scholarly journals Identification of a crack propagation law by digital image correlation

2012 ◽  
Vol 36 (1) ◽  
pp. 146-154 ◽  
Author(s):  
Florent Mathieu ◽  
François Hild ◽  
Stéphane Roux
Keyword(s):  
Digital Image Correlation ◽  
Crack Propagation ◽  
Digital Image ◽  
Image Correlation ◽  
Propagation Law

Crack propagation in a PVA dual-crosslink hydrogel: Crack tip fields measured using digital image correlation

2019 ◽  
Vol 138 ◽  
pp. 103158 ◽  
Author(s):  
Mincong Liu ◽  
Jingyi Guo ◽  
Zhilong Li ◽  
Chung-Yuen Hui ◽  
Alan T. Zehnder
Keyword(s):  
Digital Image Correlation ◽  
Crack Propagation ◽  
Digital Image ◽  
Crack Tip ◽  
Image Correlation ◽  
Crack Tip Fields

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

Proceedings ◽  
2018 ◽  
Vol 2 (8) ◽  
pp. 504
Author(s):  
Jie Zhang ◽  
Cedric Kiekens ◽  
Stijn Hertelé ◽  
Wim De Waele
Keyword(s):  
Fatigue Crack ◽  
Digital Image Correlation ◽  
Crack Propagation ◽  
Digital Image ◽  
Mixed Mode ◽  
Standardized Test ◽  
Crack Tip ◽  
Shear Loading ◽  
Image Correlation ◽  
Crack Trajectory

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.

Investigation of the Crack Propagation Behavior of the Multiwalled Carbon Nanotube/Graphite/Natural Rubber Hybrid Nanocomposites Using Digital Image Correlation Technique

2019 ◽  
Vol 14 (12) ◽  
pp. 1766-1770
Author(s):  
Hasan Kasim ◽  
Ahmad Naser Aldeen ◽  
Yücel Can ◽  
Murat Yazici
Keyword(s):  
Electrical Conductivity ◽  
Carbon Nanotube ◽  
Digital Image Correlation ◽  
Crack Propagation ◽  
Natural Rubber ◽  
Digital Image ◽  
Multiwalled Carbon Nanotube ◽  
Hybrid Nanocomposites ◽  
Image Correlation ◽  
Multiwalled Carbon

In the presented study, a hybrid Natural Rubber (NR) based semiconductive nanocomposites was examined to obtain better electrical and mechanical properties. The hybrid nanocomposite produced by incorporation of the Multiwalled Carbon Nanotube (MWCNT) and graphite nanoparticles into the NR. The conventional curing additives also included in the compound. A functionalized MWCNT (1, 2 and 3 phr's) with 3 phr graphite quotas were studied to produce the NR nanocomposites. The MWCNT/Graphite and NR mixed homogeneously to advance the interfacial interaction with the matrix. The graphite nano-particulates added to obtain 3D electrical connectivity network in the hybrid nanocomposites by becoming bridging points between multiwalled carbon nanotubes. Nanocomposites were produced as 3 mm sheets in a steel mold by vulcanizing at 165 °C for 10 min under pressure. The single-edge notched tension specimens were subjected to estimate crack propagation and electrical resistance relation. Digital Image Correlation (DIC) technique was used to observe the crack resistivity function. The results evaluated to clarify the relationship between crack length, MWCNT filler ratio, and electrical conductivity properties. MWCNTs are generally preferred as the reinforcements for their very high aspect ratio and excellent specific surface area properties. However, the electrical conductivity of the nanocomposites is owing to the constitution of a continuous conductive 3D network of MWCNT and Graphite in the NR matrix.

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