Issue |
MATEC Web Conf.
Volume 157, 2018
Machine Modelling and Simulations 2017 (MMS 2017)
|
|
---|---|---|
Article Number | 02024 | |
Number of page(s) | 11 | |
Section | Modelling and simulation, structural optimization | |
DOI | https://doi.org/10.1051/matecconf/201815702024 | |
Published online | 14 March 2018 |
Fatigue life prediction of mechanical structures under stochastic loading
University of Žilina, Faculty of Security Engineering, Department of technical sciences and informatics, 1. mája 32, Žilina, Slovakia
* Corresponding author: Bohus.Leitner@fbi.uniza.sk
Problems of fatigue life prediction of materials and structures are discussed in the paper. Service loading is assumed as a continuous loading process with possible discontinuous events, which are caused by various operating conditions. The damage in a material is due to a cumulative degradation process. The damaging process is then represented either by rain-flow matrices or by a fatigue damage function which is derived using some hypothesis of a fatigue failure criterion. Presented theoretical procedure enables a very effective estimation of a service life and/or reliable evaluation of residual life of any structures under various types of loading and environmental conditions. This approach creates a good basis for powerful expert systems in structural and mechanical engineering. The aim of the paper is to present briefly some results of analysis of load-bearing steel structure loads of special railway crane PKP 25/20i which was utilized in some specific ad relatively hard operating conditions. Virtual models of the structure were being used in an analysis of acting working dynamics loads influence to be able to forecast fatigue life of load-bearing of the crane jib.
Key words: mechanical structures / stochastic loading / material degradation / fatigue damage / measurement of dynamics loads / fatigue life prediction / load-bearing structure
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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