To enhance low-frequency vibration suppression in conventional plate structures while enabling concurrent vibration energy harvesting, a Kresling-origami-inspired compression-torsion metastructure plate is proposed in this study.By combining the mechanisms of local resonance with topological metastructure theory, low-frequency multi-bandgap vibration attenuation and elastic wave energy localization are achieved.The band structures and modal characteristics of single-and double-layer compression-torsion metastructure plates are investigated using the finite element method.The bandgap formation mechanism induced by compression-torsion coupling is then revealed based on the modal analysis.Analogous to the quantum valley Hall effect, topological interface states are constructed to localize elastic wave energy at specific interfaces by breaking structural symmetry, and a vibration energy harvesting method based on topological states is designed.Vibration transmission experiments are conducted to systematically validate the low-frequency vibration control and energy harvesting performance of the proposed metastructure.The results show that the low-frequency bandgaps are primarily governed by the translational-torsional coupled modes of the resonators, leading to pronounced attenuation of vibration transmission.Meanwhile, the topological interface states strongly confine elastic wave energy at the interface and exhibit robust immunity to defects.Based on the topological interface states, the designed piezoelectric energy harvesting system achieves a peak voltage of 0.9 V and an output power of 64 μW at the interface region, demonstrating the potential of topological states for vibration energy harvesting.This research provides a novel design strategy for developing lightweight multifunctional metastructures that integrate low-frequency vibration suppression with energy harvesting capabilities.

Wind-induced vibrations of tandem square columns are highly complex because of pronounced aerodynamic interference effects.To examine the effect of the front-column wind attack angle on the wind-induced vibration characteristics of tandem square columns, elastically suspended sectional-model wind tunnel tests were conducted for front-column attack angles from 0° to 45° and four center-to-center spacing ratios.The effects of the wind attack angle of the front column and the center-to-center spacing on the wind-induced vibration of the tandem double columns were studied.The research results indicate that both the wind attack angle of the front column and the center-to-center spacing have a significant impact on the wind-induced vibration characteristics of the tandem double columns.When the wind attack angle of the front column is between 0°and 10°, the tandem double columns are prone to large-amplitude wind-induced vibrations.However, when the wind attack angle of the front column is between 15°and 45°, only the rear column experiences small-amplitude wake-induced vibrations.When the center-to-center spacing is 1.25D and the wind attack angle of the front column is between 0°and 10°, the double columns exhibit large-amplitude vibrations over a wide range of wind speeds.When the spacing ratio exceeds 4D, aerodynamic interference is weakened, and the front column exhibits galloping behavior similar to that of an isolated square column at an attack angle of 10°.

Elastic-wave metastructures composed of unit cells with a single topology and fixed size usually exhibit narrow bandgaps.To broaden the bandgaps, this study investigates elastic-wave metamaterials constructed from composite unit cells with different geometric parameters or topological configurations.Topologically complementary “Yin” and “Yang” cells are first defined.Based on these two basic unit cells, several types of composite cells are designed.To quantify the bandgap broadening mechanism, a bandgap overlap index is further introduced.The band structures of the composite unit cells are calculated using Bloch–Floquet periodic boundary conditions and the finite element method.The variations in bandgap characteristics and the associated broadening mechanisms are then analyzed.the bandgap broadening effect is verified by evaluating the vibration level difference (VLD) of elastic-wave metastructures constructed from periodically arranged composite unit cells.The results show that the composite cells constructed from “Yin” cells can significantly enhance the directional bandgap coverage and introduce additional low-frequency bandgaps.The directional bandgap overlap remains relatively high, indicating that the bandgap superposition effect is predominantly linear.For the composite cells formed by “Yang” cells with different topologies, both the bandgap coverage and the bandgap overlap are comparatively low.This suggests that the bandgap superposition effect is generally nonlinear.For the composite cells composed of unit cells with identical topology but different characteristic sizes, the bandgaps display a linear superposition effect, and the overall bandgap corresponds to the linear summation of the bandgaps produced by the individual unit cells.

Aiming at the issue of pile formation morphology detection for flexible casing piles in karst areas, this paper proposes the concept of using the low-strain method to achieve the detection of the completed pile morphology of flexible casing piles in such regions. A strain wave analysis mathematical model, which considers the three-dimensional wave coupling effects of the pile-soil system, is established to demonstrate the feasibility of the low-strain method for detecting the morphology of flexible casing piles. Through theoretical derivation and field tests, it is found that high-frequency transverse wave interference is the main factor affecting the readability of detection signals. The adjacent averaging method is proposed to effectively suppress interference and reveal the location of cavities. Finally, parameter analysis shows that the height, opening angle, and burial depth of cavities all influence the time-domain characteristics of reflected signals, while the modulus and thickness of the flexible casing determine the degree of pile expansion and the amplitude of reflected signals.

Based on the theory of elastodynamics, the vertical vibration characteristics of a rigid circular foundation resting on an anisotropic subgrade is studied via a semi-analytical method. By introducing a novel Fourier-Bessel series vector function system combined with the dual-variable and position method, the Green's function for a layered anisotropic elastic subgrade subjected to a vertical circular load on the top surface is derived. Using the superposition method, the influence function under a vertical annular load is obtained. The integral least-squares method is employed to determine the densities of discretized annular loads within the foundation-subgrade contact region, and the vertical dynamic compliance coefficient of the rigid foundation is gained using the vertical force equilibrium condition. Through parameter analysis, the effects of the anisotropic modulus ratio, thickness, layering, and heterogeneity of the subgrade soil on the dynamic interaction between foundation and subgrade soil are systematically investigated. The results indicate that the introduction of discretized Love number significantly improves the overall computational efficiency, while soil anisotropy has a significant influence on the vertical dynamic compliance coefficient of the foundation and the vertical displacement distribution of the subgrade.

Coastal girder bridges are highly vulnerable to beam unseating failures under extreme wave actions. Bidirectional shear keys providing both horizontal and vertical restraints can effectively enhance the disaster resilience of bridge superstructures; however, the influence of key design parameters on their restraining performance remains unclear. In this study, numerical simulations are conducted to investigate the effects of three parameters—prestressing level of the shear key, initial gap between the shear key and the girder, and wave height—on the dynamic responses of a bridge subjected to simulated wave loads. The results indicate that the prestress level plays a dominant role in restraining performance: without prestress, the shear key exhibits the poorest restraint with evident residual deformation, whereas a prestress level of approximately 70% of the steel yield strength significantly enhances lateral restraint and effectively suppresses residual displacement; further increasing the prestress to 90% praovides only marginal improvement. The initial gap markedly influences impact-energy regulation: a zero gap induces excessive initial impact forces, while an overly large gap (5 mm) allows excessive kinetic energy accumulation prior to contact, which is unfavorable for structural safety; in contrast, a 2 mm gap achieves a balanced performance between impact mitigation and effective restraint. Moreover, the impact mechanisms vary significantly with wave height. As wave height increases, the wave regime transitions from non-breaking solitary waves to breaking bores, intensifying the compression of the trapped air pocket beneath the bridge deck. Structural responses reach their peak near a critical wave height of approximately 1.32 m and subsequently level off or slightly decrease due to enhanced energy dissipation associated with wave breaking.

To address the high cost, deployment difficulty, and vulnerability to sensor failure associated with conventional dense sensor networks in structural health monitoring, this study proposes a sparse reconstruction method for full-field dynamic strain responses by integrating structural dynamics with compressive sensing theory. First, a sparse representation model of the structural response is established based on the modal superposition principle. Subsequently, by exploiting the temporal continuity of the response, an adaptive regularized subspace pursuit (ARSP) algorithm is developed. Sensor placement is further optimized using the reciprocity criterion and related strategies to improve reconstruction accuracy. Finally, the effectiveness of the proposed method is validated through numerical examples and vehicle–bridge vibration experiments. The results show that the mean relative percentage error of ARSP is 3.86%, which is lower than that of the subspace pursuit (SP) algorithm at 5.65% and the iterative hard thresholding (IHT) algorithm at 23.15%. This study provides a useful reference for structural dynamic monitoring under conditions of limited sensor availability.

This paper investigates an efficient modeling method for foldable thin-plate deployment mechanisms driven by variable-length frames. Firstly, a gradient-deficient spatial beam element with time-varying length is established using the Absolute Nodal Coordinate Formulation under Arbitrary Lagrangian-Eulerian description (ALE-ANCF), which accurately describes large overall motion and bending deformation. The method of adding and deleting nodes is employed to address the issues of matrix singularity and computational accuracy in the elements containing ALE nodes. For thin-plate structures, a thin-plate element model based on the Absolute Nodal Coordinate Formulation (ANCF) is established, and the validity of the aforementioned models is verified through numerical examples such as a variable-length flexible pendulum and a gravitational plate. On this basis, the multibody system dynamics equations for the variable-length-frame-driven foldable thin-plate deployment mechanism are derived. The driving frame of the system is simplified as a time-varying-length beam system, and the contact-collision between folded thin plates is considered. The surface-to-surface contact element and the penalty function method are used to calculate the contact forces between the plates. An implicit variable-step algorithm is employed to numerically solve the deployment process of the system. Additionally, the effects of the driving speed of the frame, the spring stiffness and the elastic modulus on the dynamic characteristics of the system are explored, providing references for the design of foldable deployment mechanisms in engineering applications.

To investigate the interaction characteristics between the two rails on a curved floating slab track (FST) and the displacement variation of the slab under moving harmonic loads, a three-dimensional model of the curved FST is established based on the Euler-Bernoulli beam and Kirchhoff thin plate theories. The dynamic response solutions of the FST under moving harmonic loads are derived using the infinite periodic structure theory and the modal superposition method. The effects of various curve radii on the dynamic response of the FST are analyzed, and the interaction between the inner and outer rails is explored. Furthermore, the longitudinal and lateral displacement propagation ranges and characteristics of the slab are obtained under single-rail and double-rail moving loads, respectively. The results indicate that, within the parameter range of this study, variations in curvature significantly affect the dynamic responses of the rails and the floating slab when the curve radii are less than 400 m and 800 m, respectively. Vibration between the inner and outer rails propagates through the slab. Under single-rail excitation, the displacement attenuates by 65% within a 5 m longitudinal range of the slab, laterally, the displacement exhibits a linear trend, decreasing by an average of 54% per meter. Under double-rail excitation, the longitudinal displacement decreases by 64.6% within a 5 m range, while laterally, the inner and outer rails cause a displacement superposition effect at the center of the slab. The proposed 3D dynamic model effectively reveals the vibration transmission mechanisms of the curved track-slab system, providing a theoretical basis for the structural design and optimization of vibration mitigation measures for FSTs on curved metro lines.

Jointed structures are widely encountered in mechanical systems, where friction and contact nonlinearities at the interfaces result in pronounced amplitude-dependent dynamic responses. To address the complexity of such structures and the difficulty of nonlinear modal computation, a data-driven model order reduction method based on spectral submanifold (SSM) theory is proposed without requiring explicit governing equations. Low-dimensional SSMs are identified from numerical or experimental data to construct parametric reduced-order models. The method is validated using a representative multi-degree-of-freedom nonlinear system and further applied to an L-shaped lap-joint metal plate with bolted connections. The results show that the reduced-order models accurately reproduce nonlinear decay trajectories and predict dynamic responses with high fidelity, while nonlinear modal analysis reveals the energy-dependent evolution of damping and frequency. The proposed approach provides an efficient and physically interpretable framework for nonlinear modal analysis and dynamic modeling of complex jointed structures.

To address the issues of aerodynamic fatigue damage and the lack of a sufficient design basis for high-speed rail tunnel auxiliary facilities, a three-dimensional computational model of a train passing through a tunnel at 350 km/h was constructed using computational fluid dynamics (CFD) dynamic mesh and finite element (FE) techniques. This study systematically investigates the evolution patterns of the flow field, as well as the aerodynamic load characteristics of three typical auxiliary facilities: the catenary, the distribution box, and the cable. Furthermore, a wind-induced vibration response analysis and a fatigue assessment were conducted for the catenary. The results indicate that pressure drops are caused by compression waves and the passing of the train tail. Conversely, wind speed increases are induced by forward-propagating compression waves, backward-propagating expansion waves, and the passing of the train tail. Train-induced wind serves as the primary source of aerodynamic loads on the auxiliary facilities. The catenary and the distribution box are predominantly subjected to aerodynamic drag, with peak values reaching 60.20 N/m (at the tunnel exit) and 69.54 N (in the middle section on the near-train side), respectively. In contrast, the cable is mainly subjected to vertical force, with a peak value of 2.26 N/m (at the tunnel entrance on the near-train side). Dynamic analysis reveals that the most critically loaded catenary at the tunnel exit primarily undergoes longitudinal oscillation (fundamental frequency of 6.13 Hz) under aerodynamic forces. Its maximum equivalent alternating stress (35.66 MPa) remains below the material's fatigue limit, indicating that fatigue failure will not occur at the current operating speed. This study clarifies the aerodynamic load distribution patterns for different types of tunnel auxiliary facilities, providing a robust theoretical basis for their wind-resistant design, operational maintenance inspections, and future code revisions.

To develop a heat exchanger with enhanced overall thermal performance using elastic tube bundles, this study focuses on the Plane Elastic Tube Bundle (PETB) heat exchanger as the research subject. Based on four optimal matching schemes of inlet velocity (uin) and baffle height coefficient derived from open literature (Case Ⅰ: 0.1 m/s‒0.70; Case Ⅱ: 0.4 m/s‒0.82; Case Ⅲ: 0.7 m/s‒0.87; Case Ⅳ: 1.0 m/s‒0.73), eploying a two-way fluid-structure interaction calculation method, the shell-side heat transfer enhancement performance of the heat exchangers in four cases was investigated under different baffle arc angles (θ).Flow parameters and baffle structural parameters were optimized using a multi-objective genetic algorithm, and their intrinsic relationships with heat exchanger performance were analyzed. The results indicate that at low uin, the amplitude distribution of the tube bundles is uniform, while as uin increases, the amplitude generally increases. Across different θ values, the heat transfer coefficient of PETB 1 in all four cases is significantly higher than that of the other tube bundle rows. Excluding PETB 1, the uniformity of vibration-enhanced heat transfer coefficients among the remaining six tube bundles in Case Ⅱ is optimal. Within the range of θ variations, the heat transfer capacity of heat exchangers in Cases Ⅰ–Ⅳ under vibration conditions consistently exceeds that under non-vibration conditions, confirming the effectiveness of vibration in enhancing heat transfer. By comprehensively considering the vibration-enhanced heat transfer capacity and overall thermal performance, the optimal θ values for Cases I–IV within the range of θ (0°–20°) were determined as 0°, 20°, 5°, and 0°, respectively. An optimization model based on a BP neural network was established, and the optimal solution was identified using the linear programming technique for multidimensional analysis of preference method. A comparison of relevant parameters between the optimization model predictions and numerical simulations under the optimal scheme demonstrates the high reliability of the developed optimization model.

The combined operation of self-propelled modular transporters (SPMTs) and ship T-mooring systems has become a primary method for the roll-on/roll-off (Ro/Ro) transportation of large-scale industrial modules. The system is susceptible to single-line breakage and rope–anchor chain simultaneous failure under adverse metocean conditions, thereby compromising SPMT operational stability and vessel safety. To reveal the effects of these failure modes on vessel dynamic characteristics and berthing stability, a hydrodynamic model of the mooring system was developed using ANSYS AQWA software, and time-domain simulations were conducted to analyze vessel motion responses and mooring line tensions under single-line failure and rope–anchor chain simultaneous failure conditions. On this basis, a berthing stability evaluation framework was established to quantitatively assess system performance under different operating conditions. The results indicate that vessel motion responses exhibit a limited increase under single-line failure conditions compared with the intact condition; however, the variation strongly depends on the failure location and mooring line material type. Failure of stern ropes or anchor chains tends to significantly amplify vessel motions. The load originally borne by the failed mooring line is redistributed non-uniformly to adjacent mooring lines, with the tension increment decreasing as the spacing from the failed line increases. The system retains redundancy. In contrast, rope–anchor chain simultaneous failure significantly reduces the transverse and yaw restraining capacity, leading to highly concentrated tensions in the remaining mooring lines and vessel motions exceeding allowable limits. This study provides a theoretical basis and technical support for optimizing mooring configurations and mitigating line breakage risks at open berth.

As a critical core component in mechanical systems, the health status of rolling bearings is of paramount importance. While existing deep learning methods can extract features from high-dimensional data, they often struggle to simultaneously capture both the global health trends and local damaged details during the degradation process. This results in an inadequate characterization of the actual degradation state, leading to discrepancies between predicted remaining life and real-world conditions. To address these challenges, this paper proposes a multi-scale feature-driven cross-domain adaptive remaining useful life prediction method focused on degradation evolution consistency. Unlike existing approaches that only align static feature distributions, our method centers on the temporal evolution characteristics of bearing degradation. It integrates multi-scale convolutional features with attention mechanisms into a unified degradation-aware feature modeling framework, thereby simultaneously capturing local damage patterns and global degradation trends. Building upon this foundation, we introduce a joint distribution alignment strategy guided by lifetime labels. By mapping source domain true RUL labels and target domain pseudo labels onto a discrete degradation stage space, cross-domain alignment is no longer solely dependent on feature similarity but is constrained by degradation state consistency, thereby avoiding negative transfer issues. This mechanism achieves synergistical alignment between feature representations and degradation semantics, significantly enhancing the robustness and generalization capability of cross-condition RUL prediction. Finally, experimental results on the PHM2012 rolling bearing dataset validate the superior performance of the proposed method in cross-domain RUL prediction tasks.

As a typical passive control technique, the nonlinear energy sink introduces a nonlinear restoring force into the system to achieve targeted energy transfer, thereby effectively suppressing the vibration response of the primary structure. Based on the method for realizing customizable nonlinear restoring forces, a bistable track-type nonlinear energy sink is designed, and the dynamic model coupling the primary system and the nonlinear energy sink is established. The complex variable averaging method is employed to analyze the energy transfer characteristics of the conservative system under 1:1 internal resonance, as well as the initial conditions for achieving optimal targeted energy transfer. In addition, the influence of system parameters on the energy dissipation performance in the non-conservative system is investigated. The slow invariant manifold of the system under harmonic excitation is derived, and the regulation mechanism of system parameters on the forced vibration response is clarified. Furthermore, a horizontally excited metal plate experimental setup is constructed to validate the proposed device. The results show that the theoretical analysis agrees well with the experimental results, and the designed NES exhibits effective vibration suppression performance, providing a theoretical basis and experimental support for the engineering application of nonlinear energy sinks with customizable nonlinear restoring forces.

To explore the pressure pulsation and vibration characteristics of a gas-containing pipe, a T-type pipe system is considered and an experimental setup is established. Different conditions for gas accumulation volume, inlet pressure, and valve opening time are considered. The results indicate that the pressure pulsation is primarily caused by the water hammer effect triggered by sudden closure of the valve. This effect arises from the compression oscillations generated in a closed-end gas column when subjected to pressure. Furthermore, the shorter the opening time of the valve, the higher the pressure pulsation amplitude in the pipe; the larger the gas accumulation volume, the lower the pulsation frequency. Additionally, the amplitude of pressure pulses displays different variations with respect to the inlet pressure. As the inlet pressure is increased, the pulsation frequency is increased, resulting in intensified vibrations of the pipe, but the pulsation amplitude is diminished due to the damping effect.

In the robotic milling process, due to the dynamic changes of cutting forces and the weak rigidity of the robot body, the robotic milling system is highly prone to different types of chatter. To address the issue of accurately identifying robotic milling states, a recognition method can distinguish different types of chatter was proposed. Based on the time-frequency characteristics of vibration signals under different robotic milling states, four feature indicators were established: the Frequency Coefficient of Variation Ratio for the original signal, the Frequency Coefficient of Variation Ratio for the downconverted signal, the Periodic Frequency Energy Ratio, and the Root Mean Square. A feature matrix that can reflect the different milling states of the robot was constructed from the time domain and frequency domain. The feature matrix was input into machine learning algorithms for model training and testing, and the recognition accuracy of different algorithms was analyzed. The results showed that the state recognition model constructed by the Random Forest algorithm achieved the highest recognition accuracy, with an average recognition accuracy of 99.02% for the six robot milling states (no-load, stable cutting, severe regenerative chatter, severe low-frequency chatter, early regenerative chatter, and early low-frequency chatter), which is superior to existing chatter recognition methods.

To evaluate the protective capacity of the UHPC layer for RC bridge columns, a three-dimensional refined finite-element model for the contact-blast test and the axial-capacity test was established using the test conditions. The reliability of the model and algorithm was verified through comparisons of failure modes and axial force–displacement curves. Typical blast threats in belt-bomb, vest-bomb, and bag-bomb contact scenarios were selected using the FEMA classification of terrorist blasts. The blast resistance of RC columns and UHPC-protected columns was analyzed under these scenarios. The results indicate that under the contact explosion of a waist pack, the loss in axial bearing capacity of the column is relatively low. UHPC protective layers with thicknesses of 10 mm and 20 mm provide sufficient protective performance, with the axial bearing capacity loss percentages being 3.7% and 2.5%, respectively, and the damaged area reduced by 48.1% and 61.9%, respectively, thereby effectively lowering the repair difficulty of column damage caused by small-equivalent contact explosions. Under the contact explosion of a vest, the residual bearing capacity of the column is slightly below the design value. The 10 mm and 20 mm UHPC layers effectively reduce the damaged area of the column, with the axial bearing capacity reduced by 9.5% and 4.8%, respectively. Under the contact explosion of a suitcase, the unprotected column completely loses its bearing capacity, while columns with UHPC protective layers of 50 mm and 100 mm thickness experience reductions in axial bearing capacity of 15.3% and 4.6%, respectively.

As the strike capabilities of modern weapons continue to improve, shields face increasingly stringent requirements in terms of material performance and structural design. Although existing shields already possess a certain level of penetration resistance, shortcomings remain in areas such as material matching, interlayer coordination, and overall structural optimization. To address these issues, theoretical analysis, experiments, and numerical simulations are combined in this paper to investigate the material arrangement of a novel ceramic-aluminum alloy-armor steel composite shield. A response surface equation relating the ballistic limit velocity of this new composite shield to the thicknesses of the ceramic and aluminum alloy layers is established, and the influence of material thickness distribution on the penetration resistance of the shield structure is examined. The results indicate that the arrangement of the ceramic face layer, aluminum alloy intermediate layer, and armored steel back layer exhibits excellent penetration resistance; under high-speed projectile impact, the shield exhibits a failure mode characterized by complete fracture of the ceramic, mixed petal-shaped and plug-shaped failure of the aluminum alloy, and petal-shaped failure of the armored steel;When the total thickness remains constant, a higher proportion of material with a greater strength-to-density ratio results in a higher ballistic limit velocity and better anti-penetration performance of the structure.

This paper proposes a prefabricated combined frame structure of "wood on top and steel at the bottom". The upper part of this structure is a wooden structure and the lower part is a steel structure. To study the impact resistance performance of this structure, taking the mass of the impact object and the impact position as variables, a scale model was selected to conduct continuous impact tests under 10 working conditions. The strain time-history curve, displacement time-history curve and acceleration time-history curve of the measurement points were analyzed, revealing the deformation mode of the structure. Based on the comparative analysis of the test results, the influence laws of different variables on the impact resistance performance of steel-wood composite frames were summarized. The results show that the steel-wood composite frame structure exhibits good overall stability and anti-collapse capacity under impact loads. Among them, the lower steel structure effectively enhances the overall rigidity and strength of the structure, while the lightweight feature of the upper wood structure effectively reduces the energy transfer and damage accumulation during the impact process. This research achievement provides an important theoretical basis for the design and optimization of prefabricated composite structures.

To address the challenge of multi-domain feature extraction for impact response and reduce localization errors caused by the nonlinear attenuation of shock waves in airfoil structures, a Convolution-enhanced Image Transformer with Convolutional Block Attention Mobile Bottleneck (CeiT-CMB) network is proposed. This method employs discrete wavelet transform for noise separation and fundamental frequency elimination of impact signals, and utilizes short-time Fourier transform to establish a time-frequency spectrum image feature analysis model for the recovered effective signals. Building upon convolutional neural networks and Transformer, the approach integrates an attention mechanism to construct a network architecture that maps time-frequency spectrum image features to absolute coordinates for localization. To validate the effectiveness of the method, an impact localization experimental system was set up for an airfoil structure measuring 1200 mm × 200 mm × 1 mm. The results show that CeiT-CMB achieves a mean absolute error of 8.02 mm and a root mean square error of 9.02 mm. Compared to benchmark models such as CeiT, ResNet18, DenseNet121, and MobileNetV3, CeiT-CMB reduces the average relative error by 29.78%, 23.68%, 21.73%, and 29.36%, respectively. Additionally, compared to other attention-integrated methods, CeiT-CMB reduces the average relative error by 28.65%, 28.41%, and 16.61%, respectively. Thus, it can be concluded that the proposed method offers higher localization accuracy.

Pressure control during erosion is critical when abrasive water jet (AWJ) is applied to safe ammunition disassembly. This study investigates the pressure response of premixed AWJ impacting covered explosives, focusing on the effects of pump pressure and shell thickness on internal charge pressure. An analytical pressure model was established for premixed AWJ erosion of covered explosives comprising Q235 steel shells and Composition B charges. Coupled SPH-FEM simulations were conducted for pump pressures of 20–40 MPa and shell thicknesses of 5–10 mm, with impact experiments validating the predicted pressure trends. Results indicate that the erosion process comprises three distinct stages: dynamic water hammer loading, quasi-static stagnation loading, and unsteady penetration. Before shell penetration, explosive surface pressure is governed by competing stress wave attenuation and fluid confinement mechanisms—geometric attenuation dominates at low pump pressures, causing pressure to decrease with increasing shell thickness, whereas fluid confinement at high pump pressures yields a positive pressure–thickness correlation. After penetration, pressure transitions to a quasi-steady stagnation state expressible as Pc2=KαPs, where the correction coefficient Kα decreases linearly with shell thickness. Within the investigated parameter range, peak charge surface pressure remains below 20 MPa—far below the initiation threshold of Composition B—confirming process safety for insensitive main charges. These findings elucidate multi-condition pressure response mechanisms and provide a theoretical basis for safety assessment and parameter optimization in waste ammunition disassembly.

By comprehensively utilizing the separated Hopkinson pressure bar (SHPB) device and independent intelligent box-type resistance furnace, SHPB impact compression tests and sieving tests were conducted on sandstone under different impact air pressures (0.1 MPa~0.6 MPa) at room temperature (25 ℃) and different high temperatures (200 ℃~800 ℃). The dynamic mechanical behavior, fracture characteristics, and energy evolution of sandstone under the coupled effects of high temperature and strain rate were systematically analyzed. The results indicate that under the combined action of high temperature and impact loading, the dynamic stress-strain curve of sandstone shows a trend of strength degradation and ductility enhancement. Moreover, the temperature damage effect becomes more pronounced under high strain rates. The influence of temperature on the dynamic mechanical properties of sandstone can be divided into strengthening stage and deterioration stage. 200 °C identified as the key temperature for performance degradation. The absolute value of absorbed energy increases linearly with the increase of impact air pressure. Both high temperature and high strain rate exacerbate the fragmentation of sandstone. With the increase of temperature, the failure mode transitions from splitting to crushing. When the temperature exceeds 600 °C, the influence of strain rate on fragmentation size decreases, and thermal damage becomes the dominant factor in the failure mode. The findings of this study can provide a theoretical basis for the stability design of deep underground engineering structures. 

Due to factors such as manufacturing errors and temperature changes, the suspension parameters of high-speed trains have significant random uncertainties, and the influence of suspension parameters on dynamic performance is contradictory. High-speed trains need to obtain excellent and balanced dynamic performance under the influence of random changes in suspension parameters. Therefore, this paper proposes a game optimization method for the dynamic performance of high-speed train bogies considering the random uncertainty of suspension parameters. The distribution characteristics of suspension parameters are analyzed, and an adaptive sparse expansion chaotic polynomial method is proposed to quantify the uncertainty of dynamic performance. The mapping relationship between dynamic performance robustness optimization and game-driven decision-making is proposed, and the game optimization model is constructed. The robustness optimization of dynamic performance of high-speed train bogie is carried out by combining the uncertainty quantification method of adaptive sparse chaotic polynomial and the game optimization model. The results show that the dynamic performance index presents a normal distribution under the influence of random suspension parameters. Considering the random variation of suspension parameters, the distribution mean and standard deviation of each dynamic performance index are reduced, and the obtained matching parameters are not sensitive to random fluctuations, which improves the dynamic performance robustness and line adaptability of high-speed train bogies. The game optimization method can achieve the optimization effect and reduce the subjectivity of human design. This paper provides a new method for dynamic performance optimization of high-speed train bogie.

Curve squeal is a highly tonal noise generated when a train passes through a sharp curve, It is caused by the self-excited vibration of wheels. In recent years, a method of controlling curve squeal by injecting dither force has been proposed. This paper establishes a subway curve squeal prediction model, which includes a finite element track model, a finite element wheel model, a wheel-rail contact model (ZCON), and a wheel sound radiation model. The model is validated through field tests. Using this model, the mechanism and suppression effect of how the dither force control curve squeal are further analyzed. The results show that the dither force is equivalent to increasing the critical creepage, thereby breaking the transverse and vertical cyclic mechanism of self-excited vibration. Dither force can reduce the energy input from the wheel-rail force to the wheel, thus lowering the vibration intensity, and can be categorized into two types depending on the degree. Dither force is more suitable to be applied to the rail, with a more significant effect on reducing wheel vibration. Under the parameter combination in this paper, a square wave signal with a frequency of 200Hz and an amplitude of 1500N achieves the best effect. Laboratory tests demonstrate that using piezoelectric actuators to provide dither force is a feasible approach for squeal suppression. 

Squeal is a vibration instability phenomenon in aircraft braking systems that significantly impacts structural safety and ride comfort. As the primary configuration for current large aircraft, the squeal behavior in dual-wheel strut landing gear braking systems remains insufficiently understood. To reveal the squeal characteristics of such systems, a finite element model of the dynamic interaction between the brake structure and brake disc was established, considering the equivalent stiffness of the piston under combined hydraulic and thrust spring actions. A preloaded nonlinear statics approach was used to describe slip friction phenomena. Based on the complex eigenvalue method, the squeal frequency, mode shape characteristics, system response, and influencing parameters were investigated. The squeal frequencies and mode shapes identified through finite element simulations showed good agreement with ground inertia dynamometer test results. The squeal mode manifested as the combined torsional and whirling motion of the static disc–torque tube–piston housing assembly around the test wheel axle, accompanied by oscillation of the torque output pin. This mode induced oscillations in brake pressure and braking torque at the squeal frequency. Using bifurcation diagrams, the finite element model illustrated the coupling process between adjacent order modes with variations in brake pressure and friction coefficient, revealing the conditions for squeal instability. By constructing a high-fidelity finite element model, this work elucidates the squeal characteristics of dual-wheel strut landing gear braking systems, providing a theoretical basis for improving aircraft comfort and reliability.

To reveal the influence mechanism of lead crown relief on the dynamic behavior of the gear-rotor-bearing system, this paper establishes a coupled dynamic model that comprehensively considers multiple excitation sources such as tooth profile modification, time-varying backlash, rotor misalignment, and nonlinear bearing support forces. Based on the slice coupling method and Hertz contact theory, the time-varying meshing stiffness model incorporating modification error and the nonlinear restoring force expression of the bearing are derived, and the dimensionless equations of motion for the system are constructed. The Runge-Kutta method is employed to solve the equations. The effects of parameters such as excitation frequency, misalignment angle, and input power on the dynamic response are analyzed. By combining bifurcation, phase diagram, Poincaré, and spectrum analysis, the nonlinear evolution of the system from periodic motion through period-doubling bifurcation to chaos is revealed. The results indicate that lead crown relief effectively suppresses meshing stiffness fluctuation, improves transmission stability, and the system exhibits typical period-doubling bifurcation and chaotic characteristics within specific frequency ranges.

In conventional robust controller design for active magnetic bearings, the weighting-function parameters are typically tuned through repeated manual adjustment, leading to a cumbersome design procedure and making it difficult to explicitly coordinate the trade-off between performance and robustness at the design stage. To address this issue, this paper proposes an optimization-based robust controller design method that aims to maximize the disk margin while minimizing time-domain performance indices, thereby formulating the controller tuning task as a multi-objective optimization problem. First, the advantages of introducing the disk margin as a robustness metric are analyzed, and a nominal plant model is established based on system identification results. With a preselected weighting-function structure for robust control, an optimization variable set consisting of seven weighting-function parameters is constructed, and the resulting multi-objective optimization problem is solved under relevant constraints. By further analyzing the obtained Pareto front solution set, the conflict between system performance and robustness is intuitively characterized. Based on this analysis, a desired parameter set is selected to complete the robust controller synthesis, and experimental validation is conducted on an active magnetic bearing flexible-rotor test rig. The experimental results show that the robust controller designed via the proposed optimization method enables stable levitation of the rotor at 25 Hz, corresponding to the first bending mode frequency, thereby demonstrating the feasibility of the proposed design approach. 

Under time-varying speeds, existing methods face challenges in accurate ridge extraction and fault identification. This paper introduces a novel approach integrating Canny edge detection and a modified cost function for iterative feature extraction. First, Canny algorithm identifies energy boundaries in time-frequency maps. Edge length and average energy enable adaptive search area division, overcoming fixed bandwidth limitations. Reference ridges are then extracted within these areas. The cost function's penalty factor adjusts dynamically based on mean frequency jumps, enhancing smoothness and noise resistance. An iterative process of reference-feature ridge extraction with search area shrinkage enables continuous multi-component ridge convergence. Validation using simulated signals and University of Ottawa dataset demonstrates superior performance over MTFCE and AARE methods. The proposed technique shows improved accuracy, robustness, and diagnostic reliability in ridge extraction.

To accurately identify the weak damage of bearings in complex interference environments, a fault diagnosis method integrating improved optimal variational mode extraction (OVME) and 1.5 dimension spectrum is proposed. Firstly, a sparsity evaluation index without prior knowledge - the median square envelope Gini index (MSEGI)- is constructed, and on this basis, the objective function of the meta-heuristic optimization algorithm is established. Secondly, the characteristics of OVME are analyzed through different meta-heuristic optimization algorithms, indicating that the key to the success of OVME lies in the objective function. Then, in order to reduce the interference caused by the residual random noise in the expected mode, the 1.5 dimension spectrum analysis technique is introduced in the fault feature frequency identification stage. Finally, through the analysis of two sets of experimental signals, the effectiveness of the proposed method is verified. It is compared with methods such as adaptive variational mode extraction (VME) and variational mode decomposition (VMD), and the advantages of the proposed method are demonstrated.