Statistical Analysis of Basic Dynamic Characteristics of Large Span Cable-Stayed Bridge Based on High Order Perturbation Stochastic FEM

Abstract

With the quick development of transportation in China, long span cable-stayed bridges have been widely constructed to cross large rivers and deep canyons attribute to their unique structural forms and mechanical properties. For large-scale cable-stayed bridges, how to determine their basic dynamic characteristics or modal data is an important issue on the dynamic analysis of bridge structures. Noting the uncertainty of structural parameters or geometric shape, it is also of significance to find out the statistic dynamic characteristics of uncertain long span cable-stayed bridges. At the present paper, different from traditional low order perturbation stochastic approach, a high order perturbation stochastic FEM called as recursive stochastic finite element method was employed, which is a good practical approximation method compared to the Monte Carlo simulation method. Taking Edong Yangtze River Bridge as a research objective, the recursive stochastic finite element method was employed to solve the modal data of large span cable-stayed bridge with random parameters. Firstly, in the non-orthogonal polynomial presentation, natural frequencies and mode shapes of the random cable-stayed bridge were expressed. Then coefficients of the non-orthogonal polynomial expansion are able to be determined through high order perturbation technique. On the basis of the coefficients obtained, the probability density functions and statistic characteristics of the modal data were straightforward to implement. In accordance with detailed analyzations and discussions on the basic dynamic characteristics of the cable-stayed bridge, it can be found that the randomness of sectional flexural stiffness of the deck beam and bridge towers is very sensitive to many modes of Edong Yangtze River Bridge. However, the elastic stiffness simulating the pile-soil interaction has less influence on the in-plane modes.