Open Access

ARTICLE

A Moving Kriging Interpolation Response Surface Method for Structural Reliability Analysis

W. Zhao^1,2, J.K. Liu³, X.Y. Li², Q.W. Yang⁴, Y.Y. Chen⁵

1 Corresponding author, E-mail: zhaoweiyc@gmail.com,tel:+862085220476-2009
2 Key Laboratory of Disaster Forecast and Control in Engineering, Ministry of Education of China, Jinan University, Guangzhou 510632, China.
3 Department of Mechanics, Sun Yat-sen University, Guangzhou 510275, China.
4 Department of Civil Engineering, Shaoxing University, Shaoxing, 312000, China.
5 Key Laboratory of Eathquake Resistance, Eathquake Mitigation and Structural Safety, Ministry of Education of China, Guangzhou University, Guangzhou 510405 , China.

Computer Modeling in Engineering & Sciences 2013, 93(6), 469-488. https://doi.org/10.3970/cmes.2013.093.469

Abstract

In order to obtain reliable structural design, it is of extreme importance to evaluate the failure probability, safety levels of structure (reliability analysis) and the effect of a change in a variable parameter on structural safety (sensitivity analysis) when uncertainties are considered. With a computationally cheaper approximation of the limit state function, various response surface methods (RSMs) have emerged as a convenient tool to solve this especially for complex problems. However, the traditional RSMs may produce large errors in some conditions especially for those highly non-linear limit state functions. Instead of the traditional least squares approximation, in the present paper, a new RSM is proposed which employs moving Kriging interpolation, based on the axial experimental points selected from the region where the most probable failure point (MPFP) is likely to exist to construct the substitute response surface. The proposed method is illustrated by comparing with the results obtained from first order reliability method (FORM) and other conventional RSMs with reference to specific structural reliability analysis problems. The results show that the proposed method improves the accuracy of the reliability analysis with a reasonable computational cost, and could more quickly approach the exact solution.

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Keywords

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