Under the action of complex environmental loads, performance degradation of spatial grid structures is severe to cause sharp increase in risks of their safe service life.Here, mechanical response laws of grid structures under different design parameters were explored to perform probabilistic safety assessment of structures based on reliability.A 2D orthogonal flat plate grid structure model was established using the software ABAQUS, and its stress and displacement changes under different height-span ratios, column spacings and corrosion rates were studied.Through simulation, it was shown that with increase in height-span ratio, the maximum tensile stress and displacement gradually decrease but their drop rates are gradually smaller, while the maximum compressive stress firstly decreases and then slightly increases; if height of grid structure increases from 3.5 m to 6.3 m, the maximum displacement decreases by 53.66%; increase in column spacing causes the maximum stress and displacement increase, but their growth rates are gradually smaller; under grid structure height of 3.5 m, column spacing increases from 4.5 m to 13.5 m, the maximum displacement increases by 22.63%; increase in corrosion rate causes slow increase in maximum stress and displacement, and effects of corrosion on structural stress is a gradual accumulation process, which does not suddenly cause a sharp drop of structural performance.Furthermore, Latin hypercube sampling method was used to evaluate the probability of structural failure under effects of multidimensional uncertain parameters, taking the allowable deflection specified in “Technical Specifications for Space Grid Structures” as the evaluation criterion.The results showed that under H1L2 working condition of 3.5 m structure height and 5.3 m column spacing, the failure probability without corrosion is 0.27%; when corrosion rate is 40%, the failure probability increases to 22.76%.

Here, to obtain a reasonable limit value for deflection-span ratio of a large-span highway suspension bridge, a certain domestic suspension bridge under construction was taken as the study object.Firstly, the sensitivity analyses for structure and gravity stiffnesses of different components were performed with the finite element method to establish the stiffness regulation method.Secondly, taking driving safety and driving comfort as evaluation indexes, stiffness sizes were adjusted for multi-working condition vehicle-bridge analysis to obtain range of stiffness values exceeding limit values of driving safety and driving comfort.Finally, the stiffness reduction amplitude was reduced until driving safety and driving comfort results could reach their limit values and the bridge deflection-span ratio limit value could be obtained based on driving performance using reverse deduction.The study results showed that vertical structural stiffness of suspension bridge is mainly controlled by main beam and main cable, while its lateral structural stiffness is mainly controlled by main beam and bridge tower; reducing structural stiffness and gravity stiffness of main beam and main cable can more obviously affect the overall stiffness, but their affecting degrees are different; limit values for vertical and lateral deflection-span ratios of main beam of a super large-span highway suspension bridge are approximately 1/150 and 1/80, respectively under conditions to satisfy driving safety and driving comfort.

Vibration excitation in environment has randomness and diversity.Here, aiming at traditional energy harvester’s single energy harvesting direction and low energy harvesting efficiency, a multi-directional bending piezoelectric vibration energy harvester with nonlinear magnetic force was proposed, it could collect mechanical vibration energy in multiple directions and improve energy harvesting efficiency.The finite element model of the energy harvester was constructed using the simulation software COMSOL Multiphysics, and modal analysis, harmonic response analysis, and electric response analysis of the model were completed.Meanwhile, effects of key factors of bonding position of piezoelectric sheets, external resistance, magnetic repulsion, excitation acceleration and magnetic distance on output response characteristics of the energy harvester were deeply explored with tests.The results showed that introducing magnetic force can effectively broaden energy harvesting frequency band and improve output power; when excitation acceleration is 1g and magnetic distance is 20 mm, the device’s output power reaches 0.8 mW; in addition, parameters of piezoelectric sheet ponding position and external resistance have a significant impact on energy harvesting performance.

The submerged floating tunnel (SFT) is an ultra-long underwater traffic structure. The research on its vortex-induced vibration (VIV) under currents by considering the effects of the intermediate supporting stiffness and boundary stiffness, and the prediction of VIV amplitudes are crucial. The connections between the tube and the intermediate cables, boundaries at both ends are equivalent to vertical and rotational elastic constraints with stiffness close to engineering reality. A VIV model for the cable-supported SFT considering both types of stiffness is established, and the interaction between the current and the tube is considered by a wake oscillator. The designing parameters and constraints stiffness for the SFT are proposed by referring the existing literatures. The influence of various combinations of intermediate and boundary stiffness on the VIV characteristics are discussed. The results indicate that the SFT tube exhibits similar VIV patterns with different numbers of tube segments. An increase of stiffness can suppress the excitation of higher-order frequency modes. Within the locked interval, the vibration frequency can reach about 1.20 times the natural frequency within certain current ranges. Nonlinear phenomena such as sudden change of response amplitudes in a cliff like manner, energy conversion between modes, "beat", and quasi-periodic motion are observed in the VIV response.

Ultra-high voltage (UHV) transmission tower is of great significance to national energy security and economic development. It is necessary to evaluate its dynamic characteristics for safe operation. Taking a typical 1000kV UHV angle steel transmission tower as an example, the response data are collected by ambient excitation method in the full-scale field test. To reduce noise interference, the coherence-clustering theory is integrated with the traditional Bayesian method. An automated Bayesian modal identification method for UHV transmission towers is developed. The validity of the proposed method is verified by numerical model. The accurate modal parameters and the associated uncertainty quantification are identified. It is shown that the proposed method could effectively reduce noise interference, which is appliable for automated modal identification of UHV transmission towers. The fundamental natural frequency of the tested 1000kV UHV transmission tower is 1.39Hz and the corresponding damping ratio is 3.30%. The first six mode shapes are bending and torsion on both main axes in turn. The uncertainty of damping ratio is significantly higher than the mode shape and the natural frequency, which shows that damping ratio is more discrete. The result could provide valuable basis for structural health monitoring and dynamic analysis of UHV transmission towers.

Large-span flexible photovoltaic arrays are highly susceptible to structural failure under maximum thrust at a 0° wind direction. Current standards primarily focus on wind load calculations for flexible photovoltaic supports but lack comprehensive research on wind load reduction strategies. To enhance the wind resistance of these arrays, this study innovatively designs and tests four types of flow disturbance devices: >, <, Γ, and L types. Wind tunnel experiments with synchronized pressure measurements on both the upper and lower surfaces of the arrays were conducted, considering and not considering the disturbance devices. The study analyzed their effects on average, fluctuating, and extreme wind loads, as well as on torque. Principal component analysis (PCA) was employed to assess load reduction performance, and CFD simulations were used to explore the underlying mechanisms. The results indicate that all four disturbance devices significantly reduced the average wind pressure coefficient, extreme positive pressure coefficient, and torque coefficient at maximum thrust under a 0° wind direction, with minimal effects on fluctuating wind pressure and extreme negative pressure coefficients. The load reduction performance of the devices ranked as follows: >, <, Γ, and L types, with performance indices of 4.133, 4.022, 2.388, and 1.746, respectively. The continuous low-pressure region formed by the separation of incoming flow at the disturbance devices and the local low-pressure region resulting from vortex reattachment are the dominant factors leading to substantial load reduction on the first and rear rows of photovoltaic panels, respectively.

Carbon fiber reinforced polymer shaft is the future development direction of ship transmission system, which has an advantage of light weight, high specific stiffness and strong vibration reduction performance. Its vibration characteristics are always calculated by commercial finite element software. The study takes a ship composite shaft as research object and obtain its equivalent bending stiffness by three-dimensional analytical model firstly. Then, constructing the composite shaft lateral vibration model by transfer matrix method. The accuracy of the model was verified by finite element method. Finally, this paper analyze the influence of composite layer angle, layer thickness and layer angle order on shaft lateral vibration performance. The result shows that: adjusting the composite shaft layup angle can regulating its natural frequencies and vibration shape effectively due to the change of composite shaft bending stiffness. And the higher vibration order, the more obvious the regulation effect. However, the effect of layer thickness and layer angle order is relatively weak. The obtained results have certain significance for composite shaft lateral vibration performance rapid prediction and composite layer design.

Collision floe load is an important factor affecting the safety of polar ocean structures. Based on the co-simulation approach between CFD software STAR-CCM+ and FEM software Abaqus, a numerical model for calculating the interaction between structure-floe-water was constructed, and the collision response between cylindrical structure and square floe was studied. The influence of different factors on collision response was analyzed. Furthermore, from the perspective of energy conversion, a collision force correction model considering the initial rotation of floe is proposed. The influence of pre-collision, collision and post-collision stages on the peak value of collision force is analyzed, and the rapid estimation of collision load of floe with initial rotation is realized. It is found that the velocity attenuation of floe before collision, the duration of collision and the rotation of floe after collision have great influence on the collision force. The collision force increases first and then decreases with the increase of the rotation angle of floe. 

Due to the significant wind and structural bluntness effects in the service environment, the optical accuracy of heliostat is prone to decrease under wind loads. Therefore, the design needs to consider the stress conditions under various working states and aerodynamic shapes. Based on the theory of atmospheric boundary layer, taking into account the effects of the elevation angle, wind direction angle, aspect ratio, and column height on wind load. An analytical expression for aerodynamic coefficients of heliostat is established, and the recommended values for these coefficients are discussed. The results indicate that the elevation angle and wind direction angle are the determining factors of aerodynamic wind loads. As the elevation angle increases, the resistance coefficient, lateral force coefficient, lateral moment coefficient, overturning moment coefficient, and azimuth moment coefficient gradually decrease. The drag coefficient, lift coefficient, and overturning moment coefficient decrease with the decrease of the angle between the incoming flow and the mirror surface, and the wind direction angle has a significant impact on the uneven force distribution of the heliostat. Increasing the aspect ratio is beneficial for reducing aerodynamic loads. The column to height ratio increased to 0.75, and the moment coefficient increase by nearly 50%. By analyzing the variation law of the six component force coefficients, the analytical expression for the aerodynamic coefficient is proposed to predict the wind load of heliostat structure. When designing the structure of a heliostat, the six component coefficients can be taken as 1.42, 1.0, 1.0, 1.03, 1.53, and 0.18. 

Aiming at the finite element modeling problem of the dynamic characteristics of multilayer elastic diaphragm bolted joints, a method of equivalent modeling of subarea thin-layer elements is adopted, and a method is proposed to accurately calculate the material parameters of each area of subarea thin-layer elements. Taking the diaphragm coupling in the marine propulsion shaft system as an example, the accuracy of the simplified model is verified by comparing the dynamics of modal and vibration level drop between test and simulation. The research results show that: The research results show that: the subarea thin-layer elements modeling method can effectively simplify the modeling of the dynamic model of the diaphragm coupling under the consideration of bolt preload, the rough surface constructed on the basis of the fractal theory can accurately calculate the contact stiffness of the bolt joint, and the material parameters of the subarea thin-layer elements calculated by it can accurately analyze the dynamic characteristics of the multilayer elastic diaphragm bolted couplings.

Fast and efficient prediction of structural response under crowd walking loads is of great significance for the structural vibration serviceability assessment and design. According to the stochastic vibration theory, a response spectrum was proposed to predict structural root-mean-square (RMS) acceleration due to crowd walking in this study. The pedestrian walking condition was categorized into three traffic status based on the crowd density: unconstrained traffic, weakly and exceptionally constrained traffic. The power spectral density (PSD) matrix of crowd walking load derived in a previous study was used to simulate the response in these traffics. The relationship between the response spectrum for different structural damping ratios and crowd sizes was investigated to establish the mathematical expressions for the design spectrum. Comparison of the RMS predicted values of response spectrum acceleration with the measured values of the footbridge shows that the proposed response spectrum prediction results are reasonable, and the response spectrum method can quickly predict the acceleration response of the structure under crowd walking load.

The bifurcation and chaotic behaviour of a two-degree-of-freedom fractional-order parametrically excited system under harmonic excitation are studied. The Melnikov method is used to analyse the necessary conditions for bifurcation and chaos in the sense of Smale horseshoe in a two-degree-of-freedom fractional-order parametric excited system, and its analytical results are obtained. The obtained analytical results are compared with the results of the numerical iterative algorithm. The results show that the change trend of the chaotic threshold curves obtained by the two algorithms is consistent and the degree of consistency is high, which confirms the accuracy of the obtained chaotic threshold analytical curve. The dynamic response characteristics of some typical points are analyzed using the maximum Lyapunov exponent diagram, phase diagram, time history diagram, frequency diagram and Poincare section diagram, and the path for the system to enter a chaotic motion state is obtained. The rationality of the chaotic boundary conditions of the system calculated based on the Melnikov method is explained in detail. Finally, the influence of various system parameters on the chaos threshold curve is analyzed. The research shows that increasing the fractional-order coefficient, parametric excitation coefficient, linear damping coefficient and coupling damping coefficient can suppress the occurrence of chaos; while increasing the linear stiffness coefficient, nonlinear stiffness coefficient and the fractional-order number sometimes increases the possibility of chaos in the system. The above conclusions can provide analysis references for practical applications and have certain guiding values for the design and control of such systems.

random vibration fatigue tests were conducted on the high-frequency brazed pipes with spatial configurations, and a frequency-domain multiaxial vibration fatigue life prediction approach considering the multiaxial mean stress effect was proposed in this paper. Firstly, uniaxial vibration fatigue tests were conducted on brazed pipes with different filling pressures under broadband stochastic base excitation. Then, based on the equivalent mass method, the finite element analysis method was used to calculate the static stress level at the critical node of the brazed pipe under different filling pressure conditions. Next, based on the random vibration theory, the finite element analysis method was applied to compute the power spectral density functions with multi-order modal response of each stress component at the critical node of the brazed pipe in the broadband frequency domain. Finally, the equivalent Lemaitre stress criterion and Goodman mean stress correction criterion was used to estimate the vibration fatigue lives of brazed pipes under different operational conditions, and the predicted results were compared with experimental ones. The comparison results indicate the frequency-domain multiaxial fatigue criterion has high-accuracy in predicting the vibration fatigue life.

The stiffened plate structures are widely used in engineering applications, and the rational layout of the stiffeners can effectively enhance the stiffness and load-bearing capacity of these structures. In order to achieve optimal stiffener layout design for thin plate structures, a new dynamic topology optimization method tailored for multi-phase material stiffened structures is proposed. Firstly, the stiffeners and thin plate are respectively considered as strong and weak materials and characterized by different bending stiffness, with use of equivalent stiffness method; Next, the Hilber-Hughes-Taylor-α (HHT-α) method is employed to solve the dynamic finite element model, and dynamic sensitivity analysis is conducted using the adjoint variable method with the discretize-then-differentiate approach; Furthermore, the effectiveness of the dynamic topology optimization method for stiffened plate structures is validated through a comparison of stiffener distribution topology optimization examples of a corner simply supported square plate with traditional methods. Finally, the stiffener topology optimization design is carried out for several typical thin plate structures using both single-phase and bi-phase materials under various loading and boundary conditions. The results show that the proposed dynamic topology optimization method for stiffened plate structures demonstrates flexible and effective optimization capabilities under dynamic conditions. By introducing bi-phase materials, the issues related to continuity distribution in single-phase materials are successfully overcome through reasonable material distribution and refined structural design. The optimized stiffener structure is continuous with complete force transmission paths, and significantly outperforms traditional methods.

To address the issues of insufficient curve negotiation performance and severe wheel-rail wear caused by the prevalence of small-radius curves on intercity lines, this paper focuses on intercity electric multiple units (EMUs). An actuator was laterally installed between the axle box and bogie to form an active radial bogie. This actuator enables lateral movement of the wheelset, allowing the vehicle to follow a pure rolling line. A actuator system model was developed, and a fractional-order PI controller was employed to verify the actuator's rapidity, accuracy, and stability in tracking the desired trajectory under load disturbance conditions. Using the SIMPACK and MATLAB/Simulink software, a dynamic model of the active radial intercity EMUs was established. The study analyzed dynamic indexes such as wheelset yaw angle, wear number, lateral wheel-rail force, and derailment coefficient to evaluate the effect of operating speed and curve radius on the vehicle's curve negotiation performance. Additionally, the Jendel wear model was used to assess the wheel-rail wear performance when the vehicle passing a 500-meter curve radius. The results show that using the distance from the pure rolling line to the centerline of the track as the displacement control target for the actuator is reasonable. When passing the curved track with a radius of 500 meters, compared with traditional passive vehicles, the new type of active radial vehicle shows a 12% reduction in maximum lateral wheel-rail force, an 8% decrease in maximum wheelset coning angle, the derailment coefficient decreased by 20%, and the maximum wheel wear number decreased by 20%. The wear depth of the outer and inner wheels of the first wheelset was reduced by 31% and 12%, respectively, and the wear depth of the outer and inner rails of the curved track was reduced by 20% and 15%, respectively. Therefore, this type of active radial bogie significantly improves the vehicle's curve negotiation performance and effectively reduces wheel and rail wear.

Since the vibration signals generated by the suspension system of a high-speed train during operation are typical nonlinear signals with high complexity, coupling and uncertainty, in order to make up for the limitations of the one-dimensional signals in fault diagnosis, and taking advantage of the sensitivity of Gramian angular field (GAF) in dealing with the time-series signals as well as its adaptability to the nonlinear signals, a method based on the one-dimensional (1D) time-series signals and the two-dimensional (2D) Gramian angular summation field (GASF) feature fusion of convolutional neural network combined with gated recurrent unit network fusion multi-head self-attention mechanism (1D-2D-CNN-GRU-MSA) for fault diagnosis. The 1D timing signal is first encoded into a 2D Gramian angular summation field (GASF) map, and then the 1D timing signal and the 2D GASF map are fed into two parallel branches simultaneously, respectively. One way is the image input to extract the features of the GASF image via CNN; the other way is the one-dimensional fault waveform directly input to extract the timing features via gated recurrent network unit (GRU), and finally the two-dimensional image features and the one-dimensional timing features are strengthened by the feature focusing and fused with the downscaling via the mechanism of multiple self-attention (MSA), and then the faults of the high-speed train's transverse damper are classified via the Softmax layer. Finally, the Softmax layer is used to categorize the transverse damper faults of high-speed trains. Simulation experiments prove that the 1D-2D-CNN-GRU-MSA model has a higher accuracy than the two mainstream models for identifying transverse damper faults in high-speed trains under different working conditions.

In order to study the evolution law of wheel polygon wear of high-speed railway in severe cold area, a refined nonlinear finite element analysis model of CRTS III plate type ballastless track considering structural reinforced was established based on the ballastless track structure in seasonal freezing area of China, and then a vehicle-track-roadbed coupling dynamic model based on wheelset, frame and track flexibility was established. Combined with the MATLAB prediction model suitable for calculating the long-term wear evolution of wheel circumference, the evolution law of wheel polygon circumference wear under different temperature gradients was studied, and the influence of uneven frost heave deformation of roadbed on wheel polygon circumference wear evolution in cold regions was further analyzed. The results show that in the temperature gradient range of 20℃~-40℃, the evolution rate of wheel polygon wear will be accelerated in cold environment. The level of wheel roughness and the amplitude of polygon in the late wear period are significantly greater than that in normal temperature environment, and the fluctuation amplitude is even more than twice. The frost heave amplitude of roadbed mainly affects the wear evolution rate of wheel polygon. The larger the amplitude is, the faster the evolution rate is, but the influence on the wear evolution region is small. Frost heave wavelength mainly affects the accumulation position of wheel wear. With the increase of wavelength, the wear will be uniformly superimposed on the wheel, and the larger the wavelength, the more regular wear tends to be, while the frost heave wavelength has little effect on wheel wear rate. The research results can provide a reference for wheel wear in cold regions.

The subway spatial alignment significantly affects the wear of steel rails. If the impact of spatial alignment on rail wear is considered during the alignment design phase, optimizing the alignment can reduce rail wear at its source. However, there are infinitely many feasible alignments, a vast array of alternatives must be designed, compared, and analyzed during the alignment design phase. The existing method of establishing simulation models to calculate rail wear is extremely time-consuming, significantly reducing design efficiency and resulting in unacceptable computation times. In response, this paper employs artificial neural networks to explore the relationship between subway spatial alignment and rail wear, enabling efficient and accurate predictions of rail wear under various alignments. First, a rail wear calculation model is developed based on the prototype of subway car type A. Based on this, the impacts of alignment parameters on the wear of inner and outer rails are analyzed, and a sample dataset of rail wear under various alignments is created. Next, a rail wear prediction neural network model that considers alignment parameters such as curve radius, curve length, transition curve length, gradient, gradient difference, and superelevation is established, along with an optimization method for the model based on Sobol analysis. Finally, through training with the sample data, the mapping relationships between subway spatial alignment and rail wear are established. The research results show: 1. For inner and outer rails, the same alignment parameters have different impacts. For inner rail wear, the transition curve length, curve radius, and superelevation are the main influencing parameters; for outer rail wear, the curve radius is the main influencing parameter, and its impact is far greater than the other alignment parameters. 2. Rail wear can be accurately predicted based on subway spatial alignment parameters, with prediction accuracies for inner and outer rail wear reaching 98.11% and 94.02% respectively. 3. Optimizing the model through Sobol analysis enhances prediction accuracy, with the accuracy for inner and outer rail wear increasing by 7.14% and 26.29%, respectively.

To investigate the P2 resonance characteristics of the resilient wheel-rail system, a systematic analysis was conducted using field tests and a theoretical model. The experimental tests measured the axle box vibration acceleration characteristics of the train within the speed range of 40~80 km/h. A dynamic theoretical model of the resilient wheel-rail system was established, and the frequency equation of the coupled system between the resilient wheel and the track was derived. The experimental results indicate that the P2 resonance frequency of resilient wheels is lower than that of rigid wheels, and the influence of train speed on the P2 resonance frequency is not significant. At the same speed level, the axle box vibration acceleration amplitude of the train with resilient wheels is lower than that of the train with rigid wheels. Based on the theoretical model, the influence mechanism of track parameters and resilient wheel parameters on the P2 resonance frequency was further explored. The study found that compared with rigid wheels, the P2 resonance frequency of the resilient wheel-rail system decreases, with key influencing factors including wheel mass, radial stiffness of the rubber layer, and the mass ratio of the rim. When the radial stiffness of the rubber layer exceeds 300 MN/m, the influence of wheel mass on the P2 resonance frequency becomes more significant. When the radial stiffness of the rubber layer is less than 300 MN/m, the radial stiffness of the rubber layer and the mass ratio of the rim have a more pronounced impact on the P2 resonance frequency. Additionally, as the track foundation elastic coefficient increases, the P2 resonance frequency rises, and the influence of the radial stiffness of the rubber layer also gradually strengthens. Based on the influence of wheel-rail parameters on the resilient wheel's P2 resonance frequency, the P2 resonance frequency of the wheel-rail system can be optimized by adjusting wheel mass, rubber layer radial stiffness, and rim mass ratio, thus avoiding resonance with the natural frequency of the frame to reduce the risk of fatigue failure in the frame caused by potential P2 resonance. This study provides an important theoretical basis for the design optimization of resilient wheels and vibration control of the wheel-rail system.

Considering the nonlinear factors involved in vehicle dynamics on different road surfaces, including tire lift-off, suspension hitting bump stops, and the time-delay characteristics of suspension damper system, a nonlinear vehicle-suspension system dynamic model is established based on the measured data of different valve-controlled semi-active suspensions. By using a designed augmented Kalman filter and analyzing the accuracy of selected sensors, an identification algorithm for road surface irregularities is designed to effectively evaluate prevailing road with different roughness road and speed conditions. Three different control strategies for an electronically controlled semi-active suspension system are designed. The optimal control currents for each strategy are optimized by using a designed multi-objective particle swarm algorithm. And the control effects under various road excitation levels are analyzed based on simulation results. The results indicate that all three control schemes can improve vehicle performance compared to passive suspensions, in which the dual-valve electronically controlled semi-active suspension exhibits the best performance and better adaptability to the time delay of damper systems. The research can provide significant insights for the design of practical control algorithms for vehicle semi-active suspensions.

Hydraulic equipment undergoes multi-domain energy conversion during operation. Especially under variable operating conditions, this process typically exhibits non-linearity and non-stationarity, which poses challenges for condition monitoring and fault diagnosis. The study introduces the utilization of the instantaneous speed (IS) signal for fault diagnosis of axial piston pumps. The IS serves both as a system dynamics parameter and a condition monitoring variable, offering significant advantages when the pump operates under non-stationary conditions. Through theoretical analysis, it has been concluded that the fluctuation components of the IS signal contain information about the health status of pumps. The synchro-extracting normal S transform (SNST) is proposed for performing line-pass filtering on the signal. The K-medoids method is then applied to cluster the angular eigenvalues of the filtered and reconstructed IS fluctuation signals. Experiments under variable speed and load conditions were conducted on an integrated mechatronic-hydraulic platform, successfully diagnosing faults in the axial piston pump's swashplate under normal, slight wear, and severe wear conditions. The research findings provide new methodologies for monitoring the operating status and diagnosing faults in hydraulic equipment.

To address the issue of negative transfer caused by domain shift and noise interference in non-homogeneous fault data within the industrial application of transfer learning, this paper proposes a clustering-guided unsupervised smoothness transfer diagnosis method. First, the Singular Spectrum Decomposition technique is used to denoise the data, eliminating the interference of other frequency band components in the fault signal. Then, based on a one-dimensional convolutional neural network, an unsupervised domain adversarial transfer network is constructed. A smoothness domain adversarial training strategy is introduced to achieve smooth minimal task loss and enhance the generalization ability in the target domain. Next, a discriminative clustering method is designed to learn domain-invariant feature space and optimize the discriminative classification information of target domain samples, thereby improving unsupervised clustering performance and suppressing negative transfer. Finally, this transfer diagnosis method is applied to recognize the health status of rolling bearings under multiple cross-device and varying operating conditions. Experimental results show that the proposed method can sufficiently bridge the difference between the source and target domains, improving the transfer diagnosis accuracy and generalization of non-homogeneous machinery.

To address the issue of high annotation costs for bearing fault data in practical engineering, which leads to insufficient labeled samples for supervised model training, a semi-supervised fault diagnosis method for rolling bearings based on contrastive learning with twin representations is proposed. Firstly, Gaussian white noise is added as a data augmentation method to apply different degrees of perturbations to the unlabeled data, generating positive pairs. Simultaneously, a twin self-correcting convolutional neural network with shared weights is constructed to extract high-dimensional features from the positive pairs. Secondly, based on the contrastive learning strategy, a negative cosine similarity loss function is constructed to compare the features of the positive pairs. By maximizing the correlation between features, supervisory information is built for the pre-training stage, promoting the model to learn consistent feature representations of samples from different perspectives in the unlabeled data. Then, a small number of labeled samples are introduced for fine-tuning, establishing the mapping relationship between feature representations and labels. Finally, the test data is input into the fine-tuned encoder model to achieve semi-supervised fault diagnosis of rolling bearings. The proposed method learns the intrinsic structure and feature representations of the data from a large amount of unlabeled data, without relying on an expensive annotation process. Experiments conducted on the collected rolling bearing data and the public HUST bearing dataset verify that the proposed method achieves an accuracy of over 97%, demonstrating its excellent diagnostic performance.

Modal parameters are commonly used in structural damage identification (SDI) due to their ease of acquisition and sensitivity to structural damage. SDI methods based on modal parameter and finite element model can effectively localize and quantify structural damage. However, due to the combined effects of measurement noise and model errors, the identification results may deviate significantly from the actual situation, making it difficult to accurately assess the safety state of the structure. To address this issue, a new SDI method based on truncated total least squares (TTLS) and L1 regularization techniques is proposed. This method first analyzes the sources of error, then using the TTLS, a new approximate relationship between the change in damage reduction coefficients and the change in modal parameters is established. Finally, it employs L1 regularization to constrain problem using the sparsity of structural damage, improving the ill-posedness of the problem and identification accuracy. Numerical simulations and experimental results demonstrate that the proposed method can effectively identify various damage scenarios in the structure, with fewer misjudgments, exhibiting high identification accuracy and strong robustness.

The Superlet Transform (SLT), which is a novel high-resolution time-frequency analysis method, is obviously superior to classical time-frequency analysis methods such as the Short-time Fourier Transform and the Continuous Wavelet Transform in terms of energy aggregation and noise robustness. However, when applying SLT to bearing vibration signals with widely distributed and sparse frequency components, meeting diagnosis requirements in practical becomes challenging. To enhance computational efficiency, Energy Distribution based Adaptive SLT (ED-ASLT) is proposed. Firstly, the frequency energy distribution of signal is obtained based on Welch method. Then, the superlets center frequencies adaptive sampling is carried out based on the energy distribution. Then, the window lengths of wavelets in each superlet are determined according to the center frequency value and the energy at the center frequency. Finally, the superlets are constructed to complete the time-frequency analysis. The ED-ASLT method can identify the key frequency bands that may reflect fault information in the signal according to the energy distribution of the specific fault signal, determine the SLT parameters adaptively, and perform high energy aggregation, high noise robustness and efficient time-frequency analysis of the signal, which is helpful for more accurate time-frequency positioning of the abnormal components in the signal and resist the interference of noise. Improve the accuracy and efficiency of fault diagnosis. The ED-ASLT method were compared with other time-frequency analysis methods in terms of energy aggregation, noise robustness and time cost by using bearing vibration signals from laboratories of Paderborn University and Southeast University. It is verified that the proposed method can greatly reduce the time cost while maintaining the advantages of high energy aggregation and high noise robustness of SLT, which is helpful to provide higher-quality criteria for fault diagnosis.

The impact of high-level landslide on building clusters often leads to serious casualties. Based on the numerical model of smooth particle hydrodynamics-discrete element method-finite element method (SPH-DEM-FEM) coupling, this paper studies the impact process, the failure mechanism of building structures, the time history of impact force and the stress and bending moment at the key points of frame columns of high-level landslide on frame structure buildings. The results show as follows：SPH-DEM-FEM coupling numerical method can effectively simulate the projectile bounce and climb of the rock (DEM) mixture in the gravel soil landslide (SPH). Considering the combination layout of three rows of regular buildings perpendicular to and parallel to the landslide flow direction, the longitudinally arranged buildings at the near end of the landslide show continuous dumping damage, while the horizontally arranged buildings show overall dumping damage. Due to the dissipation of impact energy from the front row buildings on the landslide and the friction energy consumption of the landslide itself, the building at the back end of the landslide shows local damage to the wall and front row columns on the drainage surface, and the structure remains stable, the damage degree is in the order of buildings without energy consumption in the upstream, horizontal arrangement and vertical arrangement in turn. The impact attenuation amplitude of buildings arranged vertically and horizontally is 31% and 21% respectively. The damage mechanism of the overall toppling of the transverse frame building is the direct shearing of the frame column or the failure of the node plastic hinge. The damage mechanism of the continuous toppling of the longitudinal frame building is that the failure of the front frame column causes the axial pressure and limit bending moment of the rear frame column to increase, and the continuous impact load exceeds its limit bending moment, resulting in the bending failure of the rear frame column and the final structural toppling.The system energy is converted between kinetic energy, internal energy and friction energy, of which friction energy accounts for 65.5% and structural energy accounts for 23.6%. The rapid decline of kinetic energy and sharp increase of internal energy are the key characteristics of building failure.

Due to the influence of complex geological conditions in the blasting process, the vibration signal is mixed with a large amount of noise, which covers the real information of the signal to a certain extent. In order to effectively reduce the noise part of blasting vibration signal, a denoising method combining Artificial Protozoa Optimizer (APO), Variational Mode Decomposition (VMD) and wavelet threshold is proposed to obtain the real time domain and frequency domain information of vibration signal. This method uses the APO algorithm to find the intrinsic mode number K and the penalty factor α that make the best VMD decomposition effect. Then, VMD is used to adaptively decompose the noisy signal, and the noisy modal components with small variance contribution rate are eliminated. The retained modal components are subjected to wavelet threshold denoising processing, and finally the reconstructed denoised real signal is obtained. The simulation signal and the field measured blasting vibration signal are used as the initial signals, and the APO-VMD combined wavelet threshold, empirical mode decomposition, wavelet threshold denoising, VMD and other methods are used to denoise them. The results show that the APO-VMD combined wavelet threshold method can effectively remove the noise signal and make it maximally guaranteed.

Shelterbelts significantly contribute to intercepting rockfalls. However, due to the structural complexity and anisotropic properties of the "crown-trunk-root-soil" system, research on the mechanisms of rockfall interception and energy absorption by trees remains limited. To address this gap, a three-dimensional numerical simulation model was developed to represent the entire plant structure within the "crown-trunk-root-soil" system. This model investigates how individual trees influence the blocking effect and energy absorption during rockfall impacts under varying collision conditions. Results indicate that trees can block rockfalls and absorb impact energy through a multi-layered structural response: crown buffering and trunk carrying, roots provide anchorage, and the soil facilitates dissipation. The energy absorption rate of the tree decreases with increasing kinetic energy of the rockfall, and the peak impact force increases with increasing kinetic energy of the rockfall. However, both the energy absorption rate and peak impact force exhibit a decreasing trend with increasing impact height and eccentricity. During a rockfall-tree collision, approximately 75% of the kinetic energy is absorbed within the first 25 ms, primarily through canopy shaking and trunk breakage damage. When rockfall kinetic energy is low, the tree structure absorbs around 80%-90% of the energy, while the root-soil system and surrounding soil absorb the remaining 10%-20%. The energy absorption rate of rockfalls by trees tends to increase and then decrease with increasing impact angle, the root-soil system and surrounding soil absorb between 15% and 25% of the impact energy. The research results can provide a theoretical basis for the optimal design and application of protection forests for rockfall disasters.

Pyramidal Lattice Sandwich Panel (PLSP), a type of periodic topology with high porosity, which has broad application prospects in the modern military equipment field owing to its excellent mechanical properties such as lightweight, high strength, high specific stiffness characteristics, anti-explosive and impact resistance performance. The AlSi10Mg aluminium alloy PLSP is successfully prepared by additive manufacturing selective laser melting (SLM) to implement the drop hammer impact test, which reveals the failure mechanism and damage mode of PLSP under impact loadings. Based on the explicit finite element (FE) method, a simplified beam unit core FE model is established to simulate the dynamic responses of PLSP subjected to drop hammer impact, validity and reliability of the FE model is verified through the comparative analysis of failure modes and impact force-time curves. Then, a FE model of PLSP with the same surface density and armor steel-aluminium alloy-armor steel multi-materials for the Front face-pyramidal Core (PLC)-Back face is established, and the influences of structural parameters on impact resistance are numerically simulated based on the single variable method in terms of transient maximum Back face deflection (MaxD) and PLSP Energy Absorption (EA). The results show that impact resistance of armor steel-aluminium alloy-armor steel PLSP is significantly improved compared to that of aluminium alloy with same surface density, and the overall configuration of PLSP is basically intact. The core thickness, the core layer and the Front face thickness have great influences on impact resistance. These research results can provide theoretical basis and technical support for the designing and safety of lightweight, impact protection equipment. 

In order to investigate the energy dissipation characteristics of concrete slabs under low-velocity impact, 14 groups of plain concrete slabs were tested by using a drop hammer test device. The impact process of each group was numerically simulated by using the Continuous Surface Cap Model (CSCM) combined with the nonlinear display dynamic analysis software LS-DYNA. The energy change of the specimen during the impact process was found through the law of conservation of energy. The effects of different concrete strengths, impact velocities and concrete slab thicknesses on the energy dissipation characteristics of concrete slabs and their destructive effects were analysed. The results show that the impact force increases with the increase of the impact velocity of the drop hammer. The dynamic change process of the concrete slab during the low-velocity impact is mainly divided into the elastic stage, the plastic stage and the complete destruction stage. The downward deflection of the concrete slab increases with increasing impact velocity, showing a better parabolic relationship. When the impact velocity is higher, it will show a stronger erosion effect. The more energy consumed by the kinetic energy of the concrete fragments and the kinetic energy of the drop hammer during the fracture process, the less energy is applied to the crack expansion. This study can provide a reference for bridge deck slabs and pavements to prevent low-velocity impact effects for the design of rockfall hazard protection projects.

The drag coefficient Cd and the inertia force coefficient Cm of underwater pile structures are critical factors influencing the reliability of calculations when the Morison equation is applied under conditions of small Keulegan–Carpenter (KC) numbers. Currently, there is no standardized method for determining these coefficients, nor is there a unified approach to assess their accuracy. Furthermore, comprehensive analyses of the factors influencing these coefficients remain limited. To address this issue, this study utilizes two-dimensional computational fluid dynamics (CFD) simulation data to establish a model for optimizing the coefficients in the Morison equation using the ensemble Kalman filter method. A prior data preprocessing strategy is introduced to prevent non-physical fitting and support rapid iterative convergence of the equation system. Additionally, error judgment indicators for time-series data are proposed to enhance the reliability of the calculations. To validate the approach, a series of computing cases were designed, including variations in cross-sectional shapes, vibration amplitudes, and vibration periods. The results demonstrate that the ensemble Kalman filter-based method achieves a balance between computational accuracy and efficiency, effectively modeling the relationship between Cd, Cm, and hydrodynamic forces under nonlinear and complex conditions. Furthermore, this method provides valuable data guidance and a mathematical foundation for similar application scenarios, improving the precision of simulations involving underwater structures.

To investigate the impact of CFRP sheet strengthening on the seismic performance of corroded reinforced concrete (RC) rectangular columns, seven RC rectangular column specimens were designed and fabricated. Six specimens underwent accelerated corrosion using an external-current-surface coating method. Following the corro-sion process, three of the corroded columns were strengthened with CFRP sheets. Quasi-static tests were conducted on all seven specimens to analyze their failure modes, hysteresis curves, skeleton curves, displacement ductility, stiffness degradation curves, cumulative energy dissipation curves, equivalent viscous damping ratios, curvature distribution, displacement composition, and effective stiffness. The results demonstrate that rebar corrosion signifi-cantly diminishes the seismic performance of the specimens. At a corrosion rate of 15.09%, the peak load, displace-ment ductility ratio, and energy dissipation capacity of the specimens decreased by 37.5%, 14.2%, and 32.8%, re-spectively. Conversely, CFRP sheet strengthening effectively enhances the seismic performance of corroded speci-mens. Compared to the unstrengthened corroded specimens C1, C2, and C3, the CFRP-strengthened specimens. C1R, C2R, and C3R exhibited increases in peak load of 11.57%, 4.97%, and 13.32%, improvements in ductility ratio of 7.0%, 7.2%, and 12.2%, and enhancements in total cumulative energy dissipation of 112.10%, 91.35%, and 166.12%, respectively. As the corrosion rate increases, the effective stiffness of the specimen gradually decreases. To address this behavior, a predictive formula for estimating the effective stiffness of corroded RC rectangular columns is proposed. The formula demonstrates high accuracy and low dispersion when fitted to the experimental data.

Porous leading edges have been successfully applied to reduce rod-airfoil interaction noise, but the underlying flow mechanism is still unclear. A time-resolved PIV was used to conduct detailed experimental tests on the flow field near the cylindrical wake and airfoil leading edge. By comparing the average velocity, velocity fluctuation, turbulent kinetic energy, and normalized vorticity between a baseline leading edge and a porous leading edge, the flow mechanism of rod-airfoil interaction noise reduction was revealed. The results show that the cylindrical wake upstream of the porous leading edge has lower average velocity and velocity fluctuation, and the difference is greater when it is closer to the airfoil leading edge. The turbulent kinetic energy and rotational speed significantly decrease near the porous leading edge, but the rotational speed increase away from the wall and the maximum rotational speed may be greater than the baseline rod-airfoil configuration. The key physical mechanism for rod-airfoil interaction noise reduction using porous leading edges is the decrease of the impinging speed and turbulent kinetic energy upon the airfoil leading edge, and faster dissipation of shedding vortices and turbulence around the airfoil leading edge.

Addressing the issue of low-frequency noise suppression in ultra-high-voltage AC transformers, a multi-layer heterogeneous acoustic metamaterial was designed by leveraging the complementary sound absorption and insulation properties of pendulum-arm thin-film acoustic metamaterials and space-folding acoustic metamaterials. Finite element method was employed to establish simulation models for both types of acoustic metamaterials, exploring the influence of factors such as film thickness, film prestress, pendulum arm length, mass block shape, baffle layer number, perforated plate hole radius, and cavity length on their sound absorption and insulation performance. The metamaterial structure was optimized, and a finite element model for the multi-layer heterogeneous acoustic metamaterial was established. The results indicate that this multi-layer heterogeneous acoustic metamaterial exhibits high sound transmission loss in the low-frequency range, with a minimum sound transmission loss of approximately 37 dB, effectively blocking the transmission of transformer noise. The validity of the simulation method was verified through sound insulation experiments.