Dynamic response and reliability analyses of non-linear structures driven by non-stationary non-Gaussian stochastic ground motions. (1st October 2022)

• Record Type: Journal Article
• Authors: Xu, Jun; Li, Yang; Mao, Jian-feng; Yu, Zhi-wu; Tan, Sui
• Is Part Of: Engineering structures. Volume 268(2022)
• Publication Date: 2022-10-01
• Subjects: Non-Gaussian -- Translation process -- Clustering method -- High-dimensional points selection -- Spectral representation method -- Probability density evolution method; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2022.114689
• Languages: English
• ISSNs: 0141-0296

Abstract

Abstract: In this paper, stochastic dynamic response and reliability assessment of non-linear structures driven by non-stationary non-Gaussian ground motions are investigated. First, the non-stationary non-Gaussian ground motions are simulated by using the translation process theory. To circumvent the problem of a large number of iterations, an improved upgrading model is developed to obtain a power spectral density which is compatible with the target non-Gaussian probability distribution and is as close as possible to the target non-Gaussian power spectral density. To conduct stochastic dynamic response and reliability analyses of non-linear structures driven by non-stationary non-Gaussian ground motions, the probability density evolution method is employed, whereby a new high-dimensional points selection strategy based on the clustering algorithm is put forward. The new strategy of points selection is quite flexible and simple while taking into account both efficiency and accuracy. The efficacy and applicability of the proposed method are verified through a numerical example and a practical engineering example, in which the influence of non-Gaussianity on the probabilistic seismic response and reliability of the structure is discussed. Highlights: Nonstationary non-Gaussian ground motions are simulated with accuracy. High-dimensional points selection is performed based on the clustering method. Probabilistic dynamic analysis of nonlinear structures are carried out based on PDEM. Numerical examples verify the efficacy and applicability of the proposed method.