A Multi-modal Data Merging Framework for Correlative Investigation of Strain Localization in Three Dimensions
A multi-modal data-merging framework that enables the reconstruction of slip bands in three dimensions over millimeter-scale fields of view is presented. The technique combines 3D electron back-scattered diffraction (EBSD) measurements with high-resolution digital image correlation (HR-DIC) informat...
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Veröffentlicht in: | JOM (1989) 2021-11, Vol.73 (11), p.3263-3271 |
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creator | Charpagne, M.A. Stinville, J. C. Polonsky, A. T. Echlin, M. P. Pollock, T. M. |
description | A multi-modal data-merging framework that enables the reconstruction of slip bands in three dimensions over millimeter-scale fields of view is presented. The technique combines 3D electron back-scattered diffraction (EBSD) measurements with high-resolution digital image correlation (HR-DIC) information collected in the scanning electron microscope (SEM). A typical merging workflow involves the segmentation of features within the strain field (slip bands, deformation twins) and the microstructure (grains), alignment of datasets and the projection of slip bands into the 3D microstructure, using the knowledge of the local crystallographic orientation. This method is demonstrated in two materials: a face-centered cubic (FCC) nickel-base superalloy and hexagonal close-packed (HCP) titanium alloy. |
doi_str_mv | 10.1007/s11837-021-04894-6 |
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subjects | Advances in Multi-modal Characterization of Structural Materials Automation Chemistry/Food Science Crystallography Data collection Datasets Deformation Digital imaging Earth Sciences Edge dislocations Engineering Environment Face centered cubic lattice Image reconstruction Image resolution Image segmentation Localization Microstructure Modal data Nickel base alloys Physics Software Strain analysis Strain localization Superalloys Titanium alloys Titanium base alloys Tomography Workflow |
title | A Multi-modal Data Merging Framework for Correlative Investigation of Strain Localization in Three Dimensions |
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