Transport in Porous Media

, Volume 73, Issue 3, pp 319–332 | Cite as

Analysis of Pore Network in Three-dimensional (3D) Grain Bulks Using X-ray CT Images

Article

Abstract

The knowledge of distribution of pore space inside grain bulks is essential for determining the airflow resistance of grains. In this study, the internal pore structure and the 3D-distribution of air paths inside grain bulks were studied using X-ray computed tomography images. Image analysis methods were applied to the binary 3D X-ray CT images on the spatial distribution of voids to generate the connected, individualized pore objects of different size and shapes. Morphometric parameters, such as 3D air path volume distribution, structure separation factor, Euler number, fragmentation index, and structure model index were calculated based on hexahedral marching cubes volume model and marching cubes 3D surface construction algorithm. The quantified numerical measures of spatial integrity of air path networks were analyzed and compared with the airflow resistance of grain bulks. The results showed that the connectivity of airspace and the nonuniform distribution of air-path network inside grain bulks were responsible for the difference in airflow resistance between horizontal and vertical directions to the airflow of grain bulks.

Keywords

Pore network Airflow resistance Grain bulks 3D image analysis X-ray CT Connectivity 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Acasio, U.A.: Handling and Storage of Soybeans and Soybean Meal. American Soybean Association, St. Louis, MO (1997)Google Scholar
  2. Agriculture and Agri-Food Canada: Agriculture: Food and Much more. Available at: http://www.agr.gc.ca/cb/brochure/cwb_e.phtml (2005/12/27). Accessed 26 December 2005
  3. Alagusundaram K., Jayas D.S., Chotard F. and White N.D.G. (1992). Airflow pressure drop relationships of some specialty seeds. Sci. des. Alim. 12: 101–116 Google Scholar
  4. Antic A. and Hill J.M. (2000). A mathematical model for heat transfer in grain store microclimates. Austr. NewZ. Indus. Appl. Math. J. 42: 117–133 Google Scholar
  5. ASAE Standard.: Resistance to airflow of grains, seeds, other agricultural products, and perforated metal sheets. ASAE D272.3 DEC01. American society of Agricultural Engineers, St. Joseph, MI (2003)Google Scholar
  6. Berck B. (1975). Determination of air movement in stored grain as a factor of dynamic dispersion and distribution patterns of gaseous pesticides (fumigants). Bull. Environ. Contam. Toxic 13: 527–533 CrossRefGoogle Scholar
  7. Blunt M.J. (2001). Flow in porous media—pore network models and multiphase flow. Curr. Opin. Colloid Interface Sci. 6: 197–207 CrossRefGoogle Scholar
  8. Bogaert J., Hecke P.V. and Ceulemans R. (2002). The Euler number as an index of spatial integrity of landscapes: evaluation and proposed improvement. Environ. Manage. 29: 673–682 CrossRefGoogle Scholar
  9. Bouvier, D.J.: Double Time Cubes. A Fast 3D Surface Reconstruction Algorithm for Volume visualization. International Conference on Imaging, Science Systems and Technology, Las Vegas, Nevada (1997)Google Scholar
  10. Brooker D.B. (1961). Pressure patterns in grain drying systems established by numerical methods. Trans. Am. Soc. Agric. Eng. 4: 72–77 Google Scholar
  11. Darling A. and Sun W. (2004). 3D Microtomographic characterization of precision extruded poly-ε-caprolactone tissue scaffolds. J. Biomed. Mater. Res. Appl. Biomater. 70: 311–317 CrossRefGoogle Scholar
  12. Endo Y., Chen D. and Pui D.Y.H. (2002). Theoretical consideration of permeation resistance of fluid through a particle packed layer. Power. Technol. 124: 119–126 CrossRefGoogle Scholar
  13. Feldkamp L.A., Davis L.C. and Kress J.W. (1984). Practical cone-beam algorithm. J. Opt. Soc. Am. 1: 612–619 CrossRefGoogle Scholar
  14. Giner S.A. and Denisienia E. (1996). Pressure drop through wheat as affected by air velocity, moisture content and fines. J. Agric. Eng. Res. 63: 73–86 CrossRefGoogle Scholar
  15. Hahn M., Vogel M., Pompesius-Kempa M. and Delling G. (1992). Trabecular bone pattern factor—a new parameter for simple quantification of bone microarchitecture. Bone 13: 327–330 CrossRefGoogle Scholar
  16. Hildebrand T. and Ruegsegger P. (1997). Quantification of bone microarchitecture with the structure model index. Comp. Meth. Biomech. Biomed. Eng. 1: 15–23 CrossRefGoogle Scholar
  17. Hood T.J.A. and Thorpe G.R. (1992). The effects of anisotropic resistance to air flow on the design of aeration systems for bulk stored grains. Agric. Eng. Aust. 21: 18–23 Google Scholar
  18. Irvine D.A., Jayas D.S., White N.D.G. and Britton M.G. (1992). Physical properties of flax seed, lentils, and fababeans. Can. Agric. Eng. 34: 75–81 Google Scholar
  19. Jayas D.S., Alagusundaram K. and Irvine D.A. (1991). Resistance to airflow through bulk flax seed as affected by the moisture content, direction of airflow and foreign material. Can. Agric. Eng. 33: 279–285 Google Scholar
  20. Jayas D.S., Sokhansanj S., Moysey E.B. and Barber E.M. (1987). The effect of airflow direction on the resistance of canola (rapeseed) to airflow. Can. Agric. Eng. 29: 189–192 Google Scholar
  21. Kainourgiakis M.E., Kikkinides E.S., Galani A., Charalambopoulou G.C. and Stubos A.K. (2005). Digitally reconstructed porous media: transport and sorption properties. Transp. Porous Media 58: 43–62 CrossRefGoogle Scholar
  22. Kay R.L., Bern C.J. and Hurburgh C.R. (1989). Horizontal and vertical airflow resistance of shelled corn at various bulk densities. Trans. Am. Soc. Agric. Eng. 32: 733–736 Google Scholar
  23. Kumar A. and Muir W.E. (1986). Airflow resistance of wheat and barley affected by airflow direction, filling method and dockage. Trans. Am. Soc. Agric. Eng. 29: 1423–1426 Google Scholar
  24. Lindquist, W.B.: Quantitative analysis of three dimensional X-ray tomographic images, in developments in X-ray Tomography III. In: Proceedings of SPIE, 4503, pp. 103–115. SPIE, Bellingham, USA, July 7–10 (2002)Google Scholar
  25. Lorensen W.E. and Cline H.E. (1987). Marching cubes: a high resolution 3D surface construction algorithm. Comp. Graph 21: 163–169 CrossRefGoogle Scholar
  26. Mecke K.R. (1998). Integral geometry and statistical physics. Int. J. Mod. Phy. B 12: 861–899 CrossRefGoogle Scholar
  27. Nielsen J. (1998). Pressures from flowing granular solids in silos. Philos. Trans. R. Soc. Lond. A 356: 2667–2684 CrossRefGoogle Scholar
  28. Odgaard A. and Gundersen H.J. (1993). Quantification of connectivity in cancellous bone, with special emphasis on 3-D reconstructions. Bone 14: 173–182 CrossRefGoogle Scholar
  29. Parfitt A.M., Drezner M.K., Glorieux F.H., Kanis J.A., Malluche H., Meunier P.J., Ott S.M. and Recker R.R. (1987). Bone histomorphometry: standardization of nomenclature, symbols and units. J. Bone. Miner. Res. 2: 595–610 CrossRefGoogle Scholar
  30. Smith E.A. (1996). Pressure and velocity of air during drying and storage of cereal grains. Transp. Porous Media 23: 197–218 CrossRefGoogle Scholar
  31. Smith E.A. and Jayas D.S. (2004). Calculation and limitations of traverse time in designing forced ventilation systems. Trans. Am. Soc. Agric. Eng. 47: 1635–1642 Google Scholar
  32. Smith E.A., Jayas D.S. and Ville A. (2001). Modelling the flow of carbon dioxide through beds of cereal grains. Trans. Porous Media 44: 123–144 CrossRefGoogle Scholar
  33. Turner, M., Sakellariou, A., Arns, C., Sok, R., Limaye, A., Sendent, T. and Knacksted, M.: Towards Modelling Regolith Permeability with High Resolution X-ray Tomography. Adv. Rego., CRC LEME, Adelaide, Australia (2003)Google Scholar
  34. Velasco L., Jose M.M. and Haro A. (1998). Application of near-infrared reflectance spectroscopy to estimate the bulk density of ethiopian mustard seeds. J. Sci. Food. Agric. 77: 312–318 CrossRefGoogle Scholar
  35. Vogel H.J. and Babel U. (1996). Topological characterization of pore space in soil-sample preparation and digital image processing. Geoder 73: 23–28 CrossRefGoogle Scholar
  36. Vogel H.J., Cousin I. and Roth K. (2002). Quantification of pore structure and gas diffusion as a function of scale. Euro. J. Soil. Sci. 53: 465–473 CrossRefGoogle Scholar
  37. Yang C., Chung P. and Chang C. (1996). Hierarchial fast two dimensional entropy thresholding algorithm using a histogram pyramid. Opt. Eng. 35: 3227–3241 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  1. 1.The Canadian Wheat Board Centre for Grain Storage Research, Biosystems EngineeringUniversity of ManitobaWinnipegCanada
  2. 2.University of ManitobaWinnipegCanada

Personalised recommendations