Search Results (124)

Shape memory alloy dampers (SMADs) are widely applied in structural vibration control due to their excellent superelastic properties. However, there has been no research on the random wind-induced vibration control of transmission tower-line (TTL) systems with added SMADs. To address this gap, this paper proposes an analytical framework for the wind-induced vibration control of TTL systems with SMADs under random wind loads. An analytical model for the coupled TTL system is developed. The constitutive relationship of the SMAD is derived using the statistical linearization method, and a vibration control approach for the TTL-coupled system with SMADs is proposed. The vibration response of the TTL–SMAD system under random wind loads is derived, and an extreme response analysis framework based on the first exceedance failure criterion is established. The results show that the optimal installation scheme for the SMAD achieves a vibration reduction of more than 30%. When the damper’s stiffness coefficient is approximately 1, the SMAD effectively controls the vibrations. Moreover, a service temperature of 0 °C is found to be the optimal control temperature for the SMAD. These findings provide important references for the application of SMADs in the vibration control of TTL systems. Full article

With the development of urban infrastructure construction, while pedestrian bridges meet traffic functions the issue of their comfort has become a core consideration in structural design. This is because the long-span lightweight structures, with their large flexibility and low fundamental frequencies, are also vulnerable to human-induced vibrations. Pedestrian load modellings include the deterministic time-domain model, which is widely adopted in codes due to its simplicity, the random model that takes into account individual variability, and the frequency-domain model. The deterministic time-domain model has abundant parameter determination results and has become relatively mature, while the latter two, although more rigorous, have relatively lagging development. Numerous studies have shown that acceleration limits are the main indicators for comfort assessment. Vertical vibrations are controlled by amplitude constraints, while for the lateral vibrations the “lateral lock-in” that can cause dynamic instability needs to be evaluated with particular emphasis. When comfort exceeds an acceptable degree, a prevalent countermeasure is to attach a Tuned Mass Damper (TMD) or Multiple Tuned Mass Damper (MTMD) system to the structure—the latter demonstrates stronger robustness when dealing with random pedestrian loads. Full article

The exhaust duct of aero-engine exhibits complex vibration response characteristics under the influence of temperature fields and vibration loads. Taking the non-axisymmetric exhaust duct of turboshaft engine as the object of study, a finite element model of the exhaust duct was established using three-dimensional finite element analysis methods to analyze the thermal modal and random vibration response characteristics under axial loading for large thin-walled non-axisymmetric exhaust ducts. The simulation analysis method was validated through thermal vibration experiments on the scaled model. In a thermal environment, the shape of the power spectral density curves for displacement and stress of the exhaust duct remains largely unchanged in the low-frequency range; however, the response frequencies exhibit a significant forward shift. When subjected to Y-axial loading, the amplitude of the X- and Z-direction displacement response at 1st order (12.96 Hz) and the stress response at 6th order (30.92 Hz) significantly increase. Random vibration loads excite multiple modes of the exhaust duct, with lower-order modes being more easily stimulated. When subjected to X- and Z-axial loading, 1st order (12.96 Hz) has the greatest impact on the X- and Z-direction displacement responses, while 2nd order (16.93 Hz) and 13th order (82.79 Hz) frequencies have the greatest impact on the displacement response in the Y-direction and equivalent stress response. When subjected to Y-axial loading, the 5th order (22.35 Hz) and 12th order (81.69 Hz) modes have the most significant effects on the displacement responses in the X, Y, and Z directions and equivalent stress responses. Attention to these orders is essential during the design process, along with implementing certain stiffness reinforcement measures to reduce response amplitudes. Full article

As engines trend toward miniaturization, lightweight design, and higher power density, noise issues have become increasingly prominent, necessitating precise radiated noise prediction for effective noise control. This study develops a machine learning model based on surface vibration test data, which enhances the efficiency of engine noise prediction and has the potential to serve as an alternative to traditional high-cost engine noise test methods. Experiments were conducted on a four-cylinder, four-stroke diesel engine, collecting surface vibration and radiated noise data under full-load conditions (1600–3000 r/min). Five prediction models were developed using support vector regression (SVR, including linear, polynomial, and radial basis function kernels), random forest regression, and multilayer perceptron, suitable for non-anechoic environments. The models were trained on time-domain and frequency-domain vibration data, with performance evaluated using the maximum absolute error, mean absolute error, and median absolute error. The results show that polynomial kernel SVR performs best in time domain modelling, with an average relative error of 0.10 and a prediction accuracy of up to 90%, which is 16% higher than that of MLP; the model does not require Fourier transform and principal component analysis, and the computational overhead is low, but it needs to collect data from multiple measurement points. The linear kernel SVR works best in frequency domain modelling, with an average relative error of 0.18 and a prediction accuracy of about 82%, which is suitable for single-point measurement scenarios with moderate accuracy requirements. Analysis of measurement points indicates optimal performance using data from the engine top between cylinders 3 and 4. This approach reduces reliance on costly anechoic facilities, providing practical value for noise control and design optimization. Full article

This study proposes an integrated framework that combines nonlinear stochastic vibration analysis with reliability assessment to address the safety issues of cable systems under damage conditions. First of all, a mathematical model of the damaged cable is established by introducing damage parameters, and its static configuration is determined. Using the Pearl River Huangpu Bridge as a case study, the accuracy of the analytical solution for the cable’s sag displacement is validated through the finite difference method (FDM). Furthermore, a quantitative relationship between the damage parameters and structural response under stochastic excitation is developed, and the nonlinear stochastic dynamic equations governing the in-plane and out-of-plane motions of the damaged cable are derived. Subsequently, a Gaussian Radial Basis Function Neural Network (GRBFNN) method is employed to solve for the steady-state probability density function of the system response, enabling a detailed analysis of how various damage parameters affect structural behavior. Finally, the First-Order and Second-Order Reliability Method (FORM/SORM) are used to compute the reliability index and failure probability, which are further validated using Monte Carlo simulation (MCS). Results show that the severity parameter η shows the highest sensitivity in influencing the failure probability among the damage parameters. For the system of the Pearl River Huangpu bridge, an increase in the damage extent δ from 0.1 to 0.4 can reduce the reliability-based service life of by approximately 40% under fixed values of the damage severity and location, and failure risk is highest when the damage is located at the midspan of the cable. This study provides a theoretical framework from the point of stochastic vibration for evaluating the response and associated reliability of mechanical systems; the results can be applied in practice with guidance for the engineering design and avoid potential damages of suspended cables. Full article

Forest trees have emerged as a promising passive solution for mitigating low-frequency ground vibrations generated by railway operations, offering ecological and cost-effective advantages. This study proposes a three-dimensional semi-analytical method developed for evaluating the dynamic responses of the coupled track–ground–tree system. The thin-layer method is employed to derive an explicit Green’s function corresponding to a har-monic point load acting on a layered half-space, which is subsequently applied to couple the foundation with the track system. The forest trees are modeled as surface oscillators coupled on the ground surface to evaluate the characteristics of multiple scattered wavefields. The vibration attenuation capacity of forest trees in mitigating railway-induced ground vibrations is systematically investigated using the proposed method. In the direction perpendicular to the track on the ground surface, a graded array of forest trees with varying heights is capable of forming a broad mitigation frequency band below 80 Hz. Due to the interaction of wave fields excited by harmonic point loads at multiple locations, the attenuation performance of the tree system varies significantly across different positions on the surface. The influence of variability in tree height, radius, and density on system performance is subsequently examined using a Monte Carlo simulation. Despite the inherent randomness in tree characteristics, the forest still demonstrates notable attenuation effectiveness at frequencies below 80 Hz. Among the considered parameters, variations in tree height exert the most pronounced effect on the uncertainty of attenuation performance, followed sequentially by variations in density and radius. Full article

This study proposes a vibration-based approach for detecting and quantifying sub-slab corner voids in airport cement concrete pavement. Scaled down slab models were constructed and subjected to controlled moving load simulations. Acceleration signals were collected and analyzed to extract time–frequency domain features, including power spectral density (PSD), skewness, and frequency center. A finite element model incorporating contact and nonlinear constitutive relationships was established to simulate structural response under different void conditions. Based on the simulated dataset, a random forest (RF) model was developed to estimate void size using selected spectral energy indicators and geometric parameters. The results revealed that the RF model achieved strong predictive performance, with a high correlation between key features and void characteristics. This work demonstrates the feasibility of integrating simulation analysis, signal feature extraction, and machine learning to support intelligent diagnostics of concrete pavement health. Full article

In this study, the fatigue behavior in high-speed train bogie frames and mounted traction motors was investigated through dynamic stress measurements and vibration analysis. A spectrum synthesis method was developed to integrate multipoint random vibrations from the bogie frame into a unified excitation spectrum for motor fatigue assessment. The results demonstrate that fatigue damage in the bogie frame progresses linearly with increasing speed, with critical stress concentrations being identified at the motor base weld seams (41.4 MPa equivalent stress at 400 km/h). Traction motor vibration spectra were found to deviate substantially from IEC 61373 standards, leading to higher fatigue damage that follows an exponential growth pattern relative to speed increases. The proposed methodology provides direct experimental validation of component-specific fatigue mechanisms under operational loading conditions. Full article

Ensuring the safety of large spherical water storage tanks in seismic environments is critical. Therefore, this study proposed a vibration control device applicable to general spherical water tanks. By utilizing the upper interior space of a spherical tank, a novel tuned mass damper (TMD) system composed of a mass block and four elastic springs was proposed. To enable practical implementation, the vibration control mechanism and tuning principle of the proposed TMD were examined. Subsequently, an experimental setup, including the spherical water tank and the TMD, was developed. Subsequently, shaking experiments were conducted using two types of spherical tanks with different leg stiffness values under various seismic waves and excitation directions. Shaking tests using actual El Centro NS and Taft NW earthquake waves demonstrated vibration reduction effects of 34.87% and 43.38%, respectively. Additional shaking experiments were conducted under challenging conditions, where the natural frequency of the spherical tank was adjusted to align closely with the dominant frequency of the earthquake waves, yielding vibration reduction effects of 18.74% and 22.42%, respectively. To investigate the influence of the excitation direction on the vibration control performance, shaking tests were conducted at 15-degree intervals. These experiments confirmed that an average vibration reduction of more than 15% was achieved, thereby verifying the validity and practicality of the proposed TMD vibration control system for spherical water tanks. Full article

An innovative method is proposed to analyze the coupled vibration between random traffic and large-span bridges under the combined action of wind loads. The dynamic behavior of bridges subjected to these multifactorial influences is investigated through a comprehensive bridge dynamics model. Specifically, a refined full-bridge finite element model is developed to simulate the traffic–bridge coupled vibration, with wind forces applied as external dynamic loads. The effects of wind speed and vehicle speed on the coupled system are systematically evaluated using the finite element software ABAQUS 2023. To ensure computational accuracy and efficiency, the large-span nonlinear dynamic solution method is employed, integrating the Newmark-β time integration method with the Newton–Raphson iterative technique. The proposed method is validated through experimental measurements, demonstrating its effectiveness in capturing the synergistic impacts of wind and traffic on bridge dynamics. By incorporating the stochastic nature of traffic flow and combined wind forces, this approach provides a detailed analysis of bridge responses under complex loading conditions. The study establishes a theoretical foundation and practical reference for the safety assessment of large-span bridges. Full article

Duplex ball bearings are common components in space satellite mechanisms, and their behaviour impacts the overall performance and reliability of these systems. During rocket launches, these bearings suffer high vibrational loads, making their dynamic response essential for their survival. To predict the dynamic behaviour under vibration, simulations and experimental tests are performed. However, published models for space applications fail to capture the variations observed in test responses. This study presents a multi-degree-of-freedom nonlinear multibody model of a hard-preloaded duplex space ball bearing, particularized for this work to the case in which the outer ring is attached to a shaker and the inner ring to a test dummy mass. The model incorporates the Hunt and Crossley contact damping formulation and employs quaternions to accurately represent rotational dynamics. The simulated model response is validated against previously published axial test data, and its response under step, sine, and random excitations is analysed both in the case of radial and axial excitation. The results reveal key insights into frequency evolution, stress distribution, gapping phenomena, and response amplification, providing a deeper understanding of the dynamic performance of space-grade ball bearings. Full article

High-power laser diodes (HPLDs) are increasingly used in space applications, yet solder layer (SL) reliability critically limits their performance and lifespan. This study employs finite element analysis to evaluate SL failure mechanisms in microchannel-cooled HPLDs with two packaging configurations under thermal cycling and vibration. Based on the Anand constitutive model, contour plot analysis revealed that the critical stress–strain regions in both SLs were located at their edges. The stress–strain values along the X-axis of the SLs exceeded those in other axial directions, and SL failure would preferentially initiate from the edges along the cavity length direction. During random vibration analysis with excitation applied along the Z-axis, the equivalent stresses in both SLs exceeded X-/Y-axis levels. However, these values remained far below their yield strengths, indicating that only elastic strain and high-cycle fatigue occurred in the SLs. The calculated thermal fatigue lives of the two SLs were 2851 cycles and 5730 cycles, respectively. Their random vibration fatigue lives were determined as 5.75 × 10⁷ h and 8.31 × 10⁷ h. Using damage superposition under combined thermal-vibration loading, the total fatigue lives were predicted as 14,821 h and 29,786 h, respectively, with thermal cycling-induced damage dominating the failure mechanism. Full article

Fatigue failure, generated by local multi-axial random state stress, frequently occurs in many engineering fields. Therefore, it is customary to perform experimental vibration tests for a structural durability assessment. Over the years, a number of testing methodologies, which differ in terms of the testing machines, specimen geometry, and type of excitation, have been proposed. The aim of this paper is to describe a new testing procedure for random multi-axial fatigue testing. In particular, the paper presents the experimental set-up, the testing procedure, and the data analysis procedure to obtain the multi-axial random fatigue life estimation. The originality of the proposed methodology consists in the experimental set-up, which allows performing multi-axial fatigue tests with different normal-to-shear stress ratios, by choosing the proper frequency range, using a single-axis exciter. The system is composed of a special designed specimen, clamped on a uni-axial shaker. On the specimen tip, a T-shaped mass is placed, which generates a tunable multi-axial stress state. Furthermore, by means of a finite element model, the system dynamic response and the stress on the notched specimen section are estimated. The model is validated through a harmonic acceleration base test. The experimental tests validate the numerical simulations and confirm the presence of bending–torsion coupled loading. Full article

Fuel cells, propulsion systems, and reaction control systems (RCSs) are just a few of the space applications that depend on pressure vessels (PVs) to safely hold high-pressure fluids while enduring extreme environmental conditions both during launch and in orbit. Under these challenging circumstances, PVs must be lightweight while retaining structural integrity in order to increase the efficiency and lower the launch costs. PVs have significant challenges in space conditions, such as extreme vibrations during launch, the complete vacuum of space, and sudden temperature changes based on their location within the satellite and orbit types. Determining the operational temperature limits and endurance of PVs in space applications requires assessing the combined effects of these factors. As the main propellant for satellites and rockets, hydrogen has great promise for use in future space missions. This study aimed to assess the structural integrity and determine the thermal operating limits of different types of hydrogen pressure vessels using finite element analysis (FEA) with Ansys 2019 R3 Workbench. The impact of extreme space conditions on the performances of various kinds of hydrogen pressure vessels was analyzed numerically in this work. This study determined the safe operating temperature ranges for Type 4, Type 3, and Type 1 PVs at an operating hydrogen storage pressure of 35 MPa in an absolute vacuum. Additionally, the dynamic performance was assessed through modal and random vibration analyses. Various aspects of Ansys Workbench were explored, including the influence of the mesh element size, composite modeling methods, and their combined impact on the result accuracy. In terms of the survival temperature limits, the Type 4 PVs, which consisted of a Nylon 6 liner and a carbon fiber-reinforced epoxy (CFRE) prepreg composite shell, offered the optimal balance between the weight (56.2 kg) and a relatively narrow operating temperature range of 10–100 °C. The Type 3 PVs, which featured an Aluminum 6061-T6 liner, provided a broader operational temperature range of 0–145 °C but at a higher weight of 63.7 kg. Meanwhile, the Type 1 PVs demonstrated a superior cryogenic performance, with an operating range of −55–54 °C, though they were nearly twice as heavy as the Type 4 PVs, with a weight of 106 kg. The absolute vacuum environment had a negligible effect on the mechanical performance of all the PVs. Additionally, all the analyzed PV types maintained structural integrity and safety under launch-induced vibration loads. This study provided critical insights for selecting the most suitable pressure vessel type for space applications by considering operational temperature constraints and weight limitations, thereby ensuring an optimal mechanical–thermal performance and structural efficiency. Full article

Stochastic vibration control of uncertain structures under random loading is an important problem and its minimax optimal control strategy remains to be developed. In this paper, a stochastic optimal control strategy for uncertain structural systems under random excitations is proposed, based on the minimax stochastic dynamical programming principle and the Bayes optimal estimation method with the combination of stochastic dynamics and Bayes inference. The general description of the stochastic optimal control problem is presented including optimal parameter estimation and optimal state control. For the estimation, the posterior probability density conditional on observation states is expressed using the likelihood function conditional on system parameters according to Bayes’ theorem. The likelihood is replaced by the geometrically averaged likelihood, and the posterior is converted into its logarithmic expression to avoid numerical singularity. The expressions of state statistics are derived based on stochastic dynamics. The statistics are further transformed into those conditional on observation states based on optimal state estimation. Then, the obtained posterior will be more reliable and accurate, and the optimal estimation will greatly reduce uncertain parameter domains. For the control, the minimax strategy is designed by minimizing the performance index for the worst-parameter system, which is obtained by maximizing the performance index based on game theory. The dynamical programming equation for the uncertain system is derived according to the minimax stochastic dynamical programming principle. The worst parameters are determined by the maximization of the equation, and the optimal control is determined by the minimization of the resulting equation. The minimax optimal control by combining the Bayes optimal estimation and minimax stochastic dynamical programming will be more effective and robust. Finally, numerical results for a five-story frame structure under random excitations show the control effectiveness of the proposed strategy. Full article