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http://dx.doi.org/10.12989/was.2018.27.3.149

Flutter reliability analysis of suspension bridges based on multiplicative dimensional reduction method  

Guo, Junfeng (School of Civil Engineering, Southwest Jiaotong University)
Zheng, Shixiong (School of Civil Engineering, Southwest Jiaotong University)
Zhang, Jin (School of Civil Engineering, Southwest Jiaotong University)
Zhu, Jinbo (School of Civil Engineering, Southwest Jiaotong University)
Zhang, Longqi (Department of road and bridge engineering, Sichuan Vocational and Technical College of Communications)
Publication Information
Wind and Structures / v.27, no.3, 2018 , pp. 149-161 More about this Journal
Abstract
A reliability analysis method is proposed in this paper based on the maximum entropy (MaxEnt) principle in which constraints are specified in terms of the fractional moments instead of integer moments. Then a multiplicative dimensional reduction method (M-DRM) is introduced to compute the fractional moments. The method is applicable for both explicit and implicit limit state functions of complex structures. After two examples illustrate the accuracy and efficiency of this method in comparison to the Monte Carlo simulation (MCS), the method is used to analyze the flutter reliability of suspension bridge. The results show that the empirical formula method in which the limit state function is explicitly represented as a function of variables is only a too conservative estimate for flutter reliability analysis but is not accurate adequately. So it is not suitable for reliability analysis of bridge flutter. The actual flutter reliability analysis should be conducted based on a finite element method in which limit state function is implicitly represented as a function of variables. The proposed M-DRM provide an alternate and efficient way to analyze a much more complicated flutter reliability of long span suspension bridge.
Keywords
reliability analysis; failure probability; flutter; multiplicative dimensional reduction method (M-DRM); principle of maximum entropy;
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