In order to effectively simulate nonstationary stochastic turbulent wind fields, four separation hybrid (SEP-H) models are proposed in the present study. Based on the assumption that the lateral turbulence component at one single-point is uncorrelated with the longitudinal and vertical turbulence components, the fluctuating wind is separated into 2nV-1D and nV1D nonstationary stochastic vector processes. The first process can be expressed as double proper orthogonal decomposition (DPOD) or proper orthogonal decomposition and spectral representation method (POD-SRM), and the second process can be expressed as POD or SRM. On this basis, four SEP-H models of nonstationary stochastic turbulent wind fields are developed. In addition, the orthogonal random variables in the SEP-H models are presented as random orthogonal functions of elementary random variables. Meanwhile, the number theoretical method (NTM) is conveniently adopted to select representative points set of the elementary random variables. The POD-FFT (Fast Fourier transform) technique is introduced in frequency to give full play to the computational efficiency of the SEP-H models. Finally, taking a long-span bridge as the engineering background, the SEP-H models are compared with the dimension-reduction DPOD (DR-DPOD) model to verify the effectiveness and superiority of the proposed models.

A flexible-base coupled-two-beam (CTB) discrete model with equivalent tuned mass dampers is used to assess the effect of soil-structure interaction (SSI) and different types of lateral resisting systems on the design of passive dynamic absorbers (PDAs) under the action of along-wind and across-wind loads due to vortex shedding. A total of five different PDAs are considered in this study: (1) tuned mass damper (TMD), (2) circular tuned sloshing damper (C-TSD), (3) rectangular tuned sloshing damper (R-TSD), (4) two-way liquid damper (TWLD) and (5) pendulum tuned mass damper (PTMD). By modifying the non-dimensional lateral stiffness ratio, the CTB model can consider lateral deformations varying from those of a flexural cantilever beam to those of a shear cantilever beam. The Monte Carlo simulation method was used to generate along-wind and across-wind loads correlated along the height of a real shear wall-frame building, which has similar fundamental periods of vibration and different modes of lateral deformation in the xz and yz planes, respectively. Ambient vibration tests were conducted on the building to identify its real lateral behavior and thus choose the most suitable parameters for the CTB model. Both alongwind and across-wind responses of the 144-meter-tall building were computed considering four soil types (hard rock, dense soil, stiff soil and soft soil) and a single PDA on its top, that is, 96 time-history analyses were carried out to assess the effect of SSI and lateral resisting system on the PDAs design. Based on the parametric analyses, the response significantly increases as the soil flexibility increases for both type of lateral wind loads, particularly for flexural-type deformations. The results show a great effectiveness of PDAs in controlling across-wind peak displacements and both along-wind and across-wind RMS accelerations, on the contrary, PDAs were ineffective in controlling along-wind peak displacements on all soil types and different kind of lateral deformation. Generally speaking, the maximum possible value of the PDA mass efficiency index increases as the soil flexibility increases, on the contrary, it decreases as the non-dimensional lateral stiffness ratio of the building increases; therefore, there is a significant increase of the vibration control effectiveness of PDAs for lateral flexural-type deformations on soft soils.

To ensure the flutter stability of three-tower suspension bridges under skew wind, by using the computational procedure of 3D refined flutter analysis of long-span bridges under skew wind, in which structural nonlinearity, the static wind action(also known as the aerostatic effect) and the full-mode coupling effect etc., are fully considered, the flutter stability of a three-tower suspension bridge-the Taizhou Bridge over the Yangtze River in completion and during the deck erection is numerically investigated under the constant uniform skew wind, and the influences of skew wind and aerostatic effects on the flutter stability of the bridge under the service and construction conditions are assessed. The results show that the flutter critical wind speeds of three-tower suspension bridge under service and construction conditions fluctuate with the increase of wind yaw angle instead of a monotonous cosine rule as the decomposition method proposed, and reach the minimum mostly in the case of skew wind. Both the skew wind and aerostatic effects significantly reduce the flutter stability of three-tower suspension bridge under the service and construction conditions, and the combined skew wind and aerostatic effects further deteriorate the flutter stability. Both the skew wind and aerostatic effects do not change the evolution of flutter stability of the bridge during the deck erection, and compared to the service condition, they lead to a greater decrease of flutter critical wind speed of the bridge during deck erection, and the influence of the combined skew wind and aerostatic effects is more prominent. Therefore, the skew wind and aerostatic effects must be considered accurately in the flutter analysis of three-tower suspension bridges.

Large Eddy Simulation (LES) is used to explore the influence of vibration frequency and amplitude on the aerodynamic performance of a rectangular cylinder with an aspect ratio of B/D=5 (B: breadth; D: depth of cylinder) at a Reynolds number of 22,000 near resonance frequency. In smooth flow conditions, the research employs a sequence of three-dimensional simulations under forced vibration with diverse frequency ratios f_e / f_o = 0.8-1.2 (f_e : oscillation frequency; f_o : Strouhal frequency when the rectangular cylinder is stationary ) and oscillation amplitudes A_h/D = 0.05 - 0.3. The individual influences of f_e / f_o and A_h/D on the characteristics of integrated and distributed aerodynamic forces are the focal points of discussion. For the integrated aerodynamic force, particular emphasis is placed on the analysis of the dependence of velocity-proportional component C₁ and displacement-proportional component C₂ of unsteady aerodynamic force on amplitude and frequency ratio. Near the resonance frequency, the dependencies of C₁ and C₂ on amplitude are stronger than that of frequency ratio. For the distributed aerodynamic force, the increase in frequency and amplitude promotes the position of the main vortex core and reattachment to the leading edge in the streamwise direction. In the spanwise direction, vibration enhances the spanwise correlation of aerodynamic force to weaken the three-dimensional effect of the flow field, and a lower frequency ratio and larger amplitude amplify this effect.

Reliable wind signal reconstruction can be beneficial to the operational safety of long-span bridges. Non-Gaussian characteristics of wind signals make the reconstruction process challenging. In this paper, non-Gaussian wind signals are converted into a combined prediction of two kinds of features, actual wind speeds and wind angles of attack. First, two decomposition techniques, empirical mode decomposition (EMD) and variational mode decomposition (VMD), are introduced to decompose wind signals into intrinsic mode functions (IMFs) to reduce the randomness of wind signals. Their principles and applicability are also discussed. Then, four artificial intelligence (AI) algorithms are utilized for wind signal reconstruction by combining the particle swarm optimization (PSO) algorithm with back propagation neural network (BPNN), support vector regression (SVR), long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM), respectively. Measured wind signals from a bridge site in a deep-cutting gorge are taken as experimental subjects. The results showed that the reconstruction error of high-frequency components of EMD is too large. On the contrary, VMD fully extracts the multiscale rules of the signal, reduces the component complexity. The combination of VMD-PSO-Bi-LSTM is demonstrated to be the most effective among all hybrid models.