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Metallurgical and Materials Transactions A

, Volume 35, Issue 7, pp 1969–1979 | Cite as

Statistically representative three-dimensional microstructures based on orthogonal observation sections

  • David M. Saylor
  • Joseph Fridy
  • Bassem S. El-Dasher
  • Kee-Young Jung
  • Anthony D. Rollett
Article

Abstract

Techniques are described that have been used to create a statistically representative three-dimensional model microstructure for input into computer simulations using the geometric and crystallographic observations from two orthogonal sections through an aluminum polycrystal. Orientation maps collected on the observation planes are used to characterize the sizes, shapes, and orientations of grains. Using a voxel-based tessellation technique, a microstructure is generated with grains whose size and shape are constructed to conform to those measured experimentally. Orientations are then overlaid on the grain structure such that distribution of grain orientations and the nearest-neighbor relationships, specified by the distribution of relative misorientations across grain boundaries, match the experimentally measured distributions. The techniques are applicable to polycrystalline materials with sufficiently compact grain shapes and can also be used to controllably generate a wide variety of hypothetical microstructures for initial states in computer simulations.

Keywords

Material Transaction Grain Orientation Polycrystalline Microstructure Relative Misorientation Ellipsoid Center 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    B.L. Adams, S.I. Wright, and K. Kunze: Metall. Trans. A, 1993, vol. 24A, pp. 819–31.Google Scholar
  2. 2.
    V.R. Vedula, S.J. Glass, D.M. Saylor, G.S. Rohrer, W.C. Carter, S.A. Langer, and E.R. Fuller, Jr.: J. Am. Ceram. Soc., 2001, vol. 84, pp. 2947–54.CrossRefGoogle Scholar
  3. 3.
    Y. Fang, K. Ravi-Chandar, and K.W. White: J. Am. Ceram. Soc., 2002, vol. 85, pp. 1783–87.CrossRefGoogle Scholar
  4. 4.
    T. Weiss, S. Siegesmund, and E.R. Fuller, Jr.: in Natural Stone, Weathering Phenomena, Conservation Strategies and Case Studies, Geological Society of London, Special Publication No. 205, S. Siegesmund, A. Vollbrecht, and T. Weiss, eds., Geological Society of London, London, 2002, pp. 81–94.Google Scholar
  5. 5.
    T. Baudin, P. Paillard, and R. Penelle: Scripta Mater., 1999, vol. 40, pp. 1111–16.CrossRefGoogle Scholar
  6. 6.
    S.W. Cheong, E.J. Hilinski, and A.D. Rollett: Metall. Mater. Trans. A, 2003, vol. 34A, pp. 1321–27.Google Scholar
  7. 7.
    S.F. Nielsen, E.M. Lauridsen, D. Juul Jensen, H.F. Poulsen: Mater. Sci. Eng. A, 2001, vols. 319–321, pp. 179–81.Google Scholar
  8. 8.
    B.C. Larsen, W. Yang, G.E. Ice, J.D. Budal, and J.Z. Tischier: Nature, 2002, vol. 415, pp. 887–90.CrossRefGoogle Scholar
  9. 9.
    K.W. Mahin, K. Hanson, and J.W. Morris, Jr.: Acta. Met., vol. 28, pp. 443–53.Google Scholar
  10. 10.
    O. Ito and E.R. Fuller, Jr.: Acta Metall. Mater., 1993, vol. 41, pp. 191–98.CrossRefGoogle Scholar
  11. 11.
    M. Miodownik, A.W. Godfrey, E.A. Holm, and D.A. Hughes: Acta Mater., 1999, vol. 47, pp. 2661–68.CrossRefGoogle Scholar
  12. 12.
    B.L. Adams and T. Olson: Progr. Mater. Sci., 1998, vol. 43, pp. 1–87.CrossRefGoogle Scholar
  13. 13.
    W.K. Pratt: Digital Image Processing, John Wiley & Sons Inc., New York, NY, 2001, pp. 597–607.Google Scholar
  14. 14.
    G.B. Thomas, Jr.: Calculus and Analytic Geometry, Addison-Wesley Publishing Company, Inc., Reading, MA, 1968, p. 414.Google Scholar
  15. 15.
    N.L. Johnson and F.C. Leone: Statistics and Experimental Design in Engineering and the Physical Sciences, John Wiley & Sons Inc., New York, NY, 1964, p. 41.Google Scholar
  16. 16.
    W.H. Press, W.T. Vetterling, S.A. Teukolsky, and B.P. Flannery: Numerical Recipes in C++: The Art of Scientific Computing, 2nd ed., Cambridge University Press, New York, NY, 2002, pp. 448–55.Google Scholar
  17. 17.
    K. Shimada and D. Gossard: ACM 3rd Symp. on Solid Modeling and Applications, 1995, pp. 409–19.Google Scholar
  18. 18.
    F. Frank: Metall. Trans. A, 1988, vol. 19A, pp. 403–08.Google Scholar
  19. 19.
    A. Morawiec: Acta Cryst., 1997, vol. A53, pp. 273–85.Google Scholar
  20. 20.
    M.P. Anderson, G.S. Grest, and D.J. Srolovitz: Scripta Metall., 1985, vol. 19, pp. 225–30.CrossRefGoogle Scholar
  21. 21.
    D.M. Saylor, A. Morawiec, G.S. Rohrer: J. Am. Cer. Soc., 2002, vol. 85, pp. 3081–83.CrossRefGoogle Scholar

Copyright information

© ASM International & TMS-The Minerals, Metals and Materials Society 2004

Authors and Affiliations

  • David M. Saylor
    • 1
  • Joseph Fridy
    • 2
  • Bassem S. El-Dasher
    • 3
  • Kee-Young Jung
    • 3
  • Anthony D. Rollett
    • 3
  1. 1.MSEL, National Institute of Standards and TechnologyGaithersburg
  2. 2.Alcoa Technical CenterAlcoa Center
  3. 3.the Materials Science and Engineering DepartmentCarnegie Mellon UniversityPittsburgh

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