Structural Static And Seismic Reliability Analysis Of Long-span Cable-stayed Bridges

With the prominently esthetic feature and excellently structural beahavior performance, cable-stayed bridges are one of the most competitive bridges for long-span bridges. Until now the design and construction of modern long-span cable-stayed bridge are basically adopted the deterministic method, which is not accordance with the structural behavior. The responses of cable-stayed bridge under environmental effects are essentially affected by many random factors such as external loadings, material parameters and geometry factors of the cable-stayed bridges. As a highly indeterminate and flexible structure, the structural responses of long-span cable-stayed bridges are complex. It is difficult to use the deterministic method to demonstrate the substantial influence on the cable-stayed bridge's security which results from the stochastic variations of structural material parameters, geometry factors and external loadings. The reliability analysis of structures provides some solutions for the structural security of long-span cable-stayed bridges which is under the effect of random factors, and the reliability analysis method also provides the design, construction and maintainence of long-span cable-stayed bridges with a more rational basis. And the systematic and seismic reliability analysis is one of problems which are needed to be solved for the design and construction of long-span cable-stayed bridges. With three completed cable-stayed bridges as the engineering background, the systematic and seismic reliability of long-span cable-stayed bridges were investigated and presented in this dissertation. The theoretical innovations and main technological results are summarized as follows:(1) Based on the incremental virtual work equation of 2-D continuum, the incremental equilibrium equations of a plane beam and truss element in T.L. formulation was developed. The elastic and geometric stiffness matrix were deduced, and the elasto-plastic stiffness matrix of the beam element was calculated with the fiber model. The formula of response gradients in Direct Differentiation Method was deduced. A nonlinear FEM/FORM reliability approach was proposed and a stochastic finite element program written in FORTRAN was developed. Several numerical examples were computed to validate the accuracy and high efficiency of the proposed approach and program.(2) Considering the influence of random fields, the reliability of the long-span cable-stayed bridge under the serviceability limit-state was studied, and the sensitivities of the reliability index with respect to the means and the standard deviations of the random variables were computed. The most sensitive random variables on the reliability index were distinguished. The rules of the sensitivity which results from the distributed parameters of the discrete random variables in the random field to the reliability index were summarized.(3) The element reliability indices of the pylons and the main girder and the cables of the long-span cable-stayed bridge under the ultimate limit-state were calculated, and the sensitivities of the random variable's distributed parameter about the typical component units are engaged. The random variables which have the greatest impact on the reliability index of different units about the pylons and the main girder and the cables of the long-span cable-stayed bridge were found out. The rules of the sensitivity in which the distributed parameters of the discrete random variables in random fields to the reliability index of different units about the tower and the girder and the cables were concluded.(4) With considering the influence of geometrical nonlinearity, the system reliability at level 2 of the long-span cable-stayed bridge was analyzed. The (3-unzipping method was used to search the main failure modes of the cable-stayed bridge which is regarded as a series-parallel system in the end.(5) The artificial neural network-based (ANN) Response Surface Method and the support vector machines-based (SVM) Response Surface Method were proposed to make some improvement about the traditional quadratic Response Surface Method. The first-order and the second-order gradients of the response based on ANN and SVM with respect to random variables are derived. The generalizing ability of ANN and SVM was used to resolve the problems with multiple design points in the limit state function and the highly nonlinear limit state function.(6) The ANN-based and SVM-based pattern recognition reliability methods were studied by transforming the Monte Carlo simulation to a two classification problem in the same probability. The results of the numerical examples showed that the MLP-based and SVM-based pattern recognition reliability methods can enhance the computational efficiency of Monte Carlo simulation. The radial basis function network is not suited for the pattern recognition reliability method.(7) The Important Sampling Method is improved by ANN-based and SVM-based important sampling methods from the viewpoints of the RSM and pattern recognition. The accuracy and efficiency of the ANN-based and SVM-base important sampling methods were verified by the results of the numerical examples. The radial basis function network can not be used as a classifier in the pattern recognition important sampling method.(8) The results of the reliability analysis of the Jiujiang Cable-Stayed bridge under the serviceability limit-state indicate that the accuracy and efficiency of the ANN-based and SVM-base reliability methods are verified. These methods can be used in structural reliability analysis of practical long-span bridges.(9) The first-order reliability method was used to study the first excursion question of long-span cable-stayed bridges. It is very difficult to determine the exact design point excitation. The artificial neural network-based design-point excitation method was suggested to give a favorable starting point to obtain the exact design point excitation. The first excursion probability of the crucial section of the tower in the Pearl River Huangpu Bridge was investigated by the first-order reliability method.(10) The first excursion question was converted from the dynamic reliability problem to a static reliability problem, and the artificial neural network-based response surface method was discussed. The method was used to investigate the seismic reliability of the crucial section of the tower of the Pearl River Huangpu Bridge under the ground motion excitation.