期刊
INTERNATIONAL JOURNAL FOR COMPUTATIONAL METHODS IN ENGINEERING SCIENCE & MECHANICS
卷 9, 期 6, 页码 342-357出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/15502280802363035
关键词
Structural Reliability; High Dimensional Model Representation; Most Probable Point; Limit State/Performance Function; Fast Fourier Transform; Failure Probability
类别
资金
- Board of Research in Nuclear Sciences, India [2004/36/39-BRNS/2332]
This paper presents an efficient probabilistic analysis method for predicting component reliability of structural/mechanical systems subject to random loads, material properties, and geometry. The proposed method involves High Dimensional Model Representation (HDMR) for the limit state/performance function approximation and fast Fourier transform for solving the convolution integral. The limit state/performance function approximation is obtained by linear and quadratic approximations of the firstorder HDMR component functions at most probable point. In the proposed method, efforts are required in evaluating conditional responses at a selected input determined by sample points, as compared to full- scale simulation methods. Therefore, the proposed technique estimates the failure probability accurately with significantly less computational effort compared to the direct Monte Carlo simulation. The methodology developed is applicable for structural reliability estimation involving any number of random variableswith any kind of distribution. The accuracy and efficiency of the proposed method is demonstrated through five examples involving explicit/implicit performance functions.
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