Effect of uncertainties in wind speed and direction on the fatigue damage of long-span bridges

Alduse, Bejoy P.; Jung, Sungmoon; Vanli, O. Arda; Kwon, Soon-Duck

doi:10.1016/j.engstruct.2015.06.031

Cited by 24 publications

(14 citation statements)

References 33 publications

(77 reference statements)

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“…Chen and Wang developed a probabilistic cumulative fatigue damage model using Bayesian learning for long‐term SHM of long‐span suspension bridges under wind excitation; the method was utilized to analyze the measurement data from the Tsing Ma Bridge in Hong Kong, and results show that the model is suitable for the probabilistic fatigue assessment. Alduse et al presented a Bayesian approach to estimate wind‐induced fatigue damage of long‐span bridges under the effect of uncertainties in wind speed and direction; this method makes the analysis of fatigue damage boundary and exceeding probability more comprehensive, because it provides the distribution of damage value; compared with the conventional fatigue damage assessment method, results show that the proposed method is more reliable. Cho et al developed a Bayesian correlation prediction model for analyzing the relativity of hydrogen‐induced cracking in the cable wires of a steel suspension bridge; the model demonstrates better convergence and approximation capabilities when compared with a conventional linear prediction model.…”

Section: Recent Progress On Damage Identification Methods For Suspensmentioning

confidence: 99%

Recent progress and future trends on damage identification methods for bridge structures

Chatzi

Sim

et al. 2019

Struct Control Health Monit

187

112

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Summary Damage identification forms a key objective in structural health monitoring. Several state‐of‐the‐art review papers regarding progress in this field up to 2011 have been published. This paper summarizes the recent progress between 2011 and 2017 in the area of damage identification methods for bridge structures. This paper is organized based on the classification of bridge infrastructure in terms of fundamental structural systems, namely, beam bridges, truss bridges, arch bridges, cable‐stayed bridges, and suspension bridges. The overview includes theoretical developments, enhanced simulation attempts, laboratory‐scale implementations, full‐scale validation, and the summary for each type of bridges. Based on the offered review, some challenges, suggestions, and future trends in damage identification are proposed. The work can be served as a basis for both academics and practitioners, who seek to implement damage identification methods in next‐generation structural health monitoring systems.

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Section: Recent Progress On Damage Identification Methods For Suspensmentioning

confidence: 99%

Recent progress and future trends on damage identification methods for bridge structures

Chatzi

Sim

et al. 2019

Struct Control Health Monit

187

112

View full text Add to dashboard Cite

show abstract

“…During the calculation, 0:05r 2 a can be used as the upper limit of integration in equation (5). Here, we discuss only the integral length scales of longitudinal and transverse turbulent wind in the along-wind direction, L x u and L x v .…”

Section: Turbulence Intensity and Integral Length Scale Of Fluctuatinmentioning

confidence: 99%

“…1 The research on wind-induced vibrations of bridges is becoming more important with the continuous emergence of bridges with new record-span lengths. [2][3][4][5] For example, flutter determines structural safety under high-speed winds; vortex-induced oscillations greatly influence bridge performance in low-speed winds; and buffeting can influence bridge fatigue even under normal wind conditions. Therefore, wind resistance safety assessment is critical for both the design and operation of largespan bridges.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, the parameters in Figure 20, including I u , r 2 u , and G u , which reflect the turbulence degree, are generally smaller over a 1-min time interval. The reduction of the low-frequency components also reduces the autocorrelation of fluctuating winds, thereby decreasing the turbulent integral length scale derived from equation (5). This might explain the significant decrease of L x u in Figure 20 when using a 1-min averaging time interval.…”

mentioning

confidence: 97%

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Wind characteristics at a long-span sea-crossing bridge site based on monitoring data

Zhou

Sun

Xie

2018

Journal of Low Frequency Noise, Vibration and Active Control

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Six years of wind data are used to investigate the statistical characteristics of general and strong winds acting on the Donghai Bridge, a sea-crossing bridge in China. The general wind at the bridge site shows a relatively stable annual repeatability, and the discrepancies are found between the measured wind field parameters and those suggested by the design code. For strong winds, both the 10-min mean wind speed and the turbulent variance greatly exceed those of general winds, while the turbulence intensity, integral length scale, and gust factor do not exhibit any noticeable quantitative trends. The measured wind spectra of both general and strong winds show a shift toward the high-frequency range compared with Simiu’s spectrum (along-wind direction). The wind measurements at the bridge site are easily interfered with the bridge structure itself, resulting in a greater turbulence along the bridge axis and a higher turbulent kinetic energy in the high-frequency range, which needs to be considered in designing structural health monitoring systems in the future. This study provides field evidence for the wind-resistant design and evaluation of long-span sea-crossing bridges.

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“…Hong [14] and Hosch [15] observed the fatigue failure of sign, luminaire, and traffic signal support structures caused by natural wind-induced vibration and developed a comprehensive approach for fatigue design. Alduse proposed [16] a Bayesian approach to estimate the wind-induced fatigue damage of long-span bridges while considering the uncertainties in the probability model and the parameter. Repetto [17] proposed a novel approach of two levels of formulae to evaluate the alongwind-induced fatigue of slender structures and structural elements.…”

mentioning

confidence: 99%

Comprehensive investigation on the cause of a critical crack found in a diagonal member of a steel truss bridge

Wang

Nakamura

Okumatsu

et al. 2017

Engineering Structures

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Ikitsuki Bridge is a three span continuous truss bridge with a length of 800 m, which was completed in July, 1991. In December 2009, a crack which seriously damages the safety of the bridge was found in a diagonal member near an intermediate pier during an inspection for determining points to be annually inspected. In order to identify its cause, some tests on the material used for the cracked member were conducted, and a long-term monitoring of wind and vibration of some diagonal members with similar structural characteristics to the cracked member had been carried out since December 2011. In this article, the outline of the crack is presented and the main causes of the crack are discussed based on the results of the tests and monitoring. The conclusions can be summarized as follows: i) The crack initiated and propagated to become approximately 200 mm long as a fatigue crack. The quality of material and weld satisfies the requirement for them. ii) The vibration of the diagonal members is induced by the wind with the velocity of 6-8 m/s and higher than 15 m/s in the direction approximately normal to the bridge longitudinal axis. The maximum stress range induced by the vibration due to 6-8 m/s wind is approximately 30-40 MPa, while that due to the wind blowing at the velocity of over 15 m/s can be 195 MPa. iii) These wind-induced vibrations are thought to be the main cause of the fatigue crack.

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Effect of uncertainties in wind speed and direction on the fatigue damage of long-span bridges

Cited by 24 publications

References 33 publications

Recent progress and future trends on damage identification methods for bridge structures

Recent progress and future trends on damage identification methods for bridge structures

Wind characteristics at a long-span sea-crossing bridge site based on monitoring data

Comprehensive investigation on the cause of a critical crack found in a diagonal member of a steel truss bridge

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