2015
DOI: 10.1016/j.engstruct.2015.06.031
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Effect of uncertainties in wind speed and direction on the fatigue damage of long-span bridges

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Cited by 26 publications
(17 citation 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%
“…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%
“…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%
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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%