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Proceedings 2018, 2(8), 504;

Identification and Prediction of Mixed-Mode Fatigue Crack Path in High Strength Low Alloy Steel

SIM vzw, Technologiepark 935, BE-9052 Zwijnaarde, Belgium
Soete Laboratory, Department of Electrical Energy, Systems and Automation, Ghent University, 9000 Ghent, Belgium
Presented at the 18th International Conference on Experimental Mechanics (ICEM18), Brussels, Belgium, 1–5 July 2018.
Author to whom correspondence should be addressed.
Published: 30 June 2018
PDF [1491 KB, uploaded 25 July 2018]


The trajectory of fatigue crack growth is influenced by many parameters and can be irregular due to changes in stress distribution or in material properties as the crack progresses. Images of the surface of a standardized test specimen can be used to visualize the crack trajectory in a non-destructive way. Accurately identifying the location of the crack tip, however, is challenging and requires devoted image postprocessing. In this respect, digital image correlation allows to obtain full field displacement and strain fields by analysing changes of digital images of the same sample at different stages of loading. This information can be used for the purpose of crack tip tracking. This paper presents a combined experimental-numerical study of detection and prediction of fatigue crack propagation path by means of digital image correlation (DIC) and the extended finite element method (X-FEM). Experimental validation and analyses are carried out on a modified C(T) specimen in which a curved crack trajectory is triggered by introducing mixed-mode (tension + shear) loading. The developed tools are used for validating an automated framework for crack propagation prediction.
Keywords: fatigue crack propagation; digital image correlation; X-FEM; crack tip fatigue crack propagation; digital image correlation; X-FEM; crack tip
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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Zhang, J.; Kiekens, C.; Hertelé, S.; Waele, W.D. Identification and Prediction of Mixed-Mode Fatigue Crack Path in High Strength Low Alloy Steel. Proceedings 2018, 2, 504.

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