Experimental Investigations on Nonlinear Flutter Behaviors of a Bridge Deck with Different Leading and Trailing Edges

Recently, the nonlinear flutter behavior of long-span suspension bridges has attracted attention. Unlike the classical theory of bridge flutter, the stable limit cycle oscillations (LCO) have occurred for some bluff aerodynamic configurations when the inflow velocity exceeded a specific critical value. To explore the influence of aerodynamic configurations on flutter behaviors a series of flutter tests for spring-suspended sectional models were conducted. When the leading edges and trailing edges with various shapes were installed at the sectional models, different flutter types occurred. In the test, the self-excited forces and flutter responses were measured. Then, the characteristics of coupling vibration and aerodynamic hysteresis of the two kinds of flutter were analyzed and compared. Finally, the role of the phase difference between self-excited forces and displacements was discussed in the mechanism difference of the classical flutter and the postflutter LCO. As the leading edge became the bluffer, the results showed that the type of flutter gradually transformed from classical divergent flutter to postcritical LCO and the torsional mode played a more important role in the flutter than in the vertical mode. For the postflutter LCO, there was a negative feedback pattern, i.e., as the vibration amplitude increased, the phase difference gradually decreased, and the energy input to the dynamic system did not grow rapidly, which limited the further vibration divergence and resulted in a stable LCO

Numerical Investigation of Very-Large-Scale Motions in a Turbulent Boundary Layer for Different Roughness

Wall-model large eddy simulations (WMLES) are conducted to investigate the spatial features of large-scale and very-large-scale motions (LSMs and VLSMs) in turbulent boundary flow in different surface roughnesses at a very high Reynolds number, O (106–107). The results of the simulation of nearly smooth cases display good agreement with field observations and experimental data, both dimensioned using inner and outer variables. Using pre-multiplied spectral analysis, the size of VLSMs can be reduced or even disappear with increasing roughness, which indirectly supports the concept that the bottom-up mechanism is one of the origins of VLSMs. With increases in height, the power of pre-multiplied spectra at both high and low wavenumber regions decreases, which is consistent with most observational and experimental results. Furthermore, we find that the change in the spectrum scaling law from −1 to −5/3 is a gradual process. Due to the limitations of the computational domain and coarse grid that were adopted, some VLSMs and small-scale turbulence are truncated. However, the size of LSMs is fully accounted for. From the perspective of the spatial correlation of the flow field, the structural characteristics of VLSMs under various surface roughnesses, including three-dimensional length scales and inclination angles, are obtained intuitively, and the conclusions are found to be in good agreement with the velocity spectra. Finally, the generation, development and extinction of three-dimensional VLSMs are analyzed by instantaneous flow and vorticity field, and it shows that the instantaneous flow field gives evidence of low-speed streamwise-elongated flow structures with negative streamwise velocity fluctuation component, and which are flanked on each side by similarly high-speed streamwise-elongated flow structures. Moreover, each of the low-speed streamwise-elongated flow structure lies beneath many vortices

Effects of the configuration of trailing edge on the flutter of an elongated bluff body

10.3390/app112210818Applied Sciences (Switzerland)11221081

The effects of aerodynamic interference on the aerodynamic characteristics of a twin-box girder

10.3390/app11209517Applied Sciences (Switzerland)1120951

Effects of leading-edge separation on the vortex-induced vibration of an elongated bluff body

Wind-tunnel experiments were conducted to investigate the effects of leading-edge separation on the vortex-induced vibration (VIV) of an elastically-supported elongated bluff body. Solid wind barriers of various heights were fixed in the leading edge to adjust the flow separation. The vibration signals and the flow field information are acquired simultaneously by a laser-displacement system and particle image velocimetry (PIV) instrument respectively. The result shows that the VIV is excited by consecutive vortices shedding from the leading-edge shear layer. There is a critical height-to-thickness ratio (h/t)(critical) >= 0.4, the VIVs are observed when h/t 0.4, while they are suppressed owing to the insignificant leading-edge separation when h/t < 0.4. Three types of VIV are found, two of them are torsional VIV while another one is vertical VIV, which are named T1, T2, and V1 respectively. By placing a wake splitter plate at the trailing edge, V1 is suppressed entirely, T1 is weakened despite the slightly lower amplitude, while T2 transits to limit-cycle oscillations. The flow field information shows that the evolution and shedding pattern of leading-edge vortices vary from mode to mode. The status of the upperlayer leading-edge separated layer significantly affects the formation and the shedding of the trailing-edge vortices. The results reveal that leading-edge separation can play a dominant role in the vortex-induced vibrations of elongated bluff bodies

A Field Investigation on Vortex-Induced Vibrations of Stay Cables in a Cable-Stayed Bridge

A field study was conducted to identify the vortex-induced vibrations (VIVs) of stay cables in a cable-stayed bridge. A full-scale health-monitoring system was established to observe the wind effects of the selected cables. The vibration amplitudes in the twenty selected stay cables were first studied. The results indicate that only cable CAC20 has large amplitudes with a multimode and high-frequency vibration in the investigated period. The correlation between the wind and cable vibration was subsequently investigated. The large vibration amplitudes are primarily located in the mean speed scope of 4 to 6 m/s, simultaneously close to the reduced velocity of five when the wind was almost perpendicular to the bridge axis and had a smaller turbulence intensity. Moreover, the relationship between the maximum vibration amplitude with the mean wind speed was fitted by a function that was validated by the measured data. Finally, an estimation method was presented to predict the participative vibration modes that would happen in the VIVs of the stay cables, according to the known wind and cable parameters. The measured cable vibrations were employed to validate this estimation method. The results indicate the estimated vibration modes are close to the measured vibration modes

A ML-Based Wind Speed Prediction Model with Truncated Real-Time Decomposition and Multi-Resolution Data

Accurate wind speed prediction is of importance for long-span cross-sea bridges. To this end, data decomposition techniques are usually employed to promote accuracy of the prediction model. Since wind speed data come sequentially, real-time decomposition should be adopted. However, real-time decomposition may degrade the accuracy due to the end effect. In this paper, a novel scheme of real-time decomposition that is a combination of truncated real-time decomposition and multi-resolution data is developed. Specifically, truncated real-time decomposition firstly denoises the data and eliminates the end effect; high-resolution data are then introduced to compensate for the information loss. Further, a novel wind speed prediction model that consists of the proposed scheme and neural networks is proposed. Specifically, two gated recurrent unit neural networks are employed to extract features from the obtained original-resolution and high-resolution data, respectively, and a multi-layer perceptron is adopted to utilize extracted features and make predictions. The proposed model is validated on the monitoring wind speed data of two long-span cross-sea bridges. Specifically, the mean absolute error and the root of mean square error of the proposed model on the two datasets are 0.334, 0.445 and 0.233 and 0.316 m/s, which are smaller than benchmark models and demonstrate superiority of the proposed model

A ML-Based Wind Speed Prediction Model with Truncated Real-Time Decomposition and Multi-Resolution Data

Accurate wind speed prediction is of importance for long-span cross-sea bridges. To this end, data decomposition techniques are usually employed to promote accuracy of the prediction model. Since wind speed data come sequentially, real-time decomposition should be adopted. However, real-time decomposition may degrade the accuracy due to the end effect. In this paper, a novel scheme of real-time decomposition that is a combination of truncated real-time decomposition and multi-resolution data is developed. Specifically, truncated real-time decomposition firstly denoises the data and eliminates the end effect; high-resolution data are then introduced to compensate for the information loss. Further, a novel wind speed prediction model that consists of the proposed scheme and neural networks is proposed. Specifically, two gated recurrent unit neural networks are employed to extract features from the obtained original-resolution and high-resolution data, respectively, and a multi-layer perceptron is adopted to utilize extracted features and make predictions. The proposed model is validated on the monitoring wind speed data of two long-span cross-sea bridges. Specifically, the mean absolute error and the root of mean square error of the proposed model on the two datasets are 0.334, 0.445 and 0.233 and 0.316 m/s, which are smaller than benchmark models and demonstrate superiority of the proposed model