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An Orientation-space Super Sampling Technique for Six-dimensional Diffraction Contrast Tomography

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Diffraction contrast tomography (DCT) is an X-ray full-field imaging technique that allows for the non-destructive three-dimensional investigation of polycrystalline materials and the determination of the physical and morphological properties of their crystallographic domains, called grains. This task is considered more and more challenging with the increasing intra-granular deformation, also known as orientation-spread. The recent introduction of a sixdimensional reconstruction framework in DCT (6D-DCT) has proven to be able to address the intra-granular crystal orientation for moderately deformed materials. The approach used in 6D-DCT, which is an extended sampling of the six-dimensional combined position-orientation space, has a linear scaling between the number of sampled orientations, which determine the orientation-space resolution of the problem, and computer memory usage. As a result, the reconstruction of more deformed materials is limited by their high resource requirements from a memory and computational point of view, which can easily become too demanding for the currently available computer technologies. In this article we propose a super-sampling method for the orientation-space representation of the six-dimensional DCT framework that enables the reconstruction of more deformed cases by reducing the impact on system memory, at the expense of longer reconstruction times. The use of super-sampling can further improve the quality and accuracy of the reconstructions, especially in cases where memory restrictions force us to adapt to inadequate (undersampled) orientation-space sampling.
Wydawca
Rocznik
Strony
219--230
Opis fizyczny
Bibliogr. 12 poz., rys.
Twórcy
autor
  • MATEIS, INSA Lyon, CNRS (UMR5510), Univ. Lyon, F-69621 Lyon, France
  • ESRF, The European Synchrotron, F-38043 Grenoble, France
  • CWI, Amsterdam, 1098 XG Amsterdam, The Netherlands
  • University of Leiden, Mathematical Institute, 2300 RA Leiden, The Netherlands
autor
  • MATEIS, INSA Lyon, CNRS (UMR5510), Univ. Lyon, F-69621 Lyon, France
  • ESRF, The European Synchrotron, F-38043 Grenoble, France
Bibliografia
  • [1] Viganò N, Ludwig W, Batenburg KJ. Reconstruction of local orientation in grains using a discrete representation of orientation space. Journal of Applied Crystallography. 2014 oct;47(6):1826–1840. doi:10.1107/S1600576714020147.
  • [2] Viganò N, Tanguy A, Hallais S, Dimanov A, Bornert M, Batenburg KJ, et al. Three-dimensional full-field X-ray orientation microscopy. Scientific Reports. 2016 feb;6. Available from: http://www.nature.com/articles/srep20618. doi:10.1038/srep20618.
  • [3] Viganò N, Nervo L, Valzania L, Singh G, Preuss M, Batenburg KJ, et al. A feasibility study of full-field X-ray orientation microscopy at the onset of deformation twinning. Journal of Applied Crystallography. 2016 apr;49(2). doi:10.1107/S1600576716002302.
  • [4] Ludwig W, Reischig P, King A, Herbig M, Lauridsen EM, Johnson G, et al. Three-dimensional grain mapping by x-ray diffraction contrast tomography and the use of Friedel pairs in diffraction data analysis. The Review of scientific instruments. 2009 mar;80(3):033905. doi:10.1063/1.3100200.
  • [5] Reischig P, King A, Nervo L, Viganò N, Guilhem Y, Palenstijn WJ, et al. Advances in X-ray diffraction contrast tomography: flexibility in the setup geometry and application to multiphase materials. Journal of Applied Crystallography. 2013 mar;46(2):297–311. doi:10.1107/S0021889813002604.
  • [6] Frank FC. Orientation mapping. Metallurgical Transactions A. 1988;19(3):403–408. doi:10.1007/BF02649253.
  • [7] Kumar A, Dawson PR. Computational modeling of f.c.c. deformation textures over Rodrigues’ space. Acta Materialia. 2000 jun;48(10):2719–2736. doi:10.1016/S1359-6454(00)00044-6.
  • [8] Van Aarle W, Batenburg KJ, Van Gompel G, Van de Casteele E, Sijbers J. Super-resolution for computed tomography based on discrete tomography. IEEE transactions on image processing: a publication of the IEEE Signal Processing Society. 2014;23(3):1181–93. doi:10.1109/TIP.2013.2297025.
  • [9] Candes E, Romberg J. l1-magic: Recovery of sparse signals via convex programming. 2005; p. 1–19. http://statwebstanfordedu/~candes/l1magic/.
  • [10] Sidky EY, Jørgensen JH, Pan X. Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle-Pock algorithm. Physics in medicine and biology. 2012 may; 57(10):3065–91. doi:10.1088/0031-9155/57/10/3065.
  • [11] Morawiec A, Field D. Rodrigues parameterization for orientation and misorientation distributions. Philosophical Magazine A. 1996;73:1113–1130. doi:10.1080/01418619608243708.
  • [12] Poulsen HF. Three-Dimensional X-Ray Diffraction Microscopy. vol. 205 of Springer Tracts in Modern Physics. Berlin, Heidelberg: Springer Berlin Heidelberg; 2004. doi:10.1007/b97884.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e92d5354-c991-489f-82ff-0a4cdcfeaca7
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