Li, Z. and Ince, A. (2019) A unified frequency domain fatigue damage modeling approach for random-on-random spectrum. International Journal of Fatigue . ISSN 01421123 (In Press)
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Official URL: http://dx.doi.org/10.1016/j.ijfatigue.2019.02.032
Abstract
Current frequency domain damage models only deal with stationary random loadings (stationary Power Spectral Density), but many machine components, such as jet engines, rotating machines, and tracked vehicles are subjected to evolutionary i.e. time-dependent PSD conditions under real service loadings. An innovative fatigue damage modeling approach is proposed to predict fatigue damage of structures under complex evolutionary PSD loading conditions where the topology of PSD function changes with time. This new approach is based on a novel modeling framework that the evolutionary PSD response of a structure can be decomposed into a finite number of discrete PSD functions. Each PSD function can be split into narrow frequency bands so that each of narrowbands can be associated with Rayleigh distribution of stress cycles. Fatigue damage can then be predicted by summing up damages for each individual band and each discrete PSD function on the basis of a damage accumulation rule. The proposed modeling approach is numerically and experimentally validated by a finite element method and experiments. The proposed modeling approach provides a more efficient and accurate modeling technique for fatigue damage assessment of engineering structural components under very complex random loadings.
| Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical, Industrial and Aerospace Engineering |
|---|---|
| Item Type: | Article |
| Refereed: | Yes |
| Authors: | Li, Z. and Ince, A. |
| Journal or Publication: | International Journal of Fatigue |
| Date: | 23 February 2019 |
| Digital Object Identifier (DOI): | 10.1016/j.ijfatigue.2019.02.032 |
| Keywords: | Fatigue failure; accelerated test; power spectral density; frequency domain; random loading |
| ID Code: | 985041 |
| Deposited By: | Monique Lane |
| Deposited On: | 01 Mar 2019 21:01 |
| Last Modified: | 22 Feb 2021 02:00 |
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