A novel structural reliability analysis method via improved maximum entropy method based on nonlinear mapping and sparse grid numerical integration. (1st November 2019)

• Record Type: Journal Article
• Authors: He, Wanxin; Zeng, Yan; Li, Gang
• Is Part Of: Mechanical systems and signal processing. Volume 133(2019)
• Publication Date: 2019-11-01
• Subjects: Nonlinear transformation -- Cauchy distribution -- Maximum entropy method -- Structural reliability analysis -- Sparse grid numerical integration -- Statistical moment evaluation; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2019.106247
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: An accurate and stable approach is proposed for reliability analysis. The proposed method is an improved maximum entropy method. An improved sparse grid numerical integration is developed to evaluate the statistical moments. Numerical examples are investigated to validate the proposed method. Abstract: This paper proposes an improved maximum entropy method for reliability analysis (i-MEM), in which the limit state function is transformed by a nonlinear mapping to predict the failure probability accurately. Through the nonlinear mapping, more statistical information can be obtained by the first-four statistical moments, and the truncation error originating from numerical integration is solved by the bounded limit state function after the nonlinear mapping, therefore the i-MEM can capture the tail information of the real probability distribution. In order to calculate the statistical moments in i-MEM with accuracy and efficiency, an improved sparse grid numerical integration method (i-SGNI) is developed on the basis of the normalized moment-based quadrature rule. Combining the i-MEM and i-SGNI, a novel reliability analysis method is proposed. To illustrate the accuracy, efficiency and numerical stability of the proposed method, six numerical examples and one engineering example are presented, compared with some common reliability analysis methods. The results show that the proposed method, with the combination of i-MEM and i-SGNI, can achieve a good balance between accuracy and efficiency for structural reliability analysis.