Time-varying response surface method for high-temperature structural reliability analysis using copula

Author(s):  
Jian-Chun Zhang ◽  
Xiao-Bing Ma ◽  
Yu Zhao
2013 ◽  
Vol 838-841 ◽  
pp. 360-363 ◽  
Author(s):  
Li Rong Sha ◽  
Yue Yang

In order to predict the failure probability of a complicated structure, the structural responses usually need to be predicted by a numerical procedure, such as FEM method. The response surface method could be used to reduce the computational effort required for reliability analysis. However the conventional response surface method is still time consuming when the number of random variables is large. In this paper, a Fourier orthogonal neural network (FONN)-based response surface method is proposed. In this method, the relationship between the random variables and structural responses is established using FONN models. Then the FONN model is connected to the first order and second moment method (FORM) to predict the failure probability. Numerical example result shows that the proposed approach is efficient and accurate, and is applicable to structural reliability analysis.


2013 ◽  
Vol 712-715 ◽  
pp. 1506-1509 ◽  
Author(s):  
Guang Bo Li ◽  
Guang Wei Meng ◽  
Feng Li ◽  
Li Ming Zhou

The response surface method is adopted to analyze the structural reliability. This paper presents a new response surface method with the uniform design method to predict the failure probability of structures. It is the response surface method based on Fourier orthogonal basis function (RSM-Fourier). To reduce computational costs in structural reliability analysis, approximate Fourier response surface functions for reliability assessment have been suggested. The method involves the selection of training datasets for establishing a model by the uniform design points, the approximation of the limit state function by the trained model and the estimation of the failure probability using first-order reliability method (FORM). The proposed method is applied to examples, compared with other methods to demonstrate its effectiveness.


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