A nonparametric seismic reliability analysis method based on Bayesian compressive sensing – Stochastic harmonic function method and probability density evolution method. (1st August 2023)

• Record Type: Journal Article
• Authors: He, Jingran; Gao, Ruofan; Zhou, Hao
• Is Part Of: Mechanical systems and signal processing. Volume 196(2023)
• Publication Date: 2023-08-01
• Subjects: Seismic reliability -- Conditional random field -- Probability density evolution method -- Stochastic finite element method; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2023.110339
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: In engineering practice, the evaluation of seismic reliability of high-rise reinforced concrete structure relies on the probabilistic modelling of material properties. However, the measured data of material parameters in engineering practice is usually inadequate to determine the probability model accurately, especially for the problems involving spatial variability. Traditional parametric reliability analysis methods can be biased for this kind of problem. Therefore, a nonparametric seismic reliability analysis method is proposed based on the Bayesian compressive sensing – stochastic harmonic function method and the probability density evolution method. In this method, the conditional random fields are generated and applied to represent material properties of concrete. As a result, the seismic reliability of a high-rise reinforced concrete shear wall model structure is analyzed using the probability density evolution method.