Reconstruction of Single-Grain Orientation Distribution Functions for Crystalline Materials

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    A fundamental imaging problem in microstructural analysis of metals is the reconstruction of local crystallographic orientations from X-ray diffraction measurements. This work develops a fast, accurate, and robust method for the computation of the three-dimensional orientation distribution function for individual grains of the material in consideration. We study two iterative large-scale reconstruction algorithms, the algebraic reconstruction technique (ART) and conjugate gradients for least squares (CGLS), and demonstrate that right preconditioning is necessary in both algorithms to provide satisfactory reconstructions. Our right preconditioner is not a traditional one that accelerates convergence; its purpose is to modify the smoothness properties of the reconstruction. We also show that a new stopping criterion, based on the information available in the residual vector, provides a robust choice of the number of iterations for these preconditioned methods.
    Original languageEnglish
    JournalSIAM Journal of Imaging Sciences
    Volume2
    Issue number2
    Pages (from-to)593-613
    ISSN1936-4954
    DOIs
    Publication statusPublished - 2009

    Keywords

    • materials science
    • Materials characterization and modelling
    • stopping criterion
    • preconditioning
    • regularizing iterations
    • orientation distribution function,
    • polycrystals

    Cite this