Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (1): 144-153.doi: 10.13229/j.cnki.jdxbgxb20200758

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Dynamic reliability fusion prediction of long-span bridge girder considering structural serviceability

Xue-ping FAN1,2(),Guang-hong YANG2,Zhi-peng SHANG2,Xiao-xiong ZHAO2,Qing-kai XIAO3,Yue-fei LIU1,2   

  1. 1.Key Laboratory of Mechanics on Disaster and Environment in Western China of the Ministry of Education，Lanzhou University，Lanzhou 730030，China
    2.School of Civil Engineering and Mechanics，Lanzhou University，Lanzhou 730030，China
    3.School of Civil Engineering and Transportation，South China University of Technology，Guangzhou 510641，China
  • Received:2020-10-05 Online:2022-01-01 Published:2022-01-14

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Abstract:

To reasonably predict serviceability-based dynamic reliability of the long-span bridge girder， using the dynamic extreme deflection data at the control monitoring points， a dynamic serviceability reliability prediction approach for the long-span bridge girder is presented through the fusion of multi-dimensional Gaussian copula technique， multivariate Bayesian dynamic linear models （MBDLM） and the First Order Second Moment（FOSM） method. In this approach， the nonlinear correlations among the performance functions for deformation failure modes at the multiple control monitoring points are taken into consideration. The dynamic monitoring extreme deflection data at three control monitoring points from a long-span bridge girder was provided to illustrate the proposed models and methods. The results show that the predicted dynamic reliability of the bridge girder， considering the time-variant nonlinear correlation of deformation failure modes at the multiple control monitoring points， is larger than that without considering the time-dependent nonlinear correlation of deformation failure modes. This suggests that the predicted results without considering the time-variant nonlinear correlation of deformation failure modes at the multiple control monitoring points are conservative.

Key words: structural engineering, multi-dimensional Gaussian Copula technique, multivariate Bayesian dynamic linear models, first order second moment method, dynamic reliability prediction

CLC Number: 

  • TU391

Fig.1

Modeling processes of MBDLM"

Fig.2

Positions of monitoring girder （4#） and monitoring points"

Fig.3

Monitoring stresses of three control monitoring points"

Fig.4

Predicted extreme deflections and prediction precision"

Fig.5

Predicted reliability indices and failure probability at point A"

Fig.6

Predicted reliability indices and failure probability at point B"

Fig.7

Predicted reliability indices and failure probability at point C"

Fig.8

Predicted dynamic correlation coefficients"

Fig.9

Predicted failure probability of the 4# reinforced concrete box girder"

Fig.10

Predicted reliability indices of the 4# reinforced concrete box girder"

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