Analysis of large scale discrete dislocation data requires the characterisation of complex dislocation networks by suitable average quantities. In the current work, we suggest dislocation alignment tensors and closely related curvature tensors as easily extractable and intelligible measures of geometrical and topological characteristics of dislocation distributions. We provide formulae for extracting these measures from discrete dislocation data based on straight segments. Examples for interpreting and visualising these measures are provided for a simple configuration and two more involved results from discrete dislocation simulations. We suggest the alignment and curvature tensors for wider use in plasticity research.
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@article{CRPHYS_2021__22_S3_249_0,
author = {Benedikt Weger and Satyapriya Gupta and Thomas Hochrainer},
title = {Analysing discrete dislocation data using alignment and curvature tensors},
journal = {Comptes Rendus. Physique},
pages = {249--266},
publisher = {Acad\'emie des sciences, Paris},
volume = {22},
number = {S3},
year = {2021},
doi = {10.5802/crphys.60},
language = {en},
}
TY - JOUR AU - Benedikt Weger AU - Satyapriya Gupta AU - Thomas Hochrainer TI - Analysing discrete dislocation data using alignment and curvature tensors JO - Comptes Rendus. Physique PY - 2021 SP - 249 EP - 266 VL - 22 IS - S3 PB - Académie des sciences, Paris DO - 10.5802/crphys.60 LA - en ID - CRPHYS_2021__22_S3_249_0 ER -
%0 Journal Article %A Benedikt Weger %A Satyapriya Gupta %A Thomas Hochrainer %T Analysing discrete dislocation data using alignment and curvature tensors %J Comptes Rendus. Physique %D 2021 %P 249-266 %V 22 %N S3 %I Académie des sciences, Paris %R 10.5802/crphys.60 %G en %F CRPHYS_2021__22_S3_249_0
Benedikt Weger; Satyapriya Gupta; Thomas Hochrainer. Analysing discrete dislocation data using alignment and curvature tensors. Comptes Rendus. Physique, Volume 22 (2021) no. S3, pp. 249-266. doi : 10.5802/crphys.60. https://comptes-rendus.academie-sciences.fr/physique/articles/10.5802/crphys.60/
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