Reliability analysis of randomly excited FE modelled structures with interval mass and stiffness via sensitivity analysis. (15th January 2022)

• Record Type: Journal Article
• Authors: Sofi, Alba; Giunta, Filippo; Muscolino, Giuseppe
• Is Part Of: Mechanical systems and signal processing. Volume 163(2022)
• Publication Date: 2022-01-15
• Subjects: Random excitation -- Uncertain parameters -- Interval reliability function -- Interval analysis -- Sensitivity analysis; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2021.107990
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: Interval first-passage reliability analysis of FE modelled structures is performed. Uncertainties affecting both the mass and stiffness matrices are considered. A sensitivity-based procedure for evaluating the bounds of the reliability function is proposed. Only two stochastic analyses of the randomly excited structure are requested. Excellent agreement between the proposed procedure and the vertex method is found. Abstract: The present study focuses on reliability analysis of linear discretized structures with uncertain mass and stiffness parameters subjected to stationary Gaussian multi-correlated random excitation. Under the assumption that available information on the uncertain parameters is poor or incomplete, the interval model of uncertainty is adopted. The reliability function for the extreme value stress process is evaluated in the framework of the first-passage theory. Such a function turns out to have an interval nature due to the uncertainty affecting structural parameters. The aim of the analysis is the evaluation of the bounds of the interval reliability function which provide a range of structural performance useful for design purposes. To limit detrimental overestimation caused by the dependency phenomenon, a sensitivity-based procedure is applied. The main advantage of this approach is the capability of providing appropriate combinations of the endpoints of the uncertain parameters which yield accurate estimates of the bounds of the interval reliability function for the extreme value stress process as long as monotonic problems are dealt with. Two case studies are analyzed to demonstrate the accuracy and efficiency of the presented method.