A new bivariate dimension reduction method for efficient structural reliability analysis

作者：Xu, Jun^*; Dang, Chao

来源：Mechanical Systems and Signal Processing, 2019, 115: 281-300.

DOI：10.1016/j.ymssp.2018.05.046

• Bivariate dimension reduction method
• Statistical moments
• High-order unscented transformation
• Shifted generalized lognormal distribution
• Structural reliability

This paper presents a new bivariate dimension reduction method (BDRM) for statistical moments evaluation and structural reliability analysis with accuracy and efficiency. A high-order unscented transformation (HUT) is introduced to evaluate the two-dimensional integrals involved in BDRM, and the free parameter involved in HUT is suggested. In this regard, the proposed BDRM can be formulated accordingly for statistical moments assessment. Then, the performance function's probability density PDF) is reconstructed by the shifted generalized lognormal distribution (SGLD) with the available statistical moments as constraints. Thus, the failure probability can be straightforwardly obtained by a simple integral over the PDF. The proposed method is verified by five numerical examples, including linear and non-linear, explicit and implicit performance functions. Besides, some other existing methods are also employed to demonstrate the advantages of the proposed method. It is found that the proposed method can keep the trade-off of accuracy and efficiency for structural reliability analysis.

• 出版日期2019-1-15
• 单位湖南大学