Structural reliability analysis using imprecise evolutionary power spectral density functions

verfasst von: Marco Behrendt, Chao Dang, Matthias G.R. Faes, Marcos A. Valdebenito, Michael Beer
Abstract: Buildings and structures in many regions of the world are exposed to environmental factors that can cause damage or failure, making it essential to model these factors accurately in engineering. Stochastic dynamics are crucial for modelling environmental processes, such as earthquake ground motions and wind loads, which can be characterised by a power spectral density (PSD) function that determines the dominant frequencies and corresponding amplitudes of the process. However, when generating a load model described by a PSD function, uncertainties in the processes must be taken into account, which makes a reliable estimation of the PSD function challenging, especially with only limited data available. This study employs the recently developed imprecise PSD function by using a radial basis function network to optimise data-enclosing bounds that produce an interval-valued PSD function. With this approach, a data set in the frequency domain can be bounded for uncertainty quantification. The method described in this work consists of optimising best-case and worst-case PSD functions within the bounds, which are transformed into a separable evolutionary PSD function. The reliability of structures is determined by an upper and lower failure probability, taking into account the present uncertainties. Advanced interval propagation schemes are linked to the imprecise PSD function to determine the failure probabilities efficiently. The method is illustrated by means of three numerical examples.
Organisationseinheit(en): Institut für Risiko und Zuverlässigkeit
Externe Organisation(en): Technische Universität Dortmund
The University of Liverpool
Tongji University
Typ: Konferenzaufsatz in Fachzeitschrift
Journal: Journal of Physics: Conference Series
Band: 2647
Anzahl der Seiten: 10
ISSN: 1742-6588
Publikationsdatum: 2024
Publikationsstatus: Veröffentlicht
Peer-reviewed: Ja
ASJC Scopus Sachgebiete: Allgemeine Physik und Astronomie
Elektronische Version(en): https://doi.org/10.1088/1742-6596/2647/6/062003 (Zugang: Offen)

BibTeX

@article{853e9bc6f2514aa9a2edb858eedfa331,
title = "Structural reliability analysis using imprecise evolutionary power spectral density functions",
abstract = "Buildings and structures in many regions of the world are exposed to environmental factors that can cause damage or failure, making it essential to model these factors accurately in engineering. Stochastic dynamics are crucial for modelling environmental processes, such as earthquake ground motions and wind loads, which can be characterised by a power spectral density (PSD) function that determines the dominant frequencies and corresponding amplitudes of the process. However, when generating a load model described by a PSD function, uncertainties in the processes must be taken into account, which makes a reliable estimation of the PSD function challenging, especially with only limited data available. This study employs the recently developed imprecise PSD function by using a radial basis function network to optimise data-enclosing bounds that produce an interval-valued PSD function. With this approach, a data set in the frequency domain can be bounded for uncertainty quantification. The method described in this work consists of optimising best-case and worst-case PSD functions within the bounds, which are transformed into a separable evolutionary PSD function. The reliability of structures is determined by an upper and lower failure probability, taking into account the present uncertainties. Advanced interval propagation schemes are linked to the imprecise PSD function to determine the failure probabilities efficiently. The method is illustrated by means of three numerical examples.",
author = "Marco Behrendt and Chao Dang and Faes, {Matthias G.R.} and Valdebenito, {Marcos A.} and Michael Beer",
note = "Publisher Copyright: {\textcopyright} Published under licence by IOP Publishing Ltd.; 12th International Conference on Structural Dynamics, EURODYN 2023 ; Conference date: 02-07-2023 Through 05-07-2023",
year = "2024",
doi = "10.1088/1742-6596/2647/6/062003",
language = "English",
volume = "2647",
journal = "Journal of Physics: Conference Series",
issn = "1742-6588",
publisher = "IOP Publishing Ltd.",
number = "6",
}