Automated and quantitative analysis of plastic strain localization via multi-modal data recombination

M. A. Charpagne, J. C. Stinville, P. G. Callahan, D. Texier, Z. Chen, P. Villechaise, V. Valle, T. M. Pollock

Research output: Contribution to journalArticlepeer-review


A multi-modal data recombination method that enables the automated, quantitative and statistical assessment of strain localization as a function of the microstructure is presented. It consists of merging high resolution digital image correlation (HR-DIC) datasets collected in a scanning electron microscope (SEM), with crystallographic data obtained from electron back-scattered diffraction (EBSD). As the data is typically gathered over large areas (about 1 mm2), this method enables the quantitative assessment of plastic strain localization over hundreds to thousands of grains, yet with a spatial resolution of tens of nanometers. The data is treated in a hierarchical manner so that strain localization phenomena can be studied as a function of phases, texture and grain orientation. The use of discontinuity tolerant DIC codes, such as Heaviside DIC (H-DIC) in the present case, enables identification the active slip system associated with slip band discontinuities. Analyses conducted over thousands of bands in thousands of grains enable the quantitative assessment of fundamental plasticity laws. The capabilities of this method are shown through application to Ti-6Al-4V and Inconel 718 alloys.

Original languageEnglish (US)
Article number110245
JournalMaterials Characterization
StatePublished - May 2020
Externally publishedYes


  • Discontinuities measurements
  • High resolution digital image correlation
  • Multi-modal data
  • Scanning electron microscopy digital image correlation
  • Slip bands
  • Strain localization

ASJC Scopus subject areas

  • General Materials Science
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering


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