Ayse S. Giz, Ata Mugan

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In fatigue analyses and structural health monitoring applications, frequency domain theoretical fatigue life estimation models work best on Gaussian data, while many natural occurrences that influence the stress history have non-Gaussian properties. In order to handle realistic stress data, various transformations from non-Gaussian to Gaussian distributions are used. In this study, two transformation methods namely moment based Hermite polynomial model and Johnson transformation model were examined that have both a non-Gaussian to Gaussian transformation and a Gaussian to non-Gaussian transformation. These established transformation methods were compared for their distortion with reference to increasingly leptokurtic behavior and skewness. Normally distributed Gaussian data were distorted to a non-Gaussian form and then re-stored back to Gaussian form using parameters estimated from the non-Gaussian data were compared according to their kurtosis and skewness values. It was found that the restored da-ta contains significant deviation from Gaussian form the deviation depending on the distortion in the initial transformation and the deviations are more prominent in the Hermite Polynomial Transformation. These deviations in turn affect fatigue life estimations.

Orijinal dilİngilizce
DergiCOMPDYN Proceedings
Yayın durumuYayınlandı - 2023
Etkinlik9th ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, COMPDYN 2023 - Athens, Greece
Süre: 12 Haz 202314 Haz 2023

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© 2023 COMPDYN Proceedings. All rights reserved


This study is supported by the Scientific and Technological Research Council of Türkiye (TUBITAK) under the grant number 120M214

FinansörlerFinansör numarası
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu120M214

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