Failure Probability Analysis of Service Long-Span Bridge Girder Based on Optimal R-Vine Gaussian Copula Model

Abstract:

Considering the correlation among the failure modes of the multiple control monitoring points from the existing long-span bridge girder， a novel optimal R-vine Gaussian copula data fusion method for failure probability analysis is presented. Based on the extreme strain information， an optimal R-vine Gaussian copula model considering the correlation among the failure modes of the multiple control monitoring points is built by combining the corresponding performance functions， the bivariate pair-Gaussian-copula model and the optimal R-vine model. Further， with the first order second moment method， the failure probability analysis of the existing long-span bridge girder is conducted considering the correlation among the failure modes. The feasibility and application of the method proposed is compared with the other analysis methods based on the monitoring data of the existing bridge. The results show that the optimal R-Vine Gaussian copula information fusion method for the failure probability analysis of long-span bridge girder considering the correlation among failure modes is more reasonable.