Analysing discrete dislocation data using alignment and curvature tensors

Benedikt Weger, Satyapriya Gupta, Thomas Hochrainer*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Pages (from-to)249-266
Number of pages18
JournalComptes Rendus Physique
Volume22
Issue numberS3
DOIs
Publication statusPublished - 2021

Keywords

  • Data analysis
  • Discrete dislocation simulations
  • Dislocation alignment tensors
  • Dislocation curvature tensors
  • Microstructure
  • Plasticity

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Fingerprint

Dive into the research topics of 'Analysing discrete dislocation data using alignment and curvature tensors'. Together they form a unique fingerprint.

Cite this