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Statistical Void analysis from CT Imagery with Applications to Damage Evolution in an AM60B Magnesium Alloy

Amy M. Waters, Harry E. Martz, Kenneth W. Dolan. ,
Lawrence Livermore National Laboratory Livermore, CA 94550 USA
Mark F. Horstemeyer
Lawrence Livermore National Laboratory Livermore, CA 94550 USA
Permanent address Sandia National Laboratory, Livermore, CA 94550
Robert E. Green, Jr
Lawrence Livermore National Laboratory Livermore, CA 94550 USA
Permanent address Center for Nondestructive Evaluation, 102 Maryland Hall,
The Johns Hopkins University, Baltimore MD 21218
Contact

ABSTRACT

INTRODUCTION

MATERIALS

EXPERIMENTAL TECHNIQUE

DATA REDUCTION AND ANALYSIS

Fig 2: Nearest neighbor distance distribution, and void size probability plots for one tensile bar (H24) after each loading. Note the shape of the distributions does not appear to change significantly with load.

RESULTS AND DISCUSSION

SUMMARY

ACKNOWLEDGEMENTS

REFERENCES

  1. Kak, A. C. and Slaney, M., Principles of Computerized Tomographic Imaging, New York: IEEE Press, 1988.
  2. Herman, G. T., Image Reconstruction from Projections, Academic Press, 1980.
  3. Kinney, J. H., and Nichols, M. C., "X-ray Tomographic Microscopy (XTM) using synchotron radiation", Ann Rev Mater Sci 22:121-152, 1992.
  4. Hoshen, J., and Kopelman, R., "Percolation and cluster distribution. I. Cluster multiple labeling technique and critical concentration algorithm", Phys Rev B 15:3438-3445, 1976.
  5. Cocks, A. C. F., and Ashby, M. F., "On creep fracture by void growth", Prog Mater Sci 27:189-244, 1982.
  6. Garrison, W. M., and Moody, N. R., "Ductile fracture", Phys Chem Solids 48:1035-1074, 1987.

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