A new artificial neural network-based response surface method for structural reliability analysis

2008 ◽  
Vol 23 (1) ◽  
pp. 51-63 ◽  
Author(s):  
Jin Cheng ◽  
Q.S. Li ◽  
Ru-cheng Xiao
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Structural Reliability ◽  
Structural Reliability Analysis ◽  
Surface Method ◽  
Artificial Neural

Structural Reliability Analysis Using Fourier Orthogonal Neural Network Method

2013 ◽  
Vol 838-841 ◽  
pp. 360-363 ◽  
Author(s):  
Li Rong Sha ◽  
Yue Yang
Keyword(s):  
Neural Network ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Failure Probability ◽  
Structural Reliability ◽  
Random Variables ◽  
Structural Reliability Analysis ◽  
Surface Method ◽  
Structural Responses

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.

Structural Reliability Analysis Using Legendre Orthogonal Neural Network Method

2014 ◽  
Vol 501-504 ◽  
pp. 1077-1080
Author(s):  
Li Rong Sha ◽  
Yong Chun Shi
Keyword(s):  
Neural Network ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Failure Probability ◽  
Structural Reliability ◽  
Random Variables ◽  
Structural Reliability Analysis ◽  
Surface Method ◽  
Structural Responses

In order to predict the failure probability of a complicated structure, the structural responses usually need to be estimated by a numerical analysis such as finite element method. The response surface method could be used to reduce the computational effort required for reliability analysis when the performance functions are implicit. However the conventional response surface method is time-consuming or cumbersome if the number of random variables is large. This paper presents a Legendre orthogonal neural network (LONN)-based response surface method to predict the reliability of a structure. In this method, the relationship between the random variables and structural responses is established by a LONN model. Then the LONN model is connected to a reliability method, i.e. first-order reliability methods (FORM) to predict the failure probability of the structure. Numerical example has shown that the proposed approach is applicable to structural reliability analysis involving implicit performance functions.

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