Hybrid multiplicative dimension reduction method for uncertainty analysis of engineering structures

Haihe Li, Pan Wang, Qi Chang, Changcong Zhou, Zhufeng Yue

科研成果: 期刊稿件文章同行评审

3 引用 (Scopus)

摘要

For uncertainty analysis of high-dimensional complex engineering problems, this article proposes a hybrid multiplicative dimension reduction method based on the existent multiplicative dimension reduction method. It uses the multiplicative dimension reduction method to approximate the original high-dimensional performance function which is sufficiently smooth and has a small high-order derivative as the product of a series of one-dimensional functions, and then uses this approximation to calculate the statistical moments of the function. Then the variance-based global sensitivity index is employed to identify the important variables, and the identified important variables are subjected to bivariate decomposition approximation. Combined with the univariate multiplicative dimension reduction method, the hybrid decomposition approximation is obtained. Compared with the existing method, the proposed method is more accurate than the univariate decomposition approximation when used for uncertainty analysis of engineering models and needs less computational efforts than the bivariate decomposition. In the end, a numerical example and two engineering applications are tested to verify the effectiveness of the proposed method.

源语言英语
页(从-至)144-155
页数12
期刊Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
235
1
DOI
出版状态已出版 - 2月 2021

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