Data-mining of dislocation microstructures: Concepts for coarse-graining of internal energies

Hengxu Song, Nina Gunkelmann, Giacomo Po, Stefan Sandfeld

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Continuum models of dislocation plasticity require constitutive closure assumptions, e.g., by relating details of the dislocation microstructure to energy densities. Currently, there is no systematic way for deriving or extracting such information from reference simulations, such as discrete dislocation dynamics (DDD) or molecular dynamics. Here, a novel data-mining approach is proposed through which energy density data from systems of discrete dislocations can be extracted. Our approach relies on a systematic and controlled coarse-graining process and thereby is consistent with the length scale of interest. For data-mining, a range of different dislocation microstructures that were generated from 2D and 3D DDD simulations, are used. The analyses of the data sets result in energy density formulations as a function of various dislocation density fields. The proposed approach solves the long-standing problem of voxel-size dependent energy calculation during coarse graining of dislocation microstructures. Thus, it is crucial for any continuum dislocation dynamics simulation.

Original languageEnglish (US)
Article number035005
JournalModelling and Simulation in Materials Science and Engineering
Issue number3
StatePublished - Apr 2021


  • coarse graining
  • defect energy
  • dislocation dynamics
  • dislocation plasticity
  • microstructure

ASJC Scopus subject areas

  • Modeling and Simulation
  • Materials Science(all)
  • Condensed Matter Physics
  • Mechanics of Materials
  • Computer Science Applications


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