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Structural Failure Probability Estimation Using HDMR and FFT
This paper presents a new and alternative method based on High Dimensional Model Representation (HDMR) and fast Fourier transform (FFT) to estimate the structural failure probability of structural systems subject to random loads, material properties and geometry. The proposed methodology is based on the limit state/performance function approximation and the convolution theorem to estimate the structural failure probability. The limit-state function is obtained by linear approximation of the first-order HDMR component functions at the most probable failure point, and the convolution integral is solved efficiently using the FFT technique. The proposed technique estimates the failure probability accurately with significantly less computational effort compared to the direct Monte Carlo simulation. The accuracy and efficiency of the proposed method is demonstrated through numerical examples involving implicit performance functions.
Structural Failure Probability Estimation Using HDMR and FFT
This paper presents a new and alternative method based on High Dimensional Model Representation (HDMR) and fast Fourier transform (FFT) to estimate the structural failure probability of structural systems subject to random loads, material properties and geometry. The proposed methodology is based on the limit state/performance function approximation and the convolution theorem to estimate the structural failure probability. The limit-state function is obtained by linear approximation of the first-order HDMR component functions at the most probable failure point, and the convolution integral is solved efficiently using the FFT technique. The proposed technique estimates the failure probability accurately with significantly less computational effort compared to the direct Monte Carlo simulation. The accuracy and efficiency of the proposed method is demonstrated through numerical examples involving implicit performance functions.
Structural Failure Probability Estimation Using HDMR and FFT
R. Chowdhury (author) / B. N. Rao (author)
2008
Article (Journal)
Electronic Resource
Unknown
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