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Civil-Comp Proceedings
ISSN 1759-3433 CCP: 104
PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo
Paper 104
Automated Measurement of Near-surface Plastic Shear Strain G. Trummer1, K. Six1, C. Marte1, A. Meierhofer1 and C. Sommitsch2
1Virtual Vehicle Research Center, Graz, Austria
G. Trummer, K. Six, C. Marte, A. Meierhofer, C. Sommitsch, "Automated Measurement of Near-surface Plastic Shear Strain", in J. Pombo, (Editor), "Proceedings of the Second International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Stirlingshire, UK, Paper 104, 2014. doi:10.4203/ccp.104.104
Keywords: rolling contact, twin disc tests, pearlitic steel, plasticity, plastic shear strain, image analysis.
Summary
Severe plastic shear deformation and high shear strain gradients are frequently observed
in the near-surface layer of tractive rolling contacts, such as in the contact
between wheels and rails in railway systems. The variation of plastic shear strain with
depth below the surface is important with respect to the interplay between rolling contact
fatigue crack initiation and wear. To determine the distribution of plastic shear
strain in a reliable and reproducible way from grayscale images of metallographic
sections, an automated measurement method has been developed. This method uses
local orientation information and local coherency information (a measure of structural
alignment) to estimate the mean shear strain as a function of depth. No special
specimen preparation is necessary prior to the measurement, such as the insertion of
artificial markers or the manufacturing of gratings.
The proposed method is validated by analyzing the orientation of inclusions, which
have been found in parts of specimens. These inclusions serve as natural markers for
the deformation process. The shear strain data from the inclusion analysis are in excellent
agreement with the mean shear strain results obtained with the proposed automated
method. The proposed method significantly reduces the measurement uncertainty
of orientation data, compared to manual local orientation measurements. This
is achieved by averaging orientation data over image areas. As an example of use, the
plastic shear strain distributions in the near-surface layer of Twin Disc test specimens
made of rail steel R260 and wheel steel R8 are analyzed with the proposed method.
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