Combined near- and far-field high-energy diffraction microscopy dataset for Ti-7Al tensile specimen elastically loaded in situ View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-03-18

AUTHORS

Todd J. Turner, Paul A. Shade, Joel V. Bernier, Shiu Fai Li, Jay C. Schuren, Jonathan Lind, Ulrich Lienert, Peter Kenesei, Robert M. Suter, Basil Blank, Jonathan Almer

ABSTRACT

High-energy diffraction microscopy (HEDM) constitutes a suite of combined X-ray characterization methods, which hold the unique advantage of illuminating the microstructure and micromechanical state of a material during concurrent in situ mechanical deformation. The data generated from HEDM experiments provides a heretofore unrealized opportunity to validate meso-scale modeling techniques, such as crystal plasticity finite element modeling (CPFEM), by explicitly testing the accuracy of these models at the length scales where the models predict their response. Combining HEDM methods with in situ loading under known and controlled boundary conditions represents a significant challenge, inspiring the recent development of a new high-precision rotation and axial motion system for simultaneously rotating and axially loading a sample. In this paper, we describe the initial HEDM dataset collected using this hardware on an alpha-titanium alloy (Ti-7Al) under in situ tensile deformation at the Advanced Photon Source, Argonne National Laboratory. We present both near-field HEDM data that maps out the grain morphology and intragranular crystallographic orientations and far-field HEDM data that provides the grain centroid, grain average crystallographic orientation, and grain average elastic strain tensor for each grain. Finally, we provide a finite element mesh that can be utilized to simulate deformation in the volume of this Ti-7Al specimen. The dataset supporting this article is available in the National Institute of Standards and Technology (NIST) repository (http://hdl.handle.net/11256/599). More... »

PAGES

5

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s40192-016-0048-1

DOI

http://dx.doi.org/10.1186/s40192-016-0048-1

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https://app.dimensions.ai/details/publication/pub.1002750774


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