Through rigid model wind tunnel pressure tests, this study investigated the wind load distribution characteristics of an overhead photovoltaic roof under an isolated building condition, as well as the effects of the spacing and height of interfering buildings on the peak wind pressures of the affected building’s photovoltaic roof under three types of interfering building layout conditions.The results indicate that the wind load on the overhead photovoltaic roof is dominated by wind suction, and the wind pressure distribution exhibits significant wind-direction dependence and regional characteristics.According to the relevant code, when the roof is divided into two zones, the peak wind pressure coefficients of the inner and outer zones are 70% and 96% of the code values, respectively.When the roof is divided into 13 zones, the maximum peak wind pressure coefficients occur at the high eave corner, reaching -6.75 and -6.84, and it is recommended that the design value be taken as 1.4 times the code value for reinforcement.The interference effect of interfering buildings on the peak wind pressures of the overhead photovoltaic roof weakens with increasing spacing ratio and strengthens with increasing building height.The interference effect mainly affects the zones close to the interfering building.Under the three types of interfering building layout conditions, the maximum interference factor for the peak wind pressure in the corner zone adjacent to the interfering building exceeds 1.10.When the spacing ratio of the interfering building is not greater than 3.0, depending on the layout and spacing ratio of the interfering building, it is recommended that the design values of the peak wind pressures at the low-eave and high-eave corners be taken as 1.1-1.2 times and 1.5-1.6 times the code values, respectively, for reinforcement.When the spacing ratio exceeds 3.0, the interference effect can be neglected, and the design can follow the isolated building condition.

The additional conductor in the overhead contact system is a crucial component of the railway power supply infrastructure.Under adverse conditions, such as icing and strong winds, an aerodynamic instability may occur, manifested as large-amplitude, low-frequency nonlinear galloping, which severely threatens the stability of railway power supply and structural safety.However, existing studies offer limited practical mitigation strategies for complex icing environments, and traditional galloping suppression devices used in transmission lines are often incompatible with the structural characteristics of the catenary system.To address this issue, this study designs an air flow spoiler, which can alter the aerodynamics of the conductor’s cross-section and suppress instability.First, a computational fluid dynamics
 model of the iced additional conductor is developed, incorporating the effect of the air flow spoiler.The variation of aerodynamic coefficients for different icing profiles is explored.Then, a nonlinear finite element beam model based on the 
absolute nodal coordinate formulation  is established to accurately represent the geometric nonlinearity of the conductor.Finally, the galloping behavior of the iced additional conductor is analyzed, and the effects of wind speed, wind angle of attack, tension, damping ratio, ice thickness and the number of air flow spoilers on galloping amplitude are explored and optimized installation strategies are proposed.Under normal operating conditions, the installation of four anti-galloping whips can substantially reduce the galloping amplitude.For cases involving high wind speed, low damping ratio, or severe ice accretion, an additional one to three anti-galloping whips may be installed to further enhance vibration suppression.Increasing the wire tension can also mitigate the galloping amplitude; however, it has little influence on the selection of the anti-galloping whip configuration.

The safety assessment of flow induced vibration in overflow dams is closely related to the vibration source load and overall dynamic response of the structure.To address the difficulty in achieving continuous distributed measurement of the main vibration source and global dynamic displacement field of overflow dam piers, this study proposes a method for time domain vibration source identification and global dynamic displacement field inversion under discharge excitation.Based on the measured vibration response of the overflow dam pier, a mathematical model for the time domain load identification inverse problem of a multi-degree-of-freedom discrete system is constructed through modal coordinate transformation and time domain deconvolution techniques.The Tikhonov regularized pre optimized bi-conjugate gradient algorithm is used to iteratively solve the inverse problem, in order to overcome the ill-posedness of load identification inverse analysis and improve the accuracy of time domain identification of vibration source loads.On this basis, the identified vibration source load is used as input for flow induced vibration forward analysis, thereby realizing the inversion of the global dynamic displacement field of the overflow dam pier using limited measured responses under discharge excitation.Numerical results show that this method can effectively and stably achieve time domain identification of multiple vibration source loads with high identification accuracy under different noise levels.Engineering cases show that the inversion of the global dynamic displacement field of an overflow dam pier can be achieved using only the dynamic displacement response of 12 measurement points, and the inversion results are consistent with the measured values in terms of amplitude and variation.The proposed method provides a foundation for comprehensive understanding and safety assessment of flow induced vibrations in spillway dams.

To overcome the problems of structural weight increase and low material utilization rate in the traditional "full application" damping layer design, a topology optimization model oriented to dynamic vibration reduction performance was constructed for a typical constrained damping cantilever thin plate based on the parametric level set method. The optimization objectives were to minimize the difference between the moving constant and the modal loss factor, and to minimize the peak value of the resonance response, respectively. The global optimization criterion method was adopted for solution. The optimization program was compared and analyzed through numerical examples, and the effectiveness of the method was verified by experimental means. The results show that both objective functions can obtain continuous and reasonable damping material distribution configurations. Under the condition of using only 50% of the damping material, the optimization method can achieve vibration reduction performance that is better than or at least not worse than the full application scheme. The resonance peak of the first-order mode of the optimized configuration is reduced by 17.67% compared with the full application scheme, and the reduction amplitude reaches 24.00% under weighted multi-order optimization. At the same time, the comparison and verification between experiments and simulations show that the first-order response peak of the optimized structure is reduced by more than 70%, which is highly consistent with the simulation prediction. The research provides a new and effective approach for lightweight and high-performance vibration reduction design in engineering.

To investigate the dynamic damage characteristics of weakly cemented sandstone under acid erosion, specimens collected from the roof and floor of a coal mine in a mid‑western mining area of China were selected. split Hopkinson pressure bars dynamic impact tests were performed on samples after immersion in chemical solu-tions (pH 1, 3, 5, and 7) at 10‑day intervals for up to 60 days. The degradation mechanisms of dynamic strength and failure deformation characteristics were compared and analyzed, and a dynamic damage constitutive model for weakly cemented sandstone was established. The results show that the dynamic stress‑strain curve consists of three stages: an initial linear elastic stage, a yield stage, and a post‑peak softening stage, with no obvious compaction stage. As the degree of acid erosion increases, the linear elastic slope and stress increase rate decrease, while the proportions of the yield and post‑peak softening stages increase, causing the overall curve to flatten. Acid erosion significantly degrades the dynamic mechanical properties of weakly cemented sandstone, and the degree of degradation is positively correlated with acid strength. After 60 days of acid erosion, under weak acid conditions, the peak stress decreases by 37%, the elastic modulus by 40%, and the peak strain increases by 11% ; under strong acid conditions, the peak stress decreases by 53%, the elastic modulus by 56%, and the peak strain increases by 18%. Based on the strain equivalence principle, a weighted composite damage variable is defined, and a Weibull damage constitutive model incorporating the synergistic effect of acid erosion and dynamic loading is established. This model accurately characterizes the nonlinear damage evolution of mechanical parameters under acid erosion throughout the loading process. The research findings provide theoretical support for evaluating the mechanical properties and stability of acid‑eroded rock masses during coal mining.

To address the limitations of excessive static displacement and difficulty in frequency tuning in traditional tuned mass damper (TMD) for ultra-low-frequency vibration control, this study employs tuned mass damper inerter (TMDI) for the mitigation of ultra-low-frequency vibration in long-span bridges. A rack-and-pinion TMDI prototype was developed, in which precise tuning of the control frequency was achieved by adjusting the rotational inertia of the inerter flywheel. Model tests verified that the frequency tuning error of the device was less than 0.5%. Subsequently, field tests of the TMDI were conducted on an actual bridge. The practical control performance of the TMDI was evaluated through both steady-state excitation-based damping ratio tests and ambient vibration tests under strong wind conditions. The results demonstrate that, with a mass ratio of 0.0466%, the TMDI increased the target modal damping ratio of the bridge from 0.198% to 0.585%. Under actual wind loading, the acceleration response amplitude of the TMDI reached 3.56 times that of the bridge girder, indicating that the TMDI prototype operated effectively in capturing and dissipating the vibration energy of the bridge girder. This study verifies the effectiveness of the TMDI in controlling ultra-low-frequency vibration of long-span bridges and provides a reference for its practical engineering application.

To address the issue of significant aerodynamic noise generated by the suction valve assembly in reciprocating compressors during operation, this study proposes a novel sloped valve port design. A coupled fluid-structure-acoustic numerical framework, integrating large eddy simulation with the Ffowcs Williams-Hawkings acoustic equation, was employed to thoroughly investigate the noise reduction mechanisms of the proposed structure. Numerical results indicate that the sloped valve port significantly suppresses the development of local turbulence and mitigates vortex shedding as well as unsteady flow fluctuations, thereby achieving effective aerodynamic noise reduction over a broadband frequency range. Furthermore, this structural modification alleviates the stress concentration on the valve plate, enhancing its dynamic operational stability. To validate the actual noise reduction efficacy of the sloped valve port, it was applied to a full-scale compressor unit, and acoustic tests were conducted in a semi-anechoic chamber to comprehensively evaluate its sound field distribution and overall noise control performance. Experimental results confirm that the novel structure possesses superior noise reduction capability; the sound power level of the entire unit is significantly attenuated, with a maximum reduction of 3.88 dB. The findings of this study provide a theoretical basis and practical engineering guidance for the forward aerodynamic design of low-noise reciprocating compressors.

The issue of rail wear in curved sections of urban rail transit has become increasingly prominent, necessitating the optimization of key parameters such as curve superelevation and rail cant. In this paper, a three-dimensional transient wheel-rail rolling vibration analysis model based on the explicit finite element method was developed. Combined with multi-body dynamics, the initial wheel-rail geometric configuration was determined. The model was validated through force chain tests and wheel-rail force measurements. Based on the Archard wear model, the rail wear depth was calculated. The influences of train speed, rail cant, curve superelevation, and curve radius on rail wear were systematically investigated. The results indicate that lateral vibration of the inner rail dominates its wear, with the lateral component significantly higher than the longitudinal component; longitudinal vibration of the outer rail dominates its wear, with the longitudinal component being dominant. As the train speed increases from 50 km/h to 70 km/h, the wear of the inner and outer rails increases by 28.7% and 64.3%, respectively. The combination of a rail cant of 1/40 for the inner rail and 1/20 for the outer rail results in the lowest wear. Curve superelevation affects wear by altering the load distribution. As the superelevation increases, inner rail wear increases by 240%, while outer rail wear decreases by 80%. It is recommended to set the superelevation within the range of 90–105 mm to balance the wear between the inner and outer rails. Curve radius is the dominant factor; increasing the radius from 400 m to 1200 m reduces wear by 35%–40%. The research findings provide a theoretical basis for the refined design of curved track parameters.

In the research of active control algorithms for building structures, deep learning models (such as Transformer networks) demonstrate strong feature-learning capabilities. However, they suffer from poor physical interpretability, low credibility, and may yield solutions that violate physical laws. To address this issue, a physics-guided deep learning network (Phy-Transformer) is proposed for active control force prediction, based on the integration of physical constraints from structural dynamics. By incorporating the error between the predicted control force value and the actual value into the loss function, it guides the training of the Transformer network. A numerical study is conducted on a 12-story steel frame model equipped with an Active Mass Damper at the top floor under seismic excitation, to evaluate the generalization and robustness of the control algorithm. Results show that the Phy-Transformer achieves nearly 60% reduction in peak displacement at the top floor, outperforming the standard Transformer. Under the uncertainty of model parameters, except for the case where both mass and stiffness increase simultaneously, the robustness of the Phy-Transformer controller is generally superior to that of the Transformer controller. Furthermore, compared with the full-state feedback Linear Quadratic Regulator (LQR) control that provides training data, the proposed algorithm only requires the displacement and velocity information of the top and sub-top levels, as well as the seismic acceleration as input to achieve efficient control, indicating stronger engineering applicability. This research provides a feasible and effective solution path for data-driven structural intelligent active control systems. 

To address stability control challenges in the drilling and blasting of large-section soft rock tunnels, the present study establishes an equivalent simulation method for dynamic blasting loads and support structures. The deformation evolution mechanism of the surrounding rock is systematically analyzed, and support parameters are optimized accordingly. A three-dimensional numerical model is developed based on a real engineering project. The complex blasting process is simplified as an exponential stress time-history applied to the excavation boundary. The transient unloading effect of in-situ stress is also considered. The combined support system of rock bolts, shotcretes, and steel arches is treated as a reinforcement zone with improved mechanical parameters. This approach enables accurate simulation of the full construction process. The numerical results match well with field monitoring data in both vibration waveforms and deformation trends, which confirms the reliability of the proposed equivalent simulation method. Parametric analysis clarifies how the shotcrete layer, steel arches, and rock bolts work together to control deformation. An optimal support parameter set is proposed, 15 cm shotcrete thickness, 0.5 m steel arch spacing, and 0.5 × 1.0 m rock bolt spacing. After the optimization of the support scheme, the settlement of the tunnel's surrounding rock at the arch top decreased from 35.0 mm to 15.6 mm, a reduction of 55.4%, and the material cost per meter was saved by 570 yuan. This optimized scheme balances safety and economy. It has been successfully applied in practice, providing important theoretical and technical support for similar tunnel projects. 

As key components for restraining creep displacement, the structural form and mechanical properties of bearings are important factors in the creep analysis of curved bridges. To analyze the causes of creep displacement in curved girder bridges under vehicle loads from the perspective of bearings, the existing finite element model of curved girder bridges is refined by considering the mechanical friction among internal components of the bearings. First, a detailed solid model of a pot rubber bearing is established to analyze its mechanical and sliding characteristics, confirming the reliability of the model in simulating the complex mechanical behavior of the bearing. Second, moving vehicle loads on the curved bridge are equivalently represented, incorporating superelevation into the dynamic vector distribution of the loads to establish a vehicle–bridge dynamic analysis system. By comparing the transverse displacement responses of key bridge sections under vehicle passage, critical bearings are identified and determined. A curved girder bridge solid model is constructed by combining solid bearings with spring bearings and connecting them to the main girder. Finally, the transverse displacements of typical sections of the curved girder bridge under different bearing models are compared and analyzed to quantitatively demonstrate the necessity of using solid bearing models, and the mechanism of creep displacement is analyzed from both the overall response and the bearing component level.It can provide reliable theoretical basis and numerical analysis method for the creep displacement disease analysis, reasonable bearing selection and long-term safe operation of curved girder bridges in engineering practice, and possesses important practical application value for improving the design and maintenance level of curved girder bridges. The results indicate that： 1) When spring bearings are used in the bridge model， the transverse displacement time history exhibits continuous and smooth characteristics, whereas solid bearings show obvious fluctuations. The solid bearing model accounts for the frictional nonlinearity at the contact interfaces between internal components, effectively reflecting the intermittent sliding behavior within the bearing. 2) The transverse displacement response of key sections of the curved girder bridge increases significantly with increasing vehicle weight, and the transverse displacements of the stainless steel plate and polytetrafluoroethylene plate in the solid bearing increase synchronously. 3) The transverse displacement at the bridge end sections of the curved girder bridge with solid bearings is significantly greater than that of the comparative bridge model with spring elements, with a difference of approximately 3.96 times. The curved girder bridge model considering the mechanical friction of bearings more accurately reflects the actual creep behavior. The solid bearing model for curved girder bridges can more precisely capture the mechanism of creep displacement.

For flexible rotors supported by three Active Magnetic Bearings(AMBs), suppressing vibrations at a specific location can induce significant amplification at non-target positions, potentially compromising the safe traversal of its bending critical speeds. To address this, a fuzzy adaptive feedforward control algorithm for an auxiliary AMB is proposed. This approach integrates online identification of the transfer function, real-time calculation of optimal feedforward currents, and fuzzy regulation of current weighting based on the vibration magnitudes at different locations. Subsequently, to validate its efficacy in suppressing unbalance vibrations at multiple locations within the flexible rotor system, simulations under both constant-speed and variable-speed conditions were conducted, comparing the proposed algorithm with three feedforward control strategies. Finally, experimental validation on the test bench was conducted, confirming the simulation results and demonstrating that the proposed fuzzy adaptive feedforward control algorithm for auxiliary AMB can adaptively regulate the compensation current, maintaining low vibration levels at multiple target locations and enabling the flexible rotor to safely traverse its 1st bending critical speed.

A damage identification method combining multivariate AR (MVAR) model with power spectral density transmissibility (PSDT) was proposed for wind turbine blade. The method established an MVAR model from strain response signals to compute power spectral density matrices and construct PSDT matrices. Singular value decomposition at system poles verified natural frequencies and extracted strain modes. Structural damage was identified by utilizing the normalized strain mode differences before and after damage. Results show that utilizing parametric power spectrum estimation enhances low-frequency mode identification accuracy and robustness compared to traditional PSDT and Stochastic subspace identification (SSI). Numerical simulations and model tests validated the method accuracy in damage localization and severity assessment.

With the background of the increasing popularity of large-sized tires, this paper took the body peak load as study object in pothole event and involved vehicle body plastic stiffness into MBD model based on traditional virtual road load prediction technology to fully represent body stiffness. Based on this new method, peak load correlation and also plastic deformation measurement had been done on physical vehicles with Tri-coordination measuring system. The multi-body model with plastic stiffness shows good correlation through load and plastic deformation benchmarking between simulation and test and meanwhile, the necessity and rationality of introducing body plastic stiffness modeling on pothole event have also been verified. It is of good importance to precise load estimation and cost control on the early design of vehicle. 

To address the challenges of simultaneously optimizing stiffness and damping in conventional homogeneous metal rubber and the unclear influence mechanisms of structural gradient pore distribution on mechanical properties, a density-gradient design strategy was proposed to fabricate gradient metal rubber specimens. Through an integrated study combining macro–meso modeling, numerical simulations, and experiment testing, the static and dynamic mechanical properties were systematically investigated. Static tests reveal that the gradient metal rubber exhibits distinct three-stage stiffness evolution characteristics in both forming and non-forming directions, reflecting a significant anisotropic mechanical response. Mesoscopic simulations reveal that slippage and extrusion between metal wires as the primary energy dissipation mechanism. Dynamic performance analysis shows that energy dissipation and dynamic average stiffness of gradient metal rubber increase with amplitude, while the loss factor decreases. The influence of frequency variation on performance was minor, with the loss factor exhibiting a slight fluctuation trend.

To address the need for ground testing of dynamic unbalance loads in high-bypass-ratio turbofan engines under windmilling conditions, a multi-level hierarchical design methodology for a scaled rotor test rig based on dynamic similarity is proposed. Firstly, a surrogate structure that preserves the dynamic characteristics of the prototype is constructed using a three-criteria evaluation system incorporating modal contribution, stiffness contribution, and mass proportion. Subsequently, an equivalent prototype considering support stiffness and damping characteristics is established via the non-dominated sorting genetic algorithm II multi-objective optimization algorithm. Similarity scaling relationships for shafts and disks are then derived through equation analysis, while the support configuration and squeeze film damper parameters are kept consistent during the scaling process. Finally, a scaled physical test rig is developed with the LEAP-1B engine low-pressure rotor as the prototype, and steady-state windmilling unbalance response experiments are conducted within a speed range of 1140–1440 r/min under various unbalance levels (0–840 g•cm). The results show that the relative errors of the first two critical speeds between the scaled model and the prototype are 3.39% and 2.13%, respectively, and the measured trends of displacement and support reaction forces align well with the simulations, effectively reproducing the dynamic unbalance load characteristics of the prototype under windmilling conditions. The proposed methodology provides an effective approach for maintaining dynamic characteristics while simplifying the structure in the scaled design of complex rotor systems, thereby filling a technical gap in the development of scaled windmilling unbalance test rigs for airworthiness compliance verification.

With the rapid development of microelectromechanical systems technology, microscale structures have been widely applied in energy harvesting and sensing fields. In this work, a piezoelectric semiconductor microplate is investigated, focusing on the nonlinear dynamic behavior in the primary resonance region under multiphysical-field coupling. Considering the influence of size effects, the governing equation for the transverse vibration of the piezoelectric semiconductor microplate is derived based on the modified strain gradient theory and Hamilton’s principle. The Galerkin method is then employed to discretize the governing equation. The amplitude–frequency response of the system is obtained using the incremental harmonic balance method combined with the arc-length continuation method, and the stability of periodic solutions is determined via Floquet theory. On this basis, a constant excitation is introduced, and it is found that the inclusion of the constant excitation makes the hysteresis behavior in the primary resonance region more complex. The amplitude responses of the system under different external parameters are analyzed, and the distribution characteristics of the basins of attraction in the primary resonance region are investigated, revealing a symmetry between different steady-state responses. Finally, two-parameter diagrams of periodic responses and the largest Lyapunov exponent are presented to achieve a global parameter-domain analysis over a wide parameter range.

Large slewing bearing stress field reconstruction in single-point mooring systems under extreme marine conditions is addressed using a digital twin-driven MPI-XGBoost method. A finite element model of a three-row cylindrical roller bearing is developed using ABAQUS to extract nodal coordinates, Mises stress, and external load data. The dataset is optimized using K-means++ clustering. A dual-driven architecture combining data and physics is constructed. XGBoost captures high-dimensional mappings. Physical laws are embedded into a composite loss function. Hyperparameters are tuned using Bayesian optimization. Under multiple working conditions—1000 kN axial force with 650 kN•m, 700 kN•m, and 750 kN•m overturning moments—the method achieves an average RRMSE of 0.166 and an average peak prediction relative error of 0.063. Accuracy improves by over 28% compared to neural network,physics-informed neural network, and XGBoost models. Strong generalization is demonstrated for untrained intermediate conditions. The method balances accuracy and efficiency to support bearing design and maintenance.

To address the complex objective conditions and difficuly in quantification of subjective evaluation in the selection of noise barrier schemes, an evaluation method based on new distance measure is proposed. First, on the basis of the traditional TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), the entropy weight method was introduced to determine the weight, eliminating the differences caused by different evaluation indexes. Further, comprehensive consideration was given to the static distance and dynamic trend, making up for the subjective assignment bias. Secondly, the Euclidean distance and gray TOPSIS were used to quickly achieve multi-scenario comparison, sorting and selection. Focusing on the position and shape relationship of the numerical sequence, this paper explored the closeness of the posture of the noise barrier scheme to the positive and negative ideal solution curves, thereby eliminating single-theory limitations and evaluation failure. Finally, the new distance measure was utilized to construct a universal noise barrier incremental class level evaluation system. Taking the noise barrier selection of Nansha Bridge as an example, the method was applied to solve insignificant low-frequency noise reduction, easy overturning of strong crosswind panel body, and poor landscape integration in the noise barrier. Finally, a reasonable, feasible and safe noise barrier scheme was selected from seven alternatives, demonstrating the feasibility of the method. The study shows that noise barrier selection based on the new distance measure improves the accuracy of evaluation weights, and solves the problems of excessive dependence on experts' subjective assignment and invalid scheme judgment with the Euclidean distance. Improvement of Euclidean distance via gray correlation, takes into account both the positional relationship and correlation, remedying the judgment failure. The method optimizes the traditional evaluation process, and improves the objectivity of index weighting, and constructs a universal hierarchical evaluation index system for highway noise barriers. The study results can provide technical reference for the scientific selection of noise barriers. 

CRTS I slab ballastless tracks are widely used in high-speed railways. As key components maintaining the mechanical state and structural integrity of track slabs, longitudinal prestressed steel bars exert a vital influence on the structural durability and operational safety of tracks. Aiming at the fatigue degradation of prestressed steel bars under long-term temperature cycling and their fracture risk under coupled temperature loads, this paper proposes a service state evaluation method for prestressed steel bars combining equivalent fatigue tests, static tensile tests and finite element simulation. A three-point bending fatigue test scheme was designed to simulate temperature loads. Five working conditions corresponding to 10–50 years of service life were set. Static tensile tests combined with finite element numerical models were adopted to investigate mechanical property degradation and fracture behavior of prestressed steel bars. The results show that with accumulated fatigue cycles, residual strain of prestressed steel bars increases stepwise and tensile strength attenuates significantly, with a 29.0% reduction in the 50-year equivalent service group compared with the 10-year group. Simulation analysis indicates that the prestressed steel bars located on the outer side of the top layer of the track slab are subjected to relatively unfavorable stress states, and their critical temperature rise for fracture decreases with increasing equivalent service life. For the 50-year equivalent service stage, the critical temperature rise decreases to 27.18 ℃, suggesting a relatively high risk of steel bar fracture under high-temperature conditions or unfavorable constraint conditions.

Deep-sea cranes are tasked with lifting and transporting heavy underwater loads in fields such as offshore oil and gas development and subsea pipeline laying. However, due to wind and wave disturbances and hydrodynamic forces, flexible ropes undergo a certain degree of strain, which poses difficulties for the design of positioning and tracking control for deep-sea cranes. Most existing methods are designed for aerial flexible rope cranes and cannot effectively handle the parameter uncertainties in the deep-sea environment. This paper fully considers the strain of the flexible ropes of deep-sea cranes, conducts dynamic modeling of the deep-sea lifting system based on the Hamilton principle, constructs a Cerebellar Model Articulation Neural Network to locally generalize the target trajectory, and simultaneously constructs a Radial Basis Function neural network to online fit the nonlinear and uncertain parts of the model, thus proposing a double-closed-loop control method for deep-sea cranes. The asymptotic stability of the double-closed-loop control system is strictly proved by constructing a Lyapunov function. Finally, through a series of comparative experiments with proportional-derivative sliding mode control, adaptive neural network control, and boundary control methods, it is demonstrated that the proposed control method has an excellent anti-swing effect in deep-sea lifting and performance in resisting unknown disturbances. 

The wave equation for unsaturated porous thermoviscoelastic media is derived from the wave theory of unsaturated porous media, incorporating the Kelvin-Voigt viscoelastic model and generalized thermoelastic theory to account for skeleton viscosity and thermal effects. For the case of plane P wave incident on layered unsaturated soil site, the amplitude coefficient transformation matrix of layered unsaturated soil layer is derived by Helmholtz decomposition and transfer matrix method, and the analytical solution of seismic ground motion is obtained. Through numerical analysis, the effects of relaxation time, saturation and thermal expansion coefficient on seismic response are discussed. The results indicate that soil skeleton viscosity and site stratification jointly affect the amplification of surface displacement, with a more pronounced influence on horizontal displacement; the displacement amplification factor decreases with increasing relaxation time and increases with increasing degree of saturation; moreover, parameters such as the thermal expansion coefficient, the arrangement sequence of soft and hard soil layers, and frequency all have significant effects on displacement response.

To better address the complex structural damping issues in railway self-centering bridge piers, the simulation method of inherent structural damping under seismic excitation was investigated. Taking a simply supported railway bridge as the engineering background, a 1:15 scaled model shaking table test was conducted, from which the natural frequency, damping ratio, and pier-top acceleration and displacement responses under three strong ground motion records were obtained. A finite element model was established on the OpenSees platform to analyze the pier-top displacement and acceleration responses of four damping models, namely the undamped model, the Rayleigh damping model, the initial stiffness proportional damping model, and the capped viscous damping model, and the numerical results were compared with the experimental data. The results indicate that the undamped model significantly overestimates the seismic response of self-centering bridge piers due to the neglect of energy dissipation. The initial stiffness proportional damping model lacks a mass-proportional damping term, resulting in insufficient energy dissipation during low-frequency rocking motion; its displacement response approaches that of the undamped model, while the acceleration response is underestimated owing to excessive high-frequency instantaneous damping forces. The Rayleigh damping model underestimates the seismic response of the pier because of the presence of mass-proportional damping. The capped viscous damping model shows the best agreement with the experimental results and is therefore recommended for simulating the inherent structural damping in railway self-centering bridge piers.

Footbridges are subjected to crowd loads during normal service and seismic effects during earthquakes. Therefore, dual control of seismic and pedestrian-induced vibrations is necessary for footbridges. The combined action of ground motion and crowd loads will reduce the serviceability and affect the safety of footbridges, and may even cause secondary disasters such as stampedes in severe cases. This paper investigates the vertical vibration response and vibration control of footbridges under the combined action of earthquakes and crowd loads. Random crowd loads are simulated based on the social force model and Fourier series load model. The footbridge is modeled using stiffness-based fiber beam elements, and the structural motion equations are solved by an unconditionally stable explicit algorithm. Vibration comfort is evaluated based on the annoyance rate model. Three control devices, namely Tuned Mass Damper (TMD), Tuned Mass Damper Inerter (TMDI), and Pounding Tuned Mass Damper (PTMD), are adopted for vibration control, all with a uniform mass ratio of 2%, and their control effects are compared. The results show that the peak vibration reduction rate of PTMD is 14.79% higher than TMD, and that of TMDI is 26.01% higher than TMD.

Accurate discrimination between natural earthquakes and mining-induced seismic events is of great scientific significance in seismological research. A high-confidence catalog of mining-induced seismic events can provide a reliable basis for mine safety supervision, risk assessment, and related applications. Feature extraction has been demonstrated to be a key approach for effectively distinguishing between these two types of events. However, this process is often affected by noise interference, mode mixing, and other external factors. To address these issues, this study proposes a joint seismic event classification method that integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise（CEEMDAN）and Extreme Gradient Boosting（XGBoost）, namely the CEEMDAN-XGBoost method. The proposed method is designed to efficiently extract energy features from seismic data and accurately classify seismic event types. In this study, mining-induced seismic events and natural earthquakes recorded in the Liaoning region are used as the primary dataset to construct the classification model, and natural earthquake records from the Japanese K-NET network are further introduced for extended comparative analysis. The results show that the model achieves high classification accuracy when only the Liaoning regional data are used. After incorporating cross-regional natural earthquake data from Japan, the classification performance of the model does not change significantly, indicating that the method can be used to evaluate the influence of regional differences in data on model results. The experimental results demonstrate that the CEEMDAN-XGBoost method can effectively alleviate noise interference and mode mixing in seismic signals and significantly improve the classification performance between mining-induced seismic events and natural earthquakes，with the optimal classification accuracy reaching 93%. From an application perspective, the proposed method can provide a useful reference for the classification of other seismic events and the construction of seismic event catalogs.

The complex topography and frequent strong earthquakes in the mountainous regions of Southwest China create an urgent need to accurately assess the seismic response mechanisms of wind turbine towers to ensure resilient disaster prevention in large-scale renewable energy bases. Addressing the limitations of existing studies that predominantly focus on isolated or flat terrains, this paper develops a multi-domain indirect boundary element method. By employing a “zone-matching” technique to integrate the advantages of full-space and half-space Green's functions, the proposed method achieves precise and efficient solutions for the dynamic response of complex mountain-canyon terrains. After verifying the method's accuracy, a finite element model of a 5 MW wind turbine tower considering soil-structure interaction was constructed using OpenSees. Using the calculated site wavefield as input, this study systematically investigated how key parameters, including tower layout position, mountain aspect ratio, and shear wave velocity ratio between bedrock and soil layer, influence structural seismic response. Results indicate: (1) Significant spatial variation in structural response occurs, with surrounding mountains acting as natural barriers that produce a pronounced “shielding effect” on wind turbine responses within canyons; taking the valley-bottom observation point as an example, the peak tower-top acceleration under excitation of the plain-site ground motion is 1.261 m/s2 for the single-canyon case and decreases to 1.209 m/s2 and 1.111 m/s2 when low mountains and high mountains are located on both sides, respectively. (2) Topographic amplification exhibits nonlinear characteristics; the peak tower-top acceleration at the summit increases significantly with mountain steepness, reaching a maximum under high-steepness conditions; (3) The amplification effect caused by the stiffness contrast of soil layers is pronounced, as an increased shear wave velocity ratio intensifies wavefield coupling between soft and hard media, significantly amplifying the seismic response of wind turbine towers. For the high-mountain case under excitation of the mountainous ground motion, the peak tower-top acceleration at the mountain crest increases from 10.81 m/s2 to 17.21 m/s2 as the shear-wave velocity ratio increases from 1.0 to 4.0.

To address the complex combined environmental loads faced by wind turbines operating in near-fault seismic regions, this study investigates the structural dynamic responses of the NREL 5 MW wind turbine under wind–seismic coupling, considering three operational states: cut-in, rated, and shutdown. A monopile-supported tower model is established, incorporating the dynamic characteristics of the Rotor–Nacelle Assembly (RNA), to analyze the influence of operational conditions and ground motion types on structural responses. The results show that the structural responses of the wind turbine are highly sensitive to both ground motion type and operational state, and their interaction significantly affects overall seismic performance. Forward-directional (FD) pulse ground motions induce the strongest mean structural responses, followed by fling-step (FS) pulse motions, while non-pulse motions result in the weakest responses. Under FD pulse motions, the shutdown state produces the largest mean structural response, whereas under non-pulse ground motions, the shutdown state results in the smallest response; for FS pulse motions, the differences among operational states are relatively small. Structural response energy is mainly concentrated at the fundamental modal frequencies, with FD pulses significantly exciting the first mode, while non-pulse motions predominantly excite the second mode. It is recommended to adopt differentiated seismic design strategies tailored to both operational states and the severest ground motion scenarios, with priority given to strengthening the seismic resistance of the tower top, mid-tower section, and foundation, as well as enhancing control capability and structural resilience during shutdown conditions.

To study the seismic performance of corroded steel-reinforced concrete columns in service, 15 specimens were designed and tested under quasi-static loading conditions, with corrosion rate, steel layout form, axial compression ratio, shear span ratio, and web spacing as variable parameters. The failure characteristics of corroded column specimens were observed, and the influence of various parameters on their seismic performance was analyzed. The results show that the bending failure occurs in the specimens with a large shear span ratio, and the bending shear failure and bending shear bond failure occur in the specimens with a small shear span ratio. The hysteresis curve of the specimen exhibits a relatively full spindle shape. Under the condition of pouring concrete after pre-corrosion of steel, with the increase in steel corrosion rate from 0 to 10.3%, the shear bearing capacity of corroded steel-reinforced concrete columns is significantly improved. Among them, the shear bearing capacity of hollow angle steel-reinforced concrete columns is the highest, increasing by 19.1%. Increasing the axial compression ratio, reducing the shear span ratio, and increasing the spacing of the batten plate improve the shear capacity of the specimen. The deformation capacity of the specimen is improved by reducing the axial compression ratio and increasing the spacing of the batten plate, while also increasing the shear span ratio. The ductility coefficient of all specimens ranges from 1.6 to 2.87, and the ultimate inter-story displacement angle exceeds 2%, indicating good collapse resistance. Increasing the shear span ratio is the most effective way to reduce the damage development of corroded steel reinforced concrete columns.

Nonlinear time history analysis is widely used for seismic performance evaluation of high-rise frame–core tube (FCT) structures, but its high computational cost limits its applicability in rapid assessment and reliability analysis. To address this issue, a deep learning-based surrogate modeling approach is proposed for predicting peak seismic responses of structures. The model takes ground motion time histories and structural parameters as inputs and employs two hybrid architectures, namely convolutional neural network–long short-term memory (CNN–LSTM) and convolutional neural network–Transformer (CNN–Transformer), to directly predict key peak response quantities, including inter-story drift ratio, top displacement, base shear, and top acceleration. A one-dimensional convolutional network is used to extract local time–frequency features of seismic inputs, while temporal modeling networks capture the evolution of structural responses. In addition, structural and ground motion features are integrated to enhance model representation capability. To balance computational efficiency and prediction accuracy, input sequences with different temporal resolutions are constructed using multiple time-window processing strategies. The results show that an appropriate reduction in sequence length can significantly improve training efficiency and model generalization, with limited loss of prediction accuracy. Compared with single temporal models, the proposed hybrid models demonstrate superior performance in both accuracy and stability, among which the CNN–LSTM model achieves the best overall balance between performance and computational cost. The proposed approach can significantly reduce computational cost while maintaining satisfactory prediction accuracy, providing an effective tool for rapid seismic performance evaluation and reliability analysis of high-rise structures.

Prefabricated utility tunnels incorporate large spans and multiple joints, undermining the utility tunnel structural integrity and rigidity, which in turn affects its seismic response. Seismic waves propagate through the soil at varying angles, significantly influencing structural stability. However, current research on the oblique incident of seismic waves predominantly relies on numerical simulations, with a notable lack of experimental studies. To address this gap, the present study employs shaking table tests to simulate the oblique incident of seismic waves at angles of 0°, 15°, and 30°, and designs a socket-type utility tunnel incorporating two distinct joint types. Test results indicate that the dynamic response of the tunnel-soil system generally increases with the oblique incident of seismic wave. At a peak ground acceleration (PGA) of 0.7g, the structural response decreases under certain conditions due to soil nonlinearity. The type of utility tunnel joint significantly influences responses to acceleration, earth pressure and strain. Joints with a ramp surface (O-type) generally exhibit superior seismic performance compared to without a ramp (L-type), with the recommended slope angle not exceeding 10°. Concurrently, the relative displacement between the utility tunnel and the surrounding soil increases with both the incident angle of seismic wave and PGA. The test design methodology and conclusions presented herein offer valuable insights for utility tunnel joint design and seismic performance evaluation.