Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-29T07:40:25.691Z Has data issue: false hasContentIssue false
  • English
  • Français

Fracture Surface Fractal Dimension Determined Through An Extensive 3-D Reconstruction

Published online by Cambridge University Press:  15 February 2011

J.J. Ammann  and
A.M. Nazar
J.J. Ammann
Affiliation:
Materials Engineering Department, Faculty of Mechanical Engineering, State University of Campinas, Campinas, Brazil
A.M. Nazar
Affiliation:
Materials Engineering Department, Faculty of Mechanical Engineering, State University of Campinas, Campinas, Brazil
Get access

Abstract

An efficient image processing method is developed to determine the fractal dimension from a high resolution 3-D reconstruction of fracture surface. The third dimension of the fracture surface is obtained from a stereo pair. The elevation is locally determined through a recursive window matching algorithm centered on the cross-correlation operation. The method allows to reach high vertical and horizontal resolutions of the elevation map.

The fractal dimension is obtained by an implementation of the slit-island method. A series of contour lines is extracted from the reconstructed surface. The images of the contour lines are progressively reduced in size and at every step the curve length is estimated. The result is then normalized according to the scale factor to build a Kolmogorov plot.

The performance of this method is demonstrated on a synthetic image generated by a fracture surface mathematical model.

Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 409: Symposium Q – Fracture-Instablility Dynamics, scaling and Ductile/Brittle Behavior , 1995 , 359
Copyright
Copyright © Materials Research Society 1996

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Coster, M. and Chermant, J.L., International Metals Reviews 28 (4), 228 (1983).Google Scholar
2. EI-Soudani, S.M., J. of Microscopy; October 1990, 20–27.Google Scholar
3. Underwood, E.E. and Banerji, K., in Metals Handbook, 9th ed. (ASM International, Metals Park, 1987), vol.12, pp. 193–210.Google Scholar
4. Wojnar, L. and Kumosa, M., Material Science and Engineering A 128, 45 (1990).Google Scholar
5. Underwood, S.E.E., J. of Microscopy; Oct 1990, p. 10–15.Google Scholar
6. Dong, W.P., Sullivan, P.J. and Stout, K.J., Wear 178 (1–2), 29 (1994).Google Scholar
7. Russ, J.C., J. of Microscopy; October 1990, pp. 16–19.Google Scholar
8. Borodich, F.M. in IFIP trans A. Computer Science and Technology, A–41, 61 (1994).Google Scholar
9. Carpinteri, A., Mech. Mater. 18 (2), 89 (1994).Google Scholar
10. Xie, H., Sanderson, D.J. and Peacock, D.C.P., Eng. Fract. Mech. 48 (5), 655 (1994).Google Scholar
11. Friel, J. J. and Pande, C.S., J. Mater. Res. 8 (1), 100 (1993).Google Scholar
12. Brown, C. A. and Savary, G., Wear 141, 211 (1991).Google Scholar
13. Koenig, G., Nickel, W., Storl, J., Meyer, D. and Stange, J., Scanning 9, 185 (1987).Google Scholar
14. Ammann, J. J., Hein, L.R. de O. and Nazar, A. M. in Proceedings of the International Metallography Conference, (ASM, 1995).Google Scholar
15. Russ, J. C., J. of Microscopy; Dec. 1993; p. 239–248.Google Scholar
16. Konstatinides, K. and Rassure, J. in IEEE Trans. on Image Processing (IEEE, 1994), 3 (3) pp. 243–252.Google Scholar
17. Bouchaud, E., (private communication).Google Scholar