Long-term monitoring of wind field characteristics and dynamic response of a long-span suspension bridge in complex terrain

Fenerci, Aksel; Øiseth, Ole; Rönnquist, Anders

doi:10.1016/j.engstruct.2017.05.070

Cited by 118 publications

(35 citation statements)

References 40 publications

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“…Accelerometer monitoring is an effective means with which to monitor the dynamic characteristics of long-span bridges [1,2]. However, it inevitably causes drift errors as it requires a double integral for acquiring deformation displacement [3,4].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Parameter Identification of a Long-Span Arch Bridge Based on GNSS-RTK Combined with CEEMDAN-WP Analysis

Xiong

Niu

2019

Applied Sciences

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Under the action of wind, traffic, and other influences, long-span bridges are prone to large deformation, resulting in instability and even destruction. To investigate the dynamic characteristics of a long-span concrete-filled steel tubular arch bridge, we chose a global navigation satellite systems-real-time kinematic (GNSS-RTK) to monitor its vibration responses under ambient excitation. A novel approach, the use of complete ensemble empirical mode decomposition with adaptive noise combined with wavelet packet (CEEMDAN-WP) is proposed in this study to increase the accuracy of the signal collected by GNSS-RTK. Fast Fourier transform (FFT) and random decrement technique (RDT) were adopted to calculate structural modal parameters. To verify the combined denoising and modal parameter identification methods proposed in this paper, we established the structural finite element model (FEM) for comparison. Through simulation and comparison, we were able to draw the following conclusions. (1) GNSS-RTK can be used to monitor the dynamic response of long-span bridges under ambient excitation; (2) the CEEMDAN-WP is an efficient method used for the noise reduction of GNSS-RTK signals; (3) after signal filtering and noise reduction, structural modal parameters are successfully derived through RDT and illustrated graphically; and (4) the first-order natural frequency identified by field measurement is slightly higher than the FEM in this work, which may have been caused by bridge damage or the inadequate accuracy of the finite element model.

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Section: Introductionmentioning

confidence: 99%

Dynamic Parameter Identification of a Long-Span Arch Bridge Based on GNSS-RTK Combined with CEEMDAN-WP Analysis

Xiong

Niu

2019

Applied Sciences

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“…This bridge have 20 triaxial accelerometers for measuring the dynamic response, and eight anemometers that measures wind velocities in the main span [28], as shown in Fig. 3.…”

Section: Data From the Hardanger Bridgementioning

confidence: 99%

Inverse Identification of Buffeting and Self-Excited Wind Loads on the Hardanger Bridge From Acceleration Data

Petersen¹,

Øiseth²,

Nord³

et al. 2019

Proceedings of the 7th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

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The traditional wind load assessment for long-span bridges rely on assumed models for the wind field and aerodynamic coefficients from wind tunnel tests, which usually introduces some uncertainties. It is therefore desired to develop tools that can utilize full-scale vibration response data from existing bridges in order to study the wind loading in detail for in-situ conditions. This paper presents a novel case study of inverse identification of dynamic wind loads on the 1310 m long Hardanger bridge, a suspension bridge equipped with a network of accelerometers. The identification method used is an extented Kalman-type filter for joint input, state, and parameter estimation. A system model considering the still-air modes in addition to a quasi-steady submodel for the self-excited forces of the bridge is presente. The coefficients for self-excited lift and pitching moment are considered unknown and are jointly estimated with the buffeting forces.

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“…More importantly, their studies can provide references for other long-span bridges in terms of study methods and variations of wind fields at the bridge site. Fenerci et al [17] developed a measurement system consisting of 20 accelerometers and 9 anemometers and used the long-term monitoring data of wind velocities and accelerations on a long-span bridge located in a gorge terrain to investigate the relationship between the wind-loading and responses. Results showed that the wind fields have large variability in the mean wind speed, mean wind direction, turbulence intensities, and length scales in the bridge site.…”

Section: State Of the Artmentioning

confidence: 99%

Layer Character of Wind Fields over the Simplified Gorge Terrain

Peng¹,

Xue²,

Han³

et al. 2017

JESTR

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Characteristics of wind fields over gorge terrains are important not only for pollution dispersion and forest fires but also for civil structures. However, current studies are aimed only at specific gorge terrains. Thus, limited references are available for other engineering practices. Four V-shaped simplified gorge terrains were modeled in the computational domain to investigate the fundamental information of wind fields over gorge terrains, especially the layer character of the wind fields over gorge terrains. The values of mean wind speed and turbulence intensity were analyzed based on the numerical simulations on the wind fields over the four simplified gorges, and the method to calculate the height of the gorge inner layer was proposed. Results show that the wind fields over the simplified gorge terrains can be divided into two layers in the vertical direction, that is, the gorge inner layer and gorge outer layer. This finding proves that the layer character of wind fields exists in gorge terrains. The heights of the gorge inner layer are 0.242 m, 0.224 m, 0.215 m, and 0.208 m, respectively, which correspond to the gorge terrains with included angles of 80°, 100°, 120°, and 140°. This result implies that the smaller the included angle of the gorge terrain is, the higher the gorge inner layer becomes. The proposed method to calculate the height of the gorge inner layer was proved to be accurate, indicating that the derivation process is reasonable and reliable. The study provides new insights on investigating the characteristics of wind fields over gorge terrains.

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Long-term monitoring of wind field characteristics and dynamic response of a long-span suspension bridge in complex terrain

Cited by 118 publications

References 40 publications

Dynamic Parameter Identification of a Long-Span Arch Bridge Based on GNSS-RTK Combined with CEEMDAN-WP Analysis

Dynamic Parameter Identification of a Long-Span Arch Bridge Based on GNSS-RTK Combined with CEEMDAN-WP Analysis

Inverse Identification of Buffeting and Self-Excited Wind Loads on the Hardanger Bridge From Acceleration Data

Layer Character of Wind Fields over the Simplified Gorge Terrain

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