Digital image correlation at high temperatures for fatigue and phase transformation studies

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Holzweissig, M.J.; Kanagarajah, P.; Maier, H.J.: Digital image correlation at high temperatures for fatigue and phase transformation studies. In: Journal of Strain Analysis for Engineering Design 49 (2014), Nr. 4, S. 204-211. DOI: https://doi.org/10.1177/0309324713498737

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Abstract: 
In this study, digital image correlation was used for two widely different cases to assess the potential and the limitations of the technique for applications at high temperatures. Specifically, digital image correlation was employed in high-temperature low-cycle fatigue experiments in a nickel-based superalloy and in phase transformation experiments conducted on bainitic steel in order to shed light on the microstructural processes. Depending on the type of experiments, the microstructure was characterized prior to the experiments (fatigue) or after the experiments (phase transformation). In the fatigue experiments, it was found that the features dominating damage evolution were the dendrites resulting from the solidification of the cast material. In the phase transformation experiments, variant selection is active when stresses are superimposed during the phase transformation process, which resulted in the evolution of transformation plasticity strains. Thereby, mainly the bainite variants oriented along the [101], [201] and [121] directions were observed to grow parallel to the loading axis, which in turn led to transformation plasticity strains. For validation of the digital image correlation data, average strains were calculated for the surface area probed and compared to strain values obtained by conventional extensometry. In all cases studied, the correlation was satisfactory, indicating that digital image correlation can provide for additional insight into processes active at the micro level. © 2013 IMechE.
License of this version: Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. Dieser Beitrag ist aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.
Document Type: article
Publishing status: publishedVersion
Issue Date: 2014
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
total perc.
1 image of flag of Germany Germany 58 74.36%
2 image of flag of France France 4 5.13%
3 image of flag of United Kingdom United Kingdom 3 3.85%
4 image of flag of China China 3 3.85%
5 image of flag of United States United States 2 2.56%
6 image of flag of Ukraine Ukraine 2 2.56%
7 image of flag of Norway Norway 2 2.56%
8 image of flag of India India 2 2.56%
9 image of flag of Korea, Republic of Korea, Republic of 1 1.28%
10 image of flag of Japan Japan 1 1.28%

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