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Appl. Sci. 2016, 6(4), 99; doi:10.3390/app6040099

Probabilistic Fatigue Life Prediction of Bridge Cables Based on Multiscaling and Mesoscopic Fracture Mechanics

1
Key Laboratory of Concrete and Prestressed Concrete Structure, Ministry of Education, Southeast University, 2 Sipailou, Nanjing 210096, China
2
School of Civil Engineering, Southeast University, 2 Sipailou, Nanjing 210096, China
*
Author to whom correspondence should be addressed.
Academic Editor: César M. A. Vasques
Received: 22 October 2015 / Revised: 21 February 2016 / Accepted: 9 March 2016 / Published: 7 April 2016
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Abstract

Fatigue fracture of bridge stay-cables is usually a multiscale process as the crack grows from micro-scale to macro-scale. Such a process, however, is highly uncertain. In order to make a rational prediction of the residual life of bridge cables, a probabilistic fatigue approach is proposed, based on a comprehensive vehicle load model, finite element analysis and multiscaling and mesoscopic fracture mechanics. Uncertainties in both material properties and external loads are considered. The proposed method is demonstrated through the fatigue life prediction of cables of the Runyang Cable-Stayed Bridge in China, and it is found that cables along the bridge spans may have significantly different fatigue lives, and due to the variability, some of them may have shorter lives than those as expected from the design. View Full-Text
Keywords: probabilistic analysis; fatigue crack growth; cable; steel wire; cable-stayed bridge; multiscaling; mesoscopic fracture mechanics probabilistic analysis; fatigue crack growth; cable; steel wire; cable-stayed bridge; multiscaling; mesoscopic fracture mechanics
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Liu, Z.; Guo, T.; Chai, S. Probabilistic Fatigue Life Prediction of Bridge Cables Based on Multiscaling and Mesoscopic Fracture Mechanics. Appl. Sci. 2016, 6, 99.

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