International Journal of Structural Stability and Dynamics

To evaluate the crosswind stability (overturning and sideslip) of vehicles driving on the bridge, obtaining critical wind speed is essential. The traditional method is based on the aerodynamic forces of moving vehicles on the bridge and the analysis of force equilibrations. However, various shapes of the bridge make the flow field around the vehicle on the bridge very complicated to obtain. In this paper, a simplified method is introduced to calculate the critical wind speeds of moving vehicles on bridges based on the influence of coefficients of the wind environment on the bridge and the aerodynamic forces of moving vehicles on open fields. The aerodynamic forces of moving vehicles are simulated with dynamic mesh techniques. Besides, the characteristics of the wind environment on the bridge deck are studied to evaluate the driving safety and determine the influence coefficient. To further demonstrate the reliability, critical wind speed in different road conditions of the proposed simplified method shows very good agreement with the traditional method.

Previously it was shown that nonlocal piezoelectric differential models will lead to inconsistent bending response for Euler–Bernoulli beams under different loadings and boundary conditions. In this paper, the general strain- and stress-driven two-phase local/nonlocal integral piezoelectric models are applied to analyze the elastic buckling and free vibration of functionally graded piezoelectric (FGP) Euler–Bernoulli beams under different boundary conditions. The differential governing equations and standard boundary conditions are derived by the Hamilton’s principle. The relations between the general strain and general nonlocal stresses are expressed as integral equations, which are further transformed equivalently to differential forms with constitutive boundary conditions. Several nominal variables are introduced to simplify the differential governing and constitutive equations, as well as the standard and constitutive boundary conditions. The general differential quadrature method is applied to obtain the numerical results of buckling loads and vibration frequencies of the FGP Euler–Bernoulli beam. Numerical results show that general strain- and stress-driven two-phase local/nonlocal integral piezoelectric models will lead to consistently softening and toughening size-dependent responses, respectively.

In recent years, the use of partially concrete-filled steel tubular (PCFST) columns has been considered due to their cost-effectiveness and reduction of structural weight in bridge piers and building columns. One of the critical discussions about these columns is their impact resistance. In this article, the dynamic response of hollow and PCFST columns with elliptical cross-section under simultaneous loading of static axial compressive load and lateral impact load is presented using finite element modeling in ABAQUS software (FEA). To ensure the accuracy of the numerical modeling, the analysis results are compared with the results of previous works. The effects of different parameters such as impact velocity, the height of the impact location, the impact direction, the impact block mass, the size and shape of the impact block are investigated in this paper. The results of the numerical analysis showed that the partially filled specimens had better performance than the hollow specimens. The changes in impact direction and impact block mass parameters have a significant effect on the failure of the columns, especially when they are under high impact velocity. Changing the impact velocity significantly affects the impact resistance of specimens. However, the size and shape of the impact block did not have a significant effect on the displacement of the column against the impact loading.

This paper investigates the possibility for implementing machine learning-aided prediction in analyzing the buckling phenomena of ballasted railway tracks induced by extreme temperature. In this study, artificial neural networks (ANNs) have been developed to identify the relationship between various ballasted track conditions and outputs, namely safe temperature and buckling temperature. The variables included in the objective function of the optimization problems are the lateral resistance of ballasted track provided by ballast-sleeper interaction, torsional resistance provided by fastening systems, and misalignment of the track. Due to its complexity in parameter combinations, the objective of this study is to create predictive models with the aim of minimizing the usage of scarce resources. Thus, this paper is the first to develop a novel machine learning-aided prediction of railway track buckling due to extreme temperature. Comprehensively, all 353 datasets of the safe and buckling temperatures derived from previous finite element (FE) simulation results have been collected and trained. Note that the mean squared error (MSE) and the coefficient of determination ($R^2)$ are considered to quantify the performance of the ANN architectures. The optimal ANN architecture with a very high rate of accuracy has been determined and highlighted. Thus, the suggested neural network model can be applied conveniently to help estimate safe and buckling temperatures of the complex track models in order to improve track conditions and thus prevent track buckling in summer.

This paper analyzes the dynamic stability of an isotropic viscoelastic Euler–Bernoulli nano-beam using piezoelectric materials. For this purpose, the size-dependent theory was used in the framework of the modified couple stress theory (MCST) for piezoelectric materials. In order to capture the geometrical nonlinearity, the von Karman strain displacement relation was applied. Hamilton’s principle was also employed to obtain the governing equations. Furthermore, the Galerkin method was used in order to convert the governing partial differential equations (PDEs) to a nonlinear second-order ordinary differential one. Dynamic stability analysis was performed and the effects of such parameters as viscoelastic coefficients, size effect, and piezoelectric coefficient were investigated. The results showed that in this system, saddle points, central points, Hopf bifurcation points, and fork bifurcation points could be created, and the phase portraits connecting these equilibrium points exhibit periodic orbits, heteroclinic orbits, and homoclinic orbits.

Modal parameters, including natural frequencies, damping ratios, and mode shapes, are vital for evaluating the in-service condition of long-span bridges subjected to performance degradation or damages. Operational modal identification techniques requiring only ambient vibration responses are usually utilized to identify the modal parameters of in-service bridges. Due to the measurement incompleteness and modeling errors, uncertainties would inevitably be involved in the identification. The changing operational loads of long-span bridges, e.g. vehicles and winds, could also increase uncertainties. These uncertainty factors could decrease the precision of the operational modal identification and undermine the reliability of structural health monitoring (SHM) for long-span bridges. This study introduces an improved Bayesian modal identification approach using the scaled Fast Fourier Transform data for uncertainty quantification. The proposed method integrates the genetic optimization with the posterior probability density function of modal parameters to ensure the accuracy and robustness of the iteration process. Additionally, an asymptotic estimate interval with the assumption of a high signal-to-noise ratio is defined to improve the computational efficiency. The acceleration responses from a numerical example and a full-scale long-span bridge are adopted to validate the performance of the proposed method. Results show that the improved Bayesian approach can accurately identify the modal parameters and efficiently quantify the uncertainties. The method enhances the reliability of modal tracking for SHM of operational long-span bridges.

In recent years, the continuous innovation in terms of using new materials and structures for pedestrian bridges has led to a significant reduction in the natural frequency of such bridges. Thus, the human-induced vibration comfort of bridges has been increasingly affected. Therefore, this paper introduces the Stevens annoyance rate model (ARM) and proposes a design and evaluation method for human-induced vibration comfort of pedestrian bridges based on this model. In order to verify the effectiveness of the proposed method, a practical pedestrian bridge is used as an example to perform dynamic analysis, comfort evaluation, and vibration reduction design. The results show that the pedestrian bridge comfort evaluation method based on the Stevens-ARM can accurately quantify the vibration comfort of the human body under uncertainties. For comfort control, the new comfort design method and a genetic algorithm (GA) can arrange multiple tuned mass dampers (MTMDs) more reasonably, which can prevent the annoyance rate (AR) and comfort rate under the two-way coupled vibration from exceeding the limit. Moreover, data obtained from 14 pedestrian bridges in China were analyzed to verify the generality and reliability of the findings.

Offshore wind turbines (OWTs) are complex systems that may experience excessive vibrations due to winds, waves, rotor torque, or seismic loads during the operation. Tuned mass dampers (TMDs) have been a widely used vibration passive control device in structures, including wind turbines. The TMD works as a damper that transfers the kinetic energy from the main structure to a secondary mass usually attached to the hub. The spectral element method (SEM) is suitable for analyzing dynamic structural problemss with accuracy and low computational cost. This paper presents a monopile wind turbine fitted with a pendulum-TMD (PTMD) modeled by spectral elements. An optimum pendulum design is performed through the genetic algorithm technique. The wind turbine selected is a National Renewable Energy Lab (NREL) monopile 5MW baseline wind turbine fitted with a PTMD, subjected to winds and waves simulated as random spectra in the analysis. Numerical results show the efficiency of the proposed spectral model and the optimum PTMD design for the OWT under random excitation.

Concrete-filled steel tubular (CFST) column has been widely used in engineering practice. In the process of assembling two columns to form a slender member, assembling errors (AE) are inevitably produced at the section of connection. When the AE are too large, the global buckling resistance of slender column would be significantly affected. Therefore, it is necessary to investigate the influence of AE on the stability performance of slender CFST columns. In this study, an axial compressive test involving three CFST columns with AE (AE-CFST columns) was conducted. A refined finite element (FE) model is established for further parametric analysis. Based on a simplified analytical model by analyzing the isolated steel connecting plate, a theoretical formula is proposed for predicting the critical thickness $t_{p0}$ of the connecting plate. When the thickness $t_p$ of the connecting plate meets its requirement, the failure at the section of connection caused by AE could be effectively prevented. Stability design curves considering the influence of AE ratio (the ratio between assembling error and sectional depth of column) are proposed based on numerous FE examples. It is found that the proposed design curves are reliable for the design of AE-CFST columns with different AE ratios.

A fluid drive in-pipe inspection robot is an essential device for the inner inspection of long-distance oil and gas pipelines. Obstacles such as dents and welds can significantly affect the operation stability of the robot as well as the accuracy of inspection. In this paper, a dynamic model is created to investigate the vibrational response of an in-pipe inspection robot moving through a dented pipe. A mechanical model of the polyurethane sealing disc is established based on the Kelvin spring damping model to simulate its bending deformation. Using the simplified model of the in-pipe inspection robot, the axial vibration equation of the robot is analyzed in detail. Furthermore, a dynamic simulation of the virtual prototype of the in-pipe inspection robot is conducted using the MSC/ADAMS software, considering the interaction between the fluid and the structure. Then, the effects of the robot’s speed, sealing disc interval, and dent height on the vibration response during the pigging are examined. The results indicate that the faster the in-pipe inspection robot passes over the pipe dents, the higher the axial vibration generated by the robot, while the time needed for returning to the stable state is shorter. The pitch vibration caused by the dent substantially intensifies with an increase in the sealing disc interval. The axial and pitch vibration caused by the dent intensify significantly with increasing the dent height. The results obtained herein should prove useful to the optimization of the structural design and precise positioning of the in-pipe inspection robot.

Beam-column joints are responsible for maintaining the integrity and stability of frame structures, and any damage to these critical components can endanger the overall safety and reliability of the structure. Hence, early detection of structural joint damage is of paramount importance. However, most of the available structural damage identification methods focus on identifying damage in structural members, and relatively fewer methods have been developed so far for assessing damage in structural joints. In view of this, the present study proposes a new two-stage method for joint damage identification of frame structures. In the first stage, an efficient damage indicator, called residual moment-based joint damage index (RMBJDI), is developed and applied to detect the location of potentially damaged joints. This damage indicator can help to reduce the number of involved damage variables by excluding healthy joints from the problem. In the second stage, the reduced dimension damage identification problem is formulated as an optimization problem and is further tackled by employing a robust meta-heuristic algorithm, namely equilibrium optimizer (EO), to determine the damage severity of suspected damaged joints. In order to assess the capability and effectiveness of the presented joint damage identification method, two numerical examples of frame structures are conducted under both noise-free and noisy conditions. The results demonstrate that the proposed two-stage method, which integrates RMBJDI with EO, is a highly accurate and powerful tool for localizing and quantifying the joint damage in frame structures.

This work focuses on the dynamic response of the functionally graded porous (FGP) plates. To construct the FGP plate model, the material-distributed profiles of the FGP plates are given first. In addition, the relations between the stress and strain are given by means of the first-order shear deformation theory (FSDT). Furthermore, the boundary conditions are defined based on the virtual spring technique. Moreover, the third kind of Chebyshev orthogonal polynomials are employed to construct the displacement components of the FGP plate, and the energy expressions of the FGP plate are constructed and then changed into the Lagrange equation form. Ultimately, the FGP plate energy expressions are solved by means of the Rayleigh–Ritz method. On this basis, the verification of the proposed method is conducted, and then, a series of investigations are given with respect to diverse influence factors.

This research presents a novel model to examine the vibration and deflection analysis of the visco-magnetostrictive doubly-curved sandwich shell subjected to Kerr’s foundation. The shell has a homogenous core with two magnetostrictive layers and two viscoelastic faces. A velocity feedback control process is applied to reduce the vibration of the system using an active strategy. In the present model, active (magnetostrictive materials) and passive (viscoelastic materials) strategies are applied together to suppress the vibration of the sandwich shell. Simple sinusoidal deformation theory (SSDT) is dedicated to inspecting the shear impacts along with the thickness of the sandwich shell. Hamilton’s axiom and Kelvin–Voigt relation are dedicated to achieving the governing equations of motion. Then, the Navier solution technique is dedicated to deriving the eigenfrequency of the sandwich shell with simply-supported (S-S) boundary conditions. The results indicate that the present model can improve the vibration reduction of the curved structures by using the amalgamation of the passive and active strategies. Also, the application of Kerr’s foundation has a major impact on the vibration reduction of the system.

Aluminum foam/polyurethane (AF/PU) interpenetrating phase composites damper is a multi-phased hysteretic friction damper, which has a high potential for application to mitigating the seismic responses of building structures. In this paper, the hysteretic responses of the AF/PU composites damper subjected to different loading displacement amplitudes and loading cycles were experimentally investigated, and the main characteristics of the multi-phased hysteretic friction responses are assessed. According to the hysteretic responses of the AF/PU composites damper, a new model that is featured by a hysteresis mechanism, a nonlinear spring and a damping dashpot in parallel is constructed. Through the sensitivity analysis of relevant parameters, the optimum model is obtained and its main basic parameters ($E,K_e,C$) are identified using the Universal Global Algorithm of the First Optimization software. The relationships of the main basic parameters with the loading displacement amplitude and loading cycle are then established. By the comparisons with the experimental results, it is validated that the proposed optimum model has an adequate capacity to capture and predict the important features of the multi-phased hysteretic friction characteristics under the various loading displacement amplitudes and loading cycles.

In this study, the out-of-plane free vibration equations of circular curved and clothoid transition curved girders with various boundary conditions were derived. The continuous curved girder with combined linetypes was discretized into separate curved girder elements. Based on the differential quadrature element method (DQEM), the Chebyshev–Gauss–Labatto unequal mesh division was applied to discretize the vibration equations of the continuous curved girder into those of the curved girder elements, along with the boundary conditions, internal geometric compatibility conditions, and force balance conditions. The out-of-plane natural frequency equations were derived considering the boundary conditions by the substitution method. The free vibration was solved for continuous curved girders with combined linetypes of circular and clothoid transition curves. The effectiveness of the DQEM was verified, and the effect of the number of grid points on the accuracy of the solution was evaluated. In addition, the effects of the bending/torsional stiffness ratio, warping coefficient, and boundary conditions on the natural frequencies of continuous curved girders with combined linetypes were investigated. The results showed that the DQEM can be efficiently used to solve the free vibration of multispan continuous curved girders with various linetype combinations. The frequencies of the continuous curved girder with combined linetypes decrease with the weakening of boundary constraints, but increase with increasing warping coefficient and bending/torsional stiffness ratio.

This work examines the effect of porosity distributions on thermal buckling analysis of functionally graded material (FGM) sandwich plates. To consider the porosity effect, five different types of distribution models, even, uneven, logarithmic uneven, linear uneven, and sinusoidal uneven are considered. It is assumed that the FGM faces of the sandwich plate are porous while the ceramic core is nonporous. To investigate the thermal buckling behavior of porous FGM sandwich plates, four different types of thermal loads, such as uniform, linear, nonlinear, and sinusoidal temperature rise along the thickness direction are considered. Effective material properties and thermal expansion coefficients of FGM sandwich plates are evaluated based on Voigt’s micromechanical model considering power law FGM (P-FGM) and sigmoid function FGM (S-FGM). The analytical solution is carried out using Hamilton’s variational principle considering the von Karman nonlinearity. The equilibrium and stability equations are derived based on sinusoidal shear deformation theory (SSDT). Numerical results are obtained to observe the influence of different porosity distributions, porosity coefficients, thermal loadings, and geometrical parameters over critical thermal buckling temperature.