Identify the stochastic dynamic load on a complex uncertain structural system. (15th January 2021)

• Record Type: Journal Article
• Authors: Wu, Shaoqing; Zheng, Yi; Sun, Yanwei; Fei, Qingguo
• Is Part Of: Mechanical systems and signal processing. Volume 147(2021)
• Publication Date: 2021-01-15
• Subjects: Stochastic load identification -- Uncertain structural system -- Taylor expansion -- Polynomial chaos expansion -- Complex structure application; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2020.107114
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A Modified Perturbation Stochastic Finite Element Model (MPSFEM) is proposed. A Stochastic Load Identification (SLI) algorithm based on MPSFEM is developed. A standard SLI framework for complex uncertain structures is developed. Abstract: Estimating the statistics of stochastic dynamic forces applied on engineering structures is a very important task for structural safety evaluation. A novel load identification method capable of identifying the stochastic Gaussian excitation on uncertain engineering structures is proposed. The uncertain system parameters are assuming as Gaussian random variables. Stochastic Green's function is adopted to represent the relationship between the stochastic structural response and the stochastic dynamic load. The stochastic Green's function and the stochastic structural response are respectively represented by the Taylor expansion and the Polynomial Chaos expansion. With the known system parameters, the problem of stochastic load identification on uncertain structure can be transformed into the problem of stochastic load identification on deterministic structure. The statistics of the dynamic load can further be determined according to the covariance kernel of the structural response only due to stochastic excitation. Numerical simulation on a simple plane truss structure subjects to a stochastic force is conducted to verify the proposed method. To apply the proposed algorithm on complex engineering structures, a standard framework based on MATLAB and ABAQUS is developed for the first time to identify the stochastic base-excitation applied on a space satellite model with local uncertainty. Results show that the proposed method can effectively estimate the statistics of stochastic forces on complex uncertain structures.