Abstract
To analytically evaluate buffeting responses, the analysis of wind characteristics such as turbulence intensity, turbulence length, gust, and roughness coefficient must be a priority. The analytical buffeting response is affected by the static aerodynamic force coefficient, flutter coefficient, structural damping ratio, aerodynamic damping ratio, and natural frequencies of the bridge. The cable-stayed bridge of interest in this study has been used for 32 years. In that time, the terrain conditions around the bridge have markedly changed from the conditions when the bridge was built. Further, the wind environments have varied considerably due to climate change. For these reasons, the turbulence intensity, length, spectrum coefficient, and roughness coefficient of the bridge site must be evaluated from full-scale measurements using a structural health monitoring system. Although the bridge is located on a coastal area, the evaluation results indicated that the wind characteristics of bridge site were analogous to those of open terrain. The buffeting response of the bridge was analyzed using the damping ratios, static aerodynamic force coefficients, and natural frequencies obtained from measured data. The analysis was performed for four cases. Two case analyses were performed by applying the variables obtained from measured data, while two other case analyses were performed based on the Korean Society of Civil Engineers (KSCE) Design Guidelines for Steel Cable Supported Bridges. The calculated responses of each analysis case were compared with the buffeting response measured at wind speeds of less than 25 m/s. The responses obtained by numerical analysis using estimated variables based on full-scale measurements agreed well with the measured buffeting responses measured at wind speeds of less than 25 m/s. Moreover, an extreme wind speed of 44 m/s, corresponding to a recurrence interval of 200 years, was derived from the Gumbel distribution. Therefore, the buffeting responses at wind speeds of 45 m/s were also determined by applying the estimated variables. From these results, management criteria based on measurement data for in-service bridge are determined and each level of management is proposed.
Highlights
Wind-induced vibration has become a critical issue in engineering fields due to the increasing number of long-span bridges with slender, low-frequency structures
The wind speed measured on an in-service steel cable bridge was used to evaluate the damping ratio, aerodynamic force coefficient, and natural frequency of the bridge site by analyzing the acceleration and displacement of the bridge along with the wind environment such as the highest wind speed expected for 200 years, turbulence intensity, turbulent length, and roughness coefficient
The aerodynamic damping ratio was estimated by first applying random decrement technique (RDT) to the measured time-series data to estimate the overall damping ratio using the wind speed, and the structural damping ratio estimated for wind speeds below 3 m/s was subtracted from this estimation
Summary
Wind-induced vibration has become a critical issue in engineering fields due to the increasing number of long-span bridges with slender, low-frequency structures. For long-span bridges, wind-tunnel tests typically employ two models (section models and full-structure models) [1] and two stages (construction stage [2] and in-service stage [3]), depending on the aerodynamic characteristics of interest. The most reasonable method for evaluating the buffeting response to the designed wind speed of an in-service bridge utilizes the measured data to extrapolate key parameters. The wind speed measured on an in-service steel cable bridge was used to evaluate the damping ratio, aerodynamic force coefficient, and natural frequency of the bridge site by analyzing the acceleration and displacement of the bridge along with the wind environment such as the highest wind speed expected for 200 years, turbulence intensity, turbulent length, and roughness coefficient. Reasonable management criteria for maintenance of an in-service bridge were proposed using the results of in-situ data-driven buffeting response analysis
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