tension-type anchor cable. The axial strain gradually develops from the proximal end of the inner anchorage section and continuously propagates backward as the load increases. At this stage, the self-locking device has no influence on the stress state of the inner anchorage section. Within 24 hours after unloading and locking, the strain distribution of the self-locking anchorage section remains stable without significant prestress loss, demonstrating excellent anchoring and locking efficacy. Because the test anchor cable comprises two anchorage units, the interaction between these units causes notable tensile strain, negative shear stress, and an increase in shear stress at the distal end of the M_S1 unit. Affected by uncertainties such as on-site construction and measurement, the shear stress distribution is uneven, with a peak value of approximately 0.3 MPa, and the peak position of the M_S2 unit is slightly posterior to that of the M_S1 unit. In addition, the strain of the self-locking steel pipe starts from the end of the dedicated anchorage and gradually transitions from compressive strain to tensile strain with increasing distance; the strain value increases proportionally with the tensioning load. These findings provide a reference for further optimizing the support structures of fragmented rock slopes and enhancing the anchoring performance of self-locking prestressed anchor cables.

The evaluation of maintenance effects is an important reflection of the maintenance support capability of electromechanical products and a key aspect of maintenance management. Traditional methods are limited in handling high-dimensional data and interactions among indicators, making it difficult to accurately reflect maintenance effects. To solve these problems, a new method for evaluating maintenance effects that integrates interval-valued intuitionistic fuzzy sets (IVIFS) and the DEMATEL-based analytic network process (DANP) was proposed. A multi-level maintenance effect evaluation index system was established based on the simple structure and ease of fault diagnosis of electromechanical product meta-action units. In an interval-valued intuitionistic fuzzy environment, the decision-making trial and evaluation laboratory (DEMATEL) method was applied to analyze interdependencies among indicators, and the analytic network process (ANP) was used to determine their weights. Maintenance effects were quantitatively evaluated and ranked by calculating the weighted distances between candidate maintenance plans and the ideal plan. In a case study involving the worm rotation meta-action unit of a CNC grinding machine, three maintenance methods were comprehensively evaluated and ranked. The stability and feasibility of the method were verified by varying the weights assigned to experts and comparing different methods. The results show that the evaluation model integrating IVIF-DANP can accurately differentiate the relative merits of different maintenance plans.

With the rapid development of industrial automation and intelligent manufacturing, flexible manipulators have been widely used in the aerospace and precision instrument manufacturing industries. To address the challenges of achieving precise positioning and suppressing vibrations in flexible manipulators with unknown parameters, a sliding mode control method based on a time-delay estimator (TDE) is proposed. First, the dynamic characteristics of the system are analyzed and the dynamic model is established. On this basis, a sliding mode controller is designed, and the unknown system dynamics are estimated by using a time-delay estimator. Furthermore, to enhance the system’s control performance, a term for suppressing the load deflection angle is incorporated into the control law to effectively reduce the effects of flexible vibrations. Subsequently, a rigorous stability analysis of the closed-loop system is conducted, and the convergence of the system state variables is proved. Finally, simulation experiments were conducted to verify the effectiveness of the proposed method. The results show that the proposed control method can achieve accurate positioning while effectively suppressing flexible vibrations.

To investigate the unsteady fluid-structure interaction (FSI) characteristics of the NACA66 hydrofoil during typical cavitation stages, its hydrodynamic and flow-induced vibration characteristics were numerically calculated using an unsteady cavitating FSI model. First, an unsteady cavitating FSI numerical model was established, and the calculated results were compared with the experimental results reported by Wu et al. to verify the accuracy of the model. Second, the characteristics of typical cavitation flow pattern distributions and the evolution of the unsteady flow-field structure were analyzed using the numerical method. Finally, the hydrodynamic and flow-induced vibration characteristics during different typical cavitation stages were further investigated. The results show that, during typical cavitation stages, the maximum cavity length increases as the cavitation number decreases, and cloud cavitation exhibits pronounced periodicity. The lift and drag coefficients vary with the cavitation number. The maximum tip vibration displacement and velocity of the hydrofoil remain relatively high during incipient cavitation but remain low during supercavitation due to the effect of full cavity coverage. During cloud cavitation, the maximum vibration displacement and velocity exhibit substantial periodic fluctuations due to unsteady flow effects. The maximum tip displacement and maximum tip torsion angle of the hydrofoil are linearly related to the lift and pitching moment, respectively. In addition, the flow-induced vibration frequency of the hydrofoil is approximately equal to the cavitation shedding frequency, and the vibration frequency decreases as the cavitation number decreases.

To address DC interference in surrounding power systems and damage to urban pipeline networks caused by stray currents, a novel optimization scheme for the stray current collection network is proposed, in which a continuous cable is used to connect the trackbed reinforcement. The underlying mechanism through which this scheme influences the effectiveness of stray current protection is also systematically investigated. Based on the proposed continuous cable connection scheme, a four-layer return current model of a DC traction power supply system was developed to account for the stray current collection network. The boundary element method was then employed to couple the leakage current from the stray current collection network with the return current system model, thus improving simulation accuracy. The simulation accuracy of the proposed model was verified by scaled simulation experiments. A metro project in China was used as a case study to quantitatively analyze the effects of the conventional cross-connection method using 95 mm² cables and the continuous cable connection method on secondary stray current and the earth potential gradient. The results show that the average simulation error is 11.76%. When a 95 mm² cable is used directly for cross-connection and the rail-to-earth transition resistance is less than 7.72 Ω•km, the earth potential gradient along the entire line remains below 2.5 mV/m. When a 120 mm² continuous cable is used for connection and the rail-to-earth transition resistance is less than 5.37 Ω•km, the earth potential gradient along the entire line remains below 2.5 mV/m. Using a continuous cable connection can significantly reduce stray current. Using a 120 mm² continuous cable for connection reduces the secondary stray current by 36.59% and the earth potential gradient by 35.28% overall. Using a 200 mm² continuous cable for connection reduces the secondary stray current by 47.30% and the earth potential gradient by 46.89% overall.

Existing metro stray-current leakage location methods often treat longitudinal rail resistance as deterministic and ignore its uncertainty caused by material aging, joint resistance, and environmental factors, which reduces location accuracy and generalization performance. Based on measured longitudinal rail resistance data from a metro system, a method that accounts for the probabilistic characteristics of longitudinal rail resistance was proposed for locating stray-current leakage. Kernel density estimation was used to establish the probability distribution model of longitudinal rail resistance. Monte Carlo methods were then used to simulate uncertainty in longitudinal rail resistance, and a rail-earth resistance network model was constructed. Building on this model, a method was proposed to calculate the distribution of rail-to-earth transition resistance or conductance using a hybrid genetic algorithm-particle swarm optimization algorithm, and a stepwise strategy was developed for locating stray-current leakage. The strategy first identified the inter-station section containing the leakage position through coarse localization and estimated the distribution of longitudinal rail resistance by selecting the solutions with the best fitness values. The leakage zone within the identified section was then determined through stepwise subdivision. During the location process, the leakage position was identified by calculating the probability that rail-to-earth transition conductance along the line exceeds a threshold. Comparisons of the location results with simulated leakage zones show that the proposed method can accurately identify the inter-station section containing the leakage zone when longitudinal rail resistance is nonuniformly distributed and leakage severity and range vary. The location deviation is less than 30%, and the average relative error in estimating longitudinal rail resistance is less than 5% in the presence of measurement noise, indicating strong robustness and practical engineering applicability.

Active stray current mitigation devices show considerable potential for application in rail transit systems. However, the arrangement of these mitigation devices within power supply sections cannot effectively accommodate dynamic changes in stray current distribution, making it difficult to maintain effective stray current mitigation under peak current conditions during train traction or braking. Therefore, an optimal configuration strategy for these active stray current mitigation devices within power supply sections was proposed, using a DC autotransformer (DCAT)-based traction power supply system as an example. First, the rail transit traction power supply system model was established, and the suppression ratios of stray current and rail potential were derived to reveal the influence of these active devices on both stray current and rail potential distributions. Second, based on train operating characteristics, the optimal configuration principles incorporating offset enhancement, symmetric distribution, and peak response were proposed. The optimal installation positions of these active devices were determined by defining the optimized offset ratio, and the mitigation performance for stray current and rail potential in the system was compared before and after configuration optimization. Finally, the Beijing Metro Yizhuang Line was selected as a case study to validate the proposed strategy through simulations. The results show that the optimal configuration strategy significantly improves the mitigation performance without increasing the number of active devices. The error between simulation results and theoretical calculations is controlled within 3%. After configuration optimization, under traction and braking conditions, the maximum rail potential at the traction substation drops from 19.4% and 24.5% to 5.9% and 8.1%, respectively, while the maximum stray current drops from 53.1% and 66.5% to 19.7% and 26.6%, respectively, relative to the corresponding values in the conventional system.

To address the vulnerability of license plate recognition (LPR) data in intelligent transportation systems (ITS) to implicit errors, such as character misrecognition and missed vehicle captures, and the lack of methods for proactively identifying these errors, this study aims to develop a detection method that can proactively and accurately identify LPR devices exhibiting abnormal behavior, thus improving overall data quality and providing decision support for equipment operation and maintenance. First, topological neighborhood relationships between devices were defined using path data derived from vehicle trip chains connecting consecutive LPR checkpoints in the road network, and multidimensional neighbor entropy feature indicators, including total entropy, upstream and downstream neighbor entropy, and asymmetric entropy, were constructed accordingly. Second, a candidate set of abnormal devices suspected of misrecognition or missed captures was initially identified by detecting distortions in neighborhood distributions and fluctuations in vehicle counts caused by implicit errors. Then, spatiotemporal constraints were introduced for cross-verification. Misrecognition devices were identified using physical speed limits, while missed capture devices were identified by incorporating road network topology and frequency-direction consistency constraints. Finally, anomaly confidence scores were calculated for each LPR device, and the final sets of misrecognition and missed capture devices were obtained. Multi-scenario simulation experiments conducted on an actual urban road network show that, across various complex scenarios with different misrecognition and missed capture probabilities and abnormal device counts, the precision of missed capture device identification exceeds 0.8, the recall of misrecognition device identification reaches 1.0, and stable and satisfactory identification performance is maintained under mixed anomaly conditions where both errors coexist.

A dual-parameter compensation method based on thermo-mechanical coupling mechanisms was proposed to suppress the thermally induced drift of large-scale fiber optic balances caused by non-uniform temperature fields in long-duration wind tunnel tests and improve aerodynamic force measurement accuracy. Theoretical modeling was performed to reveal the synergistic deformation mechanism of elastic elements and floating frames under the coupling action of thermal expansion and structural constraints in non-uniform temperature fields. Constraint forces neglected by traditional models were identified as the key factor limiting compensation accuracy. Finite element simulation was adopted to analyze the differential thermal response laws of different measurement channels in uniform temperature rise and temperature difference conditions. A compensation model based on the temperature and temperature difference of symmetrically arranged elastic elements was further built, and the directly measurable dual parameters were employed to indirectly characterize internal constraint force effects. Static and dynamic temperature calibrations of fiber optic balances were conducted to obtain temperature sensitivity coefficients of each balance component, and a temperature history correction formula for elastic elements was fitted to eliminate response delay induced by thermal inertia. Thirty-second long-duration force measurement tests were conducted in a blowdown wind tunnel to validate the compensation method. Test results show that the aerodynamic force measurement errors of three measured components (axial force, normal force, and pitching moment) caused by thermal drift decrease from 18.87%, 85.37%, and 11.67% before compensation to 3.19%, 5.63%, and 1.86%, respectively. The results verify the high-accuracy compensation capability of this method under non-uniform temperature fields, providing a practically applicable temperature compensation scheme for long-duration wind tunnel force measurement tests.

The concept of equivalent grade sections was proposed and its reasonable equivalent method was investigated to facilitate the representation and maintenance management of track longitudinal profiles on kilometer-scale high-speed railway bridges during operation. Additionally, the objective includes addressing following problems. There is large deviation between actual and designed longitudinal profiles caused by manufacturing deviations, construction errors, and limited ballast adjustment capacity, which necessitates modification to a continuous short-slope configuration. Temperature loads during operation induce bridge deflections larger at mid-span and smaller at both ends. The actual longitudinal profile evolves into a high-order spatial curve, posing challenges to track maintenance management. By taking the tracks on two in-service kilometer-scale high-speed railway bridges as examples, four equivalent grade sections—the single-grade section, two-grade section, multi-grade section, and 200 m continuous grade section—were first established by comparing grade section lengths and mid-span elevations, simplifying the actual high-order spatial curve profile into a conventional combination of grade sections and vertical curves. Then, key indicators such as acceleration and ride comfort in actual and equivalent longitudinal profile conditions were calculated and compared. Finally, considering the need for simplified track management, the reasonable equivalent method was determined. The results show that for the Wufengshan Yangtze River Bridge, the maximum acceleration deviation between the single-grade equivalent and measured profiles is no more than 0.2 m/s², and the ratio of resistance difference to tractive force is no more than 15%. For the Husutong Yangtze River Bridge, the maximum acceleration deviation is no more than 0.1 m/s², and the ratio of resistance difference to tractive force is no more than 8%. The single-grade equivalent for both bridges is basically equivalent to the measured profile and provides a more intuitive representation. Considering train traction capacity, ride comfort, and the need for simplified on-site management, the single-grade equivalent is recommended as the basis for track management during operation.

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

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

Shaking table model tests were conducted on the Bailong deposit bank slope of the Lianghekou Hydropower Station to reveal the dynamic instability mechanism of reservoir bank deposit slopes under the combined action of impoundment and earthquakes. The dynamic response, energy evolution, and whole deformation-failure process of the bank slope in coupling conditions were analyzed. Wenchuan seismic waves with step-increased peak acceleration were adopted for excitation tests. Acceleration and pore water pressure monitoring, together with Hilbert-Huang transform time-frequency analysis, were applied to identify the internal damage evolution of the slope mass. The results show that significant local amplification occurs near the water level, besides the dynamic amplification at the slope crest in impoundment conditions. Low-frequency energy near the water level is obviously higher than that in the middle and upper slopes, and impoundment aggravates the accumulation of low-frequency energy in this zone. Pore water pressure in the weak interlayer rises sharply when seismic peak acceleration exceeds 0.5 g, which reduces the effective stress of the soil mass. Marginal spectrum analysis indicates that slope damage is initiated near the water level and slope crest, and propagates upward with the increasing earthquake strength. Under the combined action of impoundment and earthquakes, deformation and failure first take place near the water level. Continuous damage develops in the upper-slope mass, and traction-type sliding failure eventually occurs along the weak interlayer. The slope evolution includes four successive stages: erosion deformation, local damage accumulation, local deformation and failure, and overall sliding instability. The findings provide experimental support for seismic stability evaluation of similar deposit bank slopes in southwestern reservoir areas.

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.

Traditional train operation control systems usually adopt a maximum braking control strategy during emergency braking; however, when this strategy is applied to virtual coupling, it may lead to collisions among train units. Considering the heterogeneity of virtual coupling train units, different braking rates of train units, and different safe spacings, a collaborative braking control method based on the Soft Actor-Critic (SAC) algorithm for virtual coupling trains in emergency braking scenarios is designed and analyzed. First, a train safety braking model in a relative coordinate system is constructed based on the running speed of the preceding train within the virtual coupling, the spacing between adjacent trains, and the train's own braking performance, and the safe speed limit of the train is obtained. Second, an operating environment is built according to the train safety braking model, and a braking control model is designed using a multi-train SAC algorithm. The state space and action space of each train unit are determined, and the reward function is designed with the safe speed limit generated by the safety braking model in the relative coordinate system as a constraint. Finally, taking the Beijing Capital Airport Express line and its vehicles as an example, the multi-train SAC algorithm is validated and compared with the maximum braking control strategy and the minimum braking control strategy. The results show that compared with the other two traditional control strategies, the collaborative braking model can not only stop safely before the hazardous point but also ensure spacing safety during braking, thereby improving the operational safety and efficiency of the urban rail transit system.

To achieve high aperture efficiency and miniaturization for a dipole antenna operating in an environment with a single-sided metal wall inside an inspection vehicle, this paper analyzes and optimizes the antenna’s performance using multi-arm folding and current control methods. First, based on the effective current length theory, a four-arm folded dipole antenna fed by a vertical microstrip line is proposed. While maintaining the effective current length, the radiating arms are folded horizontally and vertically, respectively, achieving antenna miniaturization. Second, a back cavity is added beneath the antenna, and a horizontal strip is introduced to concentrate the resonant current in the radiation plane, thus improving the aperture efficiency and gain of the four-arm dipole antenna. Finally, to address the impedance mismatch and radiation pattern distortion caused by the single-sided metal wall inside the inspection vehicle, the four-arm folded dipole antenna is further redesigned. A shorting patch is introduced to suppress surface currents on the side nearest the wall, while the vertical arm nearest the wall is extended to suppress undesired current excitation, thus mitigating the effects of the metal wall on the antenna’s impedance and radiation pattern performance. Both antennas have been fabricated and measured. The results show that the antenna size is reduced from a half-wavelength to approximately 1/4 wavelength, achieving a reduction of 50%. The measured bandwidth is 410–447 MHz with good impedance matching. The antenna can effectively suppress the effects of the single-sided metal wall, with a peak gain of 5.5 dBi, cross-polarization levels below −10 dB, backlobe levels below −10 dB, and radiation efficiency above 80%, meeting the requirements of the wireless transmission system inside the inspection vehicle.

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

An energy attenuation coefficient (EAC) is introduced to quantify the dynamic response of building envelopes to outdoor thermal disturbances. It is defined as the ratio of the time integral of the absolute heat flux at the internal surface to that at the external surface over a given period. A higher value indicates weaker attenuation, whereas a lower value indicates stronger mitigation of outdoor thermal disturbances. Yanqi, Xinjiang, characterised by large air-temperature fluctuations and strong solar radiation, is used as a case study. Heat transfer in 25 typical envelope assemblies was simulated using a combined frequency- and time-domain method, and layer-specific EAC values were evaluated at daily, monthly, seasonal, and annual scales. The results show that the annual mean EAC values for the external insulation layer, concrete layer, and internal insulation layer are 0.85, 0.40, and 0.99, respectively, indicating that the concrete layer is the primary contributor to energy attenuation. During the heating season, the EAC of the concrete layer increases significantly to 0.78 compared with other typical periods, indicating that the building envelope is less effective at attenuating outdoor thermal disturbances. The external insulation layer mainly provides steady-state thermal resistance. At the annual scale, moderately increasing the thermal conductivity and heat capacity of the insulation layer improves the overall attenuation of outdoor thermal disturbances throughout the year.

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

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 root mean square error (RMSE) and mean absolute error (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.

In multi-attribute text-to-image generation, maintaining object integrity and semantic consistency in complex scenes remains challenging, primarily due to competition and interference among attributes that can lead to structural incompleteness and semantic mismatches. Existing diffusion models struggle with multiple objects and their attribute descriptions due to insufficient prompt information, semantic entanglement, and uneven attention allocation, leading to missing objects, attribute confusion, and misaligned relations. To address this, a multi-stage generation method based on fine-grained token-level competitive attention regularization is proposed, enabling precise control via prompt enhancement, semantic decoupling, and attention optimization. First, in the prompt stage, an LLM enhances the semantics of the input text and structures its representation to reduce ambiguity. Next, in the encoding stage, an attribute-object-level semantic decoupling mechanism is designed, integrating a token encoding module, positive and negative semantic vectors, and a semantic neighbor strategy to improve the stability and discriminability of embeddings while reducing semantic interference. Finally, in the generation stage, dual competitive attention regularization enhances the responses of attributes and objects in cross-modal attention while suppressing attention overlap between different objects, thus improving object independence and reducing semantic interference. Experiments on the T2I-benchmark show significant improvements in color, shape, and texture attribute binding, with bootstrapping language-image pre-training visual question answering (BLIP-VQA) scores of 0.7392, 0.6205, and 0.5013, respectively. Visualizations further confirm that the method effectively reduces attribute mixing and semantic misalignment in complex multi-object scenes while preserving object integrity and semantic consistency, demonstrating good robustness and controllability.

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

To address the localization problem of fatigue cracks in steel box girders with complex structures, a registration algorithm for crack and structure was proposed by leveraging the linear geometric features of welds. Consequently, the whole perception process for identifying, quantifying, and localizing the cracks was integrated and automated. Firstly, a dual-task deep neural network, CrackFormer-Hough, was established to identify the cracks and welds in two-dimensional (2D) images simultaneously. Then, the identified targets were reconstructed by stereo vision techniques to generate target point clouds and quantify their geometric features. Finally, by taking welds as the reference, the coordinate transformation relationship between the camera and structure space was obtained based on the coarse/fine point cloud registration algorithms. Based on structural coordinates, the crack segments from each scope were spliced and fused, and the complete crack morphology was plotted in the structural map. Field tests show that the identification network can overcome background interference and accurately distinguish the weld structure of specific regions by introducing the deep Hough transform to learn the scene semantics of steel box girders. By means of the obvious linear features of welds, the registration errors are controlled to about 1 mm with sparse point clouds. The fatigue crack perception performance is not sensitive to the camera poses. Under different lenses, the average localization error is within 5 mm, and the length measurement error is only about 1%.

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.

The navigation congestion problem in water control projects is often caused by the unbalanced allocation of cargo flow for dam-passing ships. To address this issue, a cargo flow distribution optimization model was established to achieve dual objectives of minimizing the total additional cost for dam-crossing ships and waiting time. Furthermore, the service charge mechanism oriented to the dam-crossing mode of the new waterway was further introduced, and its influence on the transfer law of ship cargo flow was analyzed. Then, a non-dominated sorting genetic algorithm (NSGA)-II was applied to solve the model, and the dam-crossing ship cargo flow allocation optimization scheme was proposed. Finally, by taking the Three Gorges water control project as an example, the effectiveness of the proposed model and algorithm was verified. The results demonstrate that the algorithm successfully obtains multiple sets of Pareto frontier solutions and provides diversified ship cargo flow allocation schemes. The total additional cost of dam-crossing ships is significantly negatively correlated with their waiting time. The cargo flow allocation schemes of the dam-crossing system with dual and multiple modes can achieve the objectives of effectively reducing costs and improving efficiency. The optimized scheme with a multi-mode system reduces the total additional cost for dam-crossing ships and waiting time by 67.1% and 0.5%, respectively. Compared with the initial scheduling scheme, the proposed ship cargo flow allocation scheme results in a mode shift of at least 33.4% of the ship cargo flow, which alleviates navigation congestion in water control projects. Moreover, a reasonable service charge rate for the new waterway can effectively reduce the cost and improve the efficiency of dam-crossing ships.

To improve the computational accuracy and efficiency of the probability density evolution method in analyzing high-dimensional stochastic responses of complex structures, a total variation diminishing (TVD) scheme using Van Leer’s flux limiter and a hypersphere-based uniform point selection method are proposed. First, for the TVD scheme in difference solving, the limitations of the Roe-Sweby flux limiter are analyzed. Van Leer’s flux limiter is selected to optimize numerical solution accuracy, and its effectiveness is verified through numerical examples. Second, based on existing mathematical findings, the probability calculation formulas for the n-dimensional standard normal distribution within hyperspheres and hypercubes are derived, by which the hypersphere-based high-dimensional point selection method is quantitatively validated. Furthermore, a hypersphere-based good lattice point method is developed to generate uniform point sets and perform probability calculations within hyperspheres. Finally, taking a high slope project under construction as a case study, a probability density evolution equation for slope stability is established, and the proposed improved method is applied to calculate the slope stability coefficient. The results show that under normal service conditions and rainfall conditions, compared with 10 000 Monte Carlo simulations, the minimum errors of the probability integral for the slope stability coefficient are 0.4% and 0.2%, and the maximum errors are 2.9% and 4.2%, respectively. When addressing high-dimensional stochastic structural problems, the proposed numerical solution method demonstrates satisfactory computational accuracy and efficiency.

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

To address the waveform distortion of rolling bearing fault features under strong background noise interference, a method combining Bessel series empirical wavelet transform (BSEWT) and attention-guided denoising autoencoder (AGDA) was proposed. First, the time-domain signal was mapped to a data-driven energy spectrum via Bessel basis expansion. By using a multi-scale peak detection strategy, frequency band boundaries were adaptively identified to separate modal components containing fault information. Second, an AGDA model was constructed to reconstruct the background noise distribution by using an attention weighting mechanism, reversely stripping noise components from noisy modes. Finally, the feature extraction property under five rotational speed conditions and various signal-to-noise ratio (SNR) levels was evaluated by using simulated signals and the public bearing dataset of Case Western Reserve University (CWRU). The results show that BSEWT adaptively narrows the frequency bands and finely isolates complex narrow-band interference better than the traditional empirical wavelet transform (EWT) in frequency band division. In simulation experiments with five different rotational speeds, when the input SNR exceeds 10 dB, the output SNR, root mean square error, and normalized correlation coefficient of the BSEWT-AGDA method are comprehensively superior to those of variational mode decomposition (VMD), empirical mode decomposition (EMD), and EWT. For input SNRs below −5 dB, the BSEWT method achieves the optimal output SNR index. In CWRU data validation, the signal processed by the proposed method yields a kurtosis of 8.163 5 and an impulse factor of 8.074 1, surpassing comparative algorithms like VMD and EMD. BSEWT overcomes the defect of relying on fixed frequency band division in traditional methods, achieving precise complex frequency spectrum segmentation. Combined with the AGDA model, it effectively eliminates noise interference in higher SNR ranges and achieves high-fidelity reconstruction of rolling bearing fault features.

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 1.190 to 1.430. 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 1.000 to 1.500.

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.

Transverse eccentric wear of the brake shoe is a co mmon and critical braking fault in freight trains, which can lead to thermal damage in wheels. The mechanism of transverse eccentric wear of the brake shoe influencing thermal fatigue crack propagation in freight train wheels was investigated to support wheel condition-based maintenance and safety early warning. First, material tests were carried out to obtain the mechanical property parameters and fatigue crack propagation parameters of ZL-C wheels at various temperatures. Second, a thermo-mechanically coupled finite element model of the wheel was developed to simulate the temperature and stress fields under emergency braking conditions with different degrees of eccentric wear of the brake shoe. Finally, based on fracture mechanics theory, a predictive model for thermal fatigue crack propagation service life was established to analyze the crack propagation path and its service life. The results show that the eccentric wear of the brake shoe will lead to a significant braking temperature rise during the emergency braking of the wheel, and a large cyclic circumferential stress will be generated. The combined effect of the two will lead to the initiation of “scale-like” cracks at the chamfer of the wheel rim. The thermal fatigue crack mainly propagates along the axial direction of the wheel and propagates slowly along the radial direction. With the increase of crack size, the depth-to-length ratio of thermal fatigue crack decreases continuously. Under the influence of the eccentric wear of the brake shoe, the propagation service life of the thermal crack is greatly reduced. Under the emergency braking condition of the eccentric wear of the brake shoe of 25 mm, the unstable fracture occurs when the crack extends to 50.0 mm. Compared with that in the condition without the eccentric wear of the brake shoe, the thermal fatigue crack is extended from 0.2 mm to 50.0 mm when the eccentric wear of the brake shoe is 25 mm. The propagation service life of the crack is reduced by 90.1%. For the wheels with thermal fatigue cracks, it is necessary to further strengthen the monitoring, avoiding the early failure of the wheels caused by the unstable propagation of the cracks.

To address the challenges of vibration prediction for deep-sea natural gas hydrate mining risers under complex environmental loads, a machine learning model named CLR-ZOA-RF was proposed. This model enhanced the performance of the zebra optimization algorithm (ZOA) by incorporating chaotic mapping, Levy flight, and random perturbation mutation (CLR) strategies, which are then integrated with the random forest (RF) algorithm to achieve real-time vibration response prediction of mining risers under multi-factor influences. Based on the similarity principle, a vibration simulation experimental device for the mining riser was developed to conduct multi-factor riser vibration experiments and construct an experimental dataset. The research results indicate that the proposed CLR-ZOA-RF model exhibits superior generalization performance in processing multi-dimensional non-linear data. Specifically, the determination coefficients (R²) for in-line and cross-flow vibrations are improved from 0.935 9 and 0.926 4 of the ZOA-RF model to 0.971 9 and 0.966 7, respectively. Compared with those of the ZOA-RF model, the mean absolute error and root mean square error of the CLR-ZOA-RF model decrease by 26.83% and 33.72% for in-line vibration and by 45.15% and 29.49% for cross-flow vibration. It can be seen that the model achieves high prediction accuracy and good generalization, confirming the effectiveness of the hybrid intelligent algorithm.

Achieving a balanced combination of high strength and high hole expansion ratio is a critical research objective for the application of high-strength steel in automotive manufacturing. A novel low-carbon Ti-Nb microalloyed hot-rolled multiphase steel with a high hole expansion of 780 MPa grade was designed. The thermomechanical controlled process (TMCP) was employed to investigate the influence of different coiling and annealing temperatures on its microstructure and mechanical property evolution, as well as to elucidate the mechanisms governing the high hole expansion property. The results indicate that increasing the annealing temperature enhances the precipitation strengthening effect of Ti/NbC particles, promotes grain refinement of the experimental steel, and leads to a progressive increase in both yield and tensile strengths. However, elongation after fracture and hole expansion ratio exhibit a gradual decline with rising annealing temperature. At a coiling temperature of 480 ℃, the hole expansion property is primarily governed by the bainite/ferrite ratio. Elevated annealing temperatures result in increased bainite content, which restricts crack deflection and bifurcation, thereby causing a monotonic reduction in hole expansion ratio. At a coiling temperature of 520 ℃ and an annealing temperature of 610 ℃, an optimal matching among the fine-grained microstructure of experimental steel, an appropriate bainite/ferrite phase ratio, and dispersed fine Ti/NbC precipitates was realized. This microstructural configuration effectively promotes crack deflection, bifurcation, and microvoid formation during hole expansion, enabling greater energy consumption prior to fracture and resulting in a hole expansion ratio exceeding 60%.

Aiming at the problem that the photoelectric and photothermal conversion performance of photovoltaic/thermal (PV/T) systems is still constrained by low winter temperatures in cold regions of northern China, this paper proposes a novel solar photovoltaic/thermal integrated system integrated with a micro-channel heat pipe array and evaluates its energy conversion performance under actual operating conditions. The system consists of a PV module, an aluminum micro-channel heat pipe array using R141b as the working fluid, and a U-shaped manifold heat exchanger. Indoor experiments determine that the optimal mass flow rate of cooling water in the U-shaped manifold heat exchanger is 0.025 kg/s, achieving a balance between energy conversion efficiency and circulating pump energy consumption. Based on multi-day outdoor experiments, the temperature distribution and energy conversion performance of the system in winter and summer are investigated, as well as its net energy conversion performance when circulating pump energy consumption is considered. The experimental results of two days with representative weather conditions show that under winter outdoor conditions, the thermal efficiency, net electrical efficiency, and net overall efficiency of the system are 27.21%, 10.41%, and 37.62%, respectively; the average daily net overall energy output is 376.53 W, including a net electrical output of 127.54 W and a thermal output of 248.98 W. Under summer operating conditions, the corresponding thermal efficiency, net electrical efficiency, and net overall efficiency can reach 47.42%, 8.55%, and 55.97%, respectively; the average daily net overall energy output is 643.71 W, including a net electrical output of 110.49 W and a thermal output of 533.22 W. The experimental results show obvious seasonal performance differences.

A periodic acoustic black hole is a new type of vibration-damping structure that exhibits both bandgap characteristics and broadband vibration-damping performance. The current research on periodic acoustic black holes has difficulty in forming an omnidirectional low-frequency bandgap at the two-dimensional level and low structural strength. Based on this, the analysis method of combining real and complex energy bands was adopted to achieve low-frequency broadband vibration damping, and a grid-type periodic acoustic black hole structure was proposed, verifying its favorable omnidirectional bandgap characteristics at the two-dimensional level with low-frequency bandgap characteristics and broadband vibration-damping performance. Then, two reinforcement structures of grid-type acoustic periodic black holes were proposed, and the theoretical analysis was validated by employing the vibration transmission experiment. The results show that the first bandgap onset frequency of the reinforcement structure with stiffeners increases by 170.1%, while its bandgap range is reduced to 42.1% of the original value. For the reinforcement structure with stiffening grids, the first bandgap onset frequency increases by 69.3%, with its bandgap range reducing to 42.3% of the original one. The low-frequency bandgap characteristics of the reinforcement structures are not as good as those of the original structure, but the vibration-damping performance is better than that of the original structure in the medium and high frequency bands, and the reinforcement structures have excellent broadband vibration-damping performance. Through comparison of two reinforcement structures, the one with stiffening grids has better low-frequency bandgap characteristics and broadband vibration-damping performance.

In order to investigate the influence law of vehicle parameters on derailment risk of rear-end collisions of electric multiple units, a mathematical model of a speed-sensitive tight-lock coupler was innovatively proposed and integrated into the vehicle dynamics model. The train collision dynamics model was established through the coupling of adjacent vehicles. Rear-end collisions of two identical short electric multiple units were simulated on straight tracks to obtain the dynamic responses of the vehicles under different parameters. Finally, the derailment risk of rear-end collisions was evaluated by using the derailment coefficient, wheel load reduction rate, wheel–rail contact force, wheel lift, and other derailment indices. The influence law of collision speed, leading car body mass, and anti-climber steady-state force on the derailment indices was investigated. The results show that under various collision conditions, the maximum values of wheel lift and wheel load reduction rate are observed at the right wheel of the third wheelset on the leading car of the active train during rear-end collisions of short electric multiple units on straight tracks. The maximum values of derailment coefficient and wheel–rail contact force are observed at the right wheel of the second wheelset on the leading car under the same conditions. Derailment indices increase with higher collision speed under identical initial conditions. The wheel lift increases from 0.01 mm to 33.40 mm when the collision speed increases from 25 km/h to 55 km/h. The maximum vertical wheel force increases from 83.8 kN to 159.0 kN, an increase of 89.7%, under the same conditions. The peak value of the wheel load reduction rate firstly decreases and then increases with the increase in the leading car body mass. The wheel lift increases by 83.6% compared with its maximum when the anti-climber steady-state force is minimized.

Clarifying the magnetic force characteristics of null-flux coils and side-wall beams under mechanical, electrical, and magnetic multi-field coupling has significant guiding value for the design of coil modules and the construction of track structures in superconducting electrodynamic suspension systems. To this end, an electrodynamic force numerical calculation model was established based on the dynamic circuit principle, referencing the parameters of the Yamanashi line electrodynamic suspension system in Japan. The electrodynamic force responses of a single null-flux coil, coil module, and side-wall beam under the full-load operation of the maglev train were calculated, and the basic characteristics of the system magnetic force were obtained. Subsequently, the influence of motion parameters of superconducting magnets on the electrodynamic force was explored, and the variation rules of dynamic loads of magnets under different motion speeds, sinking amounts, and lateral displacements were statistically analyzed. The results indicate that the load on the track follows an increase, stabilization, and decrease trend, and it takes at least 11 consecutive null-flux coils to stabilize; the main characteristic wavelengths in the frequency-domain response of electrodynamic force are the superconducting coil pole pitch of 1.35 m and the 2.5-times wavelength of 3.375 m; the magnetic force amplitude of a single null-flux coil decreases with the increase of speed, and the average magnetic force acting on the side-wall beam gradually increases. When the magnetic force involves multiple null-flux coils, its magnitude is jointly determined by the induced current and speed, and the fundamental frequency gradually shifts from the frequency corresponding to the 1.35 m wavelength to that of the 3.375 m wavelength; at the speed of 200–600 km/h, the fundamental frequency of the side-wall beam’s magnetic force response ranges from 17 to 49 Hz. By considering that the commonly used operating speed of maglev trains is 400–600 km/h, it is recommended that the fundamental frequency of the side-wall beam structure should not exceed 33 Hz. The lateral force acting on the track is sensitive to the lateral displacement of superconducting magnets; to enhance the dynamic stability of the side-wall beam structure, significant lateral displacements of magnets should be avoided as much as possible.

To study the shear mechanical properties of special shear keys in composite structures of a double-layer plate truss, the influence of concrete strength and the hole diameter of transverse perforated stiffening ribs on the shear property of special shear keys was explored through push-out tests. The refined numerical simulation analysis was verified, revealing the failure mode of specimens and the collaborative working mechanism of special shear keys. Based on numerical simulation for parameter analysis, a calculation formula for shear bearing capacity suitable for special shear keys was proposed. The results show that the composite structure of a double-layer plate truss bears the shear force by the transverse perforated stiffening ribs and studs. As the concrete strength increases, the shear bearing capacity of the shear keys gradually improves. The concrete strength increases from C30 to C50, and the shear bearing capacity of the shear key rises from 341.16 kN to 448.09 kN, an increase of 31.34%. The ductility of the shear key with a hole diameter of 25 × 20 mm is 2.06 mm, which is 89.0% higher than that without a hole. Moreover, the greater strength of the concrete leads to a greater influence on the ductility of the shear key. The stress at the root of the stud first reaches the yield strength, and then the transverse perforated stiffening rib reaches the yield strength. Parameters, such as the diameter of the stud, the ultimate tensile strength of the stud, the strength of the concrete, and the thickness of the transverse perforated stiffening rib, affect the shear bearing capacity of the special shear key. Based on the parameter analysis, a calculation formula suitable for the shear bearing capacity of the special shear key is proposed. The prediction results are in good agreement with the finite element results, providing a reference basis for engineering design.

To investigate the effects of loading angle on the crack propagation life and damage mechanisms of 6005A-T6 aluminum alloy under different fatigue degradation levels, a systematic fatigue crack propagation test was designed and conducted. The compact tension shear specimens were employed, and the comparative tests were performed under four degradation levels and four loading angles. The crack propagation rate was calculated and evaluated by using the seven-point incremental polynomial method. First, crack propagation curves were obtained under non-degraded and different degrees of pre-fatigue conditions. Second, the variation law of residual life at different loading angles was compared. Finally, the local strain distribution at the crack tip was analyzed by using digital image correlation (DIC) technology, and fracture morphology was observed to reveal the crack propagation mechanisms. The results show that the loading angle significantly affects the crack propagation behavior. As the loading angle increases, the crack propagation rate decreases significantly, and the residual life is greatly extended. Under the non-degraded condition, the degree of life extension can reach up to 186%. Under the 1.5 × 10⁵ cycles of degradation, the degree of life extension drops to approximately 140%, indicating that the effect of loading angle on life extension diminishes as degradation deepens. DIC results show that increasing the loading angle reduces the local strain at the crack tip, decreases the sensitivity of the crack to the main loading direction, and exhibits a stronger propagation hysteresis effect. In terms of fracture morphology, as the loading angle increases, the fracture roughness increases, and the cleavage steps and tear ridges gradually become coarser, with the crack propagation path becoming more complex, revealing the dominant role of loading angle in the crack failure mode.

To investigate the effect of phase change materials (PCMs) on the thermal properties of ceramsite foam concrete, phase change energy storage ceramsite lightweight foam concrete, namely PCESLFC was prepared by using solid–solid phase change material (SS) and phase change microencapsule (MC). The effects of different PCM dosages on the thermal conductivity, specific heat capacity, phase change temperature, and phase change enthalpy of the ceramsite foam concrete were studied. A concrete panel heat transfer test was conducted to evaluate the thermal insulation property of PCESLFC, and a miniature test house was constructed to assess its thermal regulation property under natural environments. The results show that the incorporation of MC effectively reduces the thermal conductivity and increases the specific heat capacity of the ceramsite foam concrete. The MC-100% group exhibits a reduction of 18.16% in thermal conductivity and an increase of 21.1% in specific heat capacity compared to the control group. In contrast, the SS has limited enhancement effects on the thermal properties of the ceramsite foam concrete. Differential scanning calorimetry (DSC) analysis reveals that the MC has a higher phase change enthalpy, with the MC-100% group achieving a phase change enthalpy of 9.08 J/g, which is 7.32% higher than that of the SS-100% group. Temperature damping coefficient calculations indicate that the thermal insulation property improvement of the ceramsite foam concrete in the SS group is significantly lower than that in the MC group. Temperature monitoring in the miniature test house shows that the occurrence time of peak temperature in the PCESLFC test house is delayed by 20 min, and the peak temperature reduces by 0.8 ℃ compared to that of the control group. The occurrence time of minimum temperature is delayed by 20 min, and the valley temperature increases by 0.4 ℃. MC shows excellent thermal regulation properties to ceramsite foam concrete, making it suitable for building envelope systems.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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