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Stereological Estimation of Orientation Distribution of Generalized Cylinders from a Unique 2D Slice

Published online by Cambridge University Press:  24 October 2013

Jean-Pierre Da Costa*
Affiliation:
Univ. Bordeaux, IMS, UMR 5218, F-33400 Talence, France CNRS, IMS, UMR 5218, F-33400 Talence, France
Stefan Oprean
Affiliation:
CNRS, IMS, UMR 5218, F-33400 Talence, France
Pierre Baylou
Affiliation:
Univ. Bordeaux, IMS, UMR 5218, F-33400 Talence, France CNRS, IMS, UMR 5218, F-33400 Talence, France
Christian Germain
Affiliation:
Univ. Bordeaux, IMS, UMR 5218, F-33400 Talence, France CNRS, IMS, UMR 5218, F-33400 Talence, France
*
*Corresponding author. E-mail: jean-pierre.dacosta@ims-bordeaux.fr
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Abstract

Though three-dimensional (3D) imaging gives deep insight into the inner structure of complex materials, the stereological analysis of 2D snapshots of material sections is still necessary for large-scale industrial applications for reasons related to time and cost constraints. In this paper, we propose an original framework to estimate the orientation distribution of generalized cylindrical structures from a single 2D section. Contrary to existing approaches, knowledge of the cylinder cross-section shape is not necessary. The only requirement is to know the area distribution of the cross-sections. The approach relies on minimization of a least squares criterion under linear equality and inequality constraints that can be solved with standard optimization solvers. It is evaluated on synthetic data, including simulated images, and is applied to experimental microscopy images of fibrous composite structures. The results show the relevance and capabilities of the approach though some limitations have been identified regarding sensitivity to deviations from the assumed model.

Type
Techniques and Instrumentation Development
Copyright
Copyright © Microscopy Society of America 2013 

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References

Badel, P., Vidal-Sallé, E., Maire, E. & Boisse, P. (2009). Simulation and tomography analysis of textile composite reinforcement deformation at the mesoscopic scale. Int J Mater Forming 2, 189192.Google Scholar
Bale, H., Blacklock, M., Begley, M.R., Marshall, D.B., Cox, B.N. & Ritchie, R.O. (2012). Characterizing three-dimensional textile ceramic composites using synchrotron X-ray micro-computed-tomography. J Am Ceram Soc 95, 392402.CrossRefGoogle Scholar
Ballard, D.H. & Brown, C.M. (1982). Computer Vision, Chap. 9.1, pp. 274275. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
Blanc, R., Baylou, P., Germain, C. & Da Costa, J.P. (2010). Confidence bounds for the estimation of the volume phase fraction from a single image in a nickel base superalloy. Microsc Microanal 16, 273281.Google Scholar
Blanc, R., Germain, C., Da Costa, J.P., Baylou, P. & Cataldi, M. (2006). Fiber orientation measurements in composite materials. Composites Part A 37, 197206.Google Scholar
Chapoullié, C., Germain, C., Da Costa, J., Vignoles, G.L. & Cataldi, M. (2013). Multiscale extraction of morphological features in woven cmcs. In Proceedings of ICACC, Daytona Beach, FL, USA. Google Scholar
Clarke, A., Eberhardt, C. & Davidson, N. (2012). 3D characterisation of glass fibers in composites by confocal microscopy. In Proceedings of ICCM12, Paris. Google Scholar
Coindreau, O. & Vignoles, G.L. (2005). Assessment of structural and transport properties in fibrous c/c composite preforms as digitized by X-ray CMT. Part I: Image acquisition and geometrical properties. J Mater Res 20, 23282339.Google Scholar
Couégnat, G., Martin, E. & Lamon, J. (2010). 3D Multiscale Modeling of the Mechanical Behavior of Woven Composite Materials, pp. 185194. Hoboken, NJ: John Wiley & Sons Inc. Google Scholar
Davidson, N., Clarke, A. & Archetypal, G. (1997). Large-area, high-resolution image analysis of composite materials. J Microsc 185, 233242.CrossRefGoogle Scholar
Eberhardt, C. & Clarke, A. (2001). Fiber-orientation measurements in short-glass-fibre composites. Part I. Automated, high-angular-resolution measurement by confocal microscopy. Composites Sci Technol 61, 13891400.Google Scholar
Germain, C., Blanc, R., Donias, M., Lavialle, O., Da Costa, J.P. & Baylou, P. (2005). Estimating the section elevation angle of cubes on a cubic mesh. Application to nickel microstructure size estimation. Image Anal Stereol 24, 127134.Google Scholar
Harris, J.W. & Stocker, H. (1998). Handbook of Mathematics and Computational Science, Chapter 4.6, pp. 102104. New York: Springer-Verlag.Google Scholar
Hivet, G., Wendling, A., Vidal-Salle, E., Laine, B. & Boisse, P. (2010). Modeling strategies for fabrics unit cell geometry application to permeability simulations. Int J Mater Form 3, 727730.CrossRefGoogle Scholar
Kern, W.F. & Bland, J.R. (1948). Solid Mensuration with Proofs, chapters 16–17, pp. 3642. New York: Wiley.Google Scholar
Kim, J., Liaw, P.K., Hsu, D.K. & McGuire, D.J. (1997). Nondestructive evaluation of nicalon/sic composites by ultrasonics and X-ray computed tomography. Ceram Eng Sci Proc 18, 287296.Google Scholar
Lee, K.S., Lee, S.W., Youn, J., Kang, T. & Chung, K. (2001). Confocal microscopy measurement of the fiber orientation in short fiber reinforced plastics. Fibers Polym 2, 4150.Google Scholar
Lee, Y.H., Lee, S.W., Youn, J., Chung, K. & Kang, T. (2002). Characterization of fiber orientation in short fiber reinforced composites with an image processing technique. Mater Res Innov 6, 6572.Google Scholar
Martín-Herrero, J. & Germain, C. (2007). Microstructure reconstruction of fibrous c/c composites from X-ray microtomography. Carbon 45, 12421253.Google Scholar
Miao, J., Charalambous, P., Kirz, J. & Sayre, D. (1999). Extending the methodology of X-ray crystallography to allow imaging of micrometre-sized non-crystalline specimens. Nature 400, 342344.CrossRefGoogle Scholar
Miao, J., Sandberg, R. & Song, C. (2012). Coherent X-ray diffraction imaging. Selected topics in quantum electronics, IEEE J Sel Topics Quantum Electron 18, 399410.CrossRefGoogle Scholar
Mlekusch, B. (1999). Fiber orientation in short-fiber-reinforced thermoplastics. II. Quantitative measurements by image analysis. Compos Sci Technol 59, 547560.Google Scholar
Oakeshott, R.B.S. & Edwards, S.F. (1992). On the stereology of ellipsoids and cylinders. Phys A 189, 208233.Google Scholar
Russ, J. & Dehoff, R. (2000). Practical Stereology. New York: Plenum Press.Google Scholar
Sterio, D. (1984). The unbiased estimation of number and sizes of arbitrary particles using the dissector. J Microsc 134, 127136.Google Scholar
Weisstein, E.W. (2013). Cylinder, from Mathworld—A Wolfram web resource. Available at http://mathworld.wolfram.com/Cylinder.html.Google Scholar