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A Gaussian process-based response surface method for structural reliability analysis
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 Title & Authors
A Gaussian process-based response surface method for structural reliability analysis
Su, Guoshao; Jiang, Jianqing; Yu, Bo; Xiao, Yilong;
 Abstract
A first-order moment method (FORM) reliability analysis is commonly used for structural stability analysis. It requires the values and partial derivatives of the performance to function with respect to the random variables for the design. These calculations can be cumbersome when the performance functions are implicit. A Gaussian process (GP)-based response surface is adopted in this study to approximate the limit state function. By using a trained GP model, a large number of values and partial derivatives of the performance functions can be obtained for conventional reliability analysis with a FORM, thereby reducing the number of stability analysis calculations. This dynamic renewed knowledge source can provide great assistance in improving the predictive capacity of GP during the iterative process, particularly from the view of machine learning. An iterative algorithm is therefore proposed to improve the precision of GP approximation around the design point by constantly adding new design points to the initial training set. Examples are provided to illustrate the GP-based response surface for both structural and non-structural reliability analyses. The results show that the proposed approach is applicable to structural reliability analyses that involve implicit performance functions and structural response evaluations that entail time-consuming finite element analyses.
 Keywords
first-order moment method;structural reliability;response surface method;Gaussian process;
 Language
English
 Cited by
1.
A response surface method based on sub-region of interest for structural reliability analysis,;;;

Structural Engineering and Mechanics, 2016. vol.57. 4, pp.587-602 crossref(new window)
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