Use of X-ray Micro Computed Tomography for the Investigation of Drying and Salt Precipitation in a Regular Glass Bead Structure

  • Robert HaideEmail author
  • Maurizio Santini
Conference paper
Part of the Fluid Mechanics and Its Applications book series (FMIA, volume 121)


Micro computed tomography is a powerful tool for the inspection of porous media since it essentially provides the possibility to reconstruct a three dimensional volume of an object at micrometric spatial resolution. The technique is non-intrusive, while still being capable of dealing with matter that is opaque at the wavelengths of visible light. The processing of the obtained data such as segmentation and morphology characterization in multi-phase porous systems is a challenging research topic for the comprehension of countless physical problems in a variety of technical applications. This research project is dedicated to the investigation and optimization of all aspects along the process chain, starting from the preparation of adequate porous samples towards the acquisition of the computed tomographies and data processing until pore-scale fluid displacement processes in multi-phase systems can eventually be visualized and characterized. Presented here are the production process of a regular glass bead pack, the data acquisition and processing methods and the obtained results for tomographic experiments during which the pack is containing distilled water, doped with potassium iodide and air and is subjected to drying in ambient atmosphere. The sample design allows validation of values derived from tomographic data with analytically predictable values.



The authors acknowledge the help and guidance of Dr.-Ing. Stephanie Fest-Santini.


  1. 1.
    Wildenschild, D., Sheppard, A.P.: X-ray imaging and analysis techniques for quantifying pore-scale structure and processes in subsurface porous medium systems. Adv. Water Resour. 51, 217–246 (2013)Google Scholar
  2. 2.
    Foerst, P., Melo de Carvalho, T., Lechner, M., Kovacevic, T., Kim, S., Kirse, C., Briesen, H.: Estimation of mass transfer rate and primary drying times during freeze-drying of frozen maltodextrin solutions based on X-ray \(\upmu \)-computed tomography measurements of pore size distributions. J. Food Eng. 260, 50–57 (2019)Google Scholar
  3. 3.
    Warning, A., Verboven, P., Nicolaï, B., van Dalen, G., Datta, A.K.: Computation of mass transport properties of apple and rice from X-ray microtomography images. Innov. Food Sci. Emerg. Technol. 24, 14–27 (2014)CrossRefGoogle Scholar
  4. 4.
    Li, T., Schlüter, S., Dragila, M.I., Wildenschild, D.: An improved method for estimating capillary pressure from 3D microtomography images and its application to the study disconnected nonwetting phase. Adv. Water Resour. 114, 249–260 (2018)CrossRefGoogle Scholar
  5. 5.
    Gueven, I., Frijters, S., Harting, J., Luding, S., Steeb, H.: Hydraulic properties of porous sintered glass bead systems. Granul. Matter 19–28 (2017)Google Scholar
  6. 6.
    Kak, A.C., Slaney, M.: Principles of computerized tomographic imaging. Soc. Ind. Appl. Math. (2001)Google Scholar
  7. 7.
    Santini, M., Guilizzoni, M., Fest-Santini, S.: X-ray computed microtomography for drop shape analysis and contact angle measurement. J. Colloid Interface Sci. 409, 204–210 (2013)CrossRefGoogle Scholar
  8. 8.
    Conway, J.H., Sloane, N.J.A.: Sphere Packings, Lattices and Groups, 2nd edn. Grundlehren Der Mathematischen Wissenschaften (1993)Google Scholar
  9. 9.
    Krishna, P., Verma, A.R.: Closed packed structures. Int. Union Crystallogr. (1981)Google Scholar
  10. 10.
    Ketcham, R.A., Hanna, R.D.: Beam hardening correction for X-ray computed tomography of heterogeneous natural materials. Comput. Geosci. 67, 49–61 (2014)CrossRefGoogle Scholar
  11. 11.
    Volume Graphics GmbH. Cited 25 Nov 2019
  12. 12.
    Feldkamp, L.A., Davis, L., Kress, J.: Practical cone-beam algorithm. J. Opt. Soc. Am. 1, 612–619 (1984)CrossRefGoogle Scholar
  13. 13.
    Gilbert, P.: Iterative methods for the reconstruction of three dimensional objects from their projections. J. Theor. Biol. 36, 105–117 (1972)CrossRefGoogle Scholar
  14. 14.
    Batenburg, K.J., Sijbers, J.: DART: a practical reconstruction algorithm for discrete tomography. IEEE Trans. Image Process. 20(9), 2542–2553 (2011)MathSciNetCrossRefGoogle Scholar
  15. 15.
    van Aarle, W., Palenstijn, W.J., Cant, J., Janssens, E., Bleichrodt, F., Dabravolski, A., de Beenhouwer, J., Batenburg, K.J., Sijbers, J.: Fast and flexible X-ray tomography using the ASTRA toolbox. Opt. Express 24(22), 25129–25147 (2016)CrossRefGoogle Scholar
  16. 16.
    Lloyd, S.P.: Least square quantization in PCM. Bell Telephone Laboratories Paper (1957)Google Scholar
  17. 17.
    Buades, A., Coll, B., Morel, J.M.: A non-local algorithm for image denoising. Comput. Soc. Conf. Comput. Vis. Pattern Recognit. 2, 60–65 (2005)zbMATHGoogle Scholar
  18. 18.
    Immerkær, J.: Fast noise variance estimation. Comput. Vis. Image Underst. 64(2), 300–302 (1995)CrossRefGoogle Scholar
  19. 19.
  20. 20.
    Toei, R., Okazaki, M.: Drying mechanism of capillary-porous bodies. J. Eng. Phys. 19(3), 1123–1131 (1970)CrossRefGoogle Scholar
  21. 21.
    Thermo Fisher Scientific. Cited 26 Nov 2019
  22. 22.
    Beucher, S., Meyer, F.: The morphological approach to segmentation: the watershed transformation. Math. Morphol. Image Process. 433–481 (1993)Google Scholar
  23. 23.
    Chapman, R.: Physics for Geologists, 2nd edn (2002)Google Scholar
  24. 24.
    Shokri, N., Lehmann, P., Or, D.: Liquid-phase continuity and solute concentration dynamics during evaporation from porous media: pore-scale processes near vaporization surface. Phys. Rev. E 81, 046308 (2010)CrossRefGoogle Scholar
  25. 25.
    Huinink, H.P., Pel, L., Michels, M.A.J.: How ions distribute in a drying porous medium: a simple model. Phys. Fluids 14(4), 1389–1395 (2002)CrossRefGoogle Scholar
  26. 26.
    Dunlop, P.J., Stokes, R.H.: The diffusion coefficients of sodium and potassium iodides in aqueous solution at 25\(^\circ \). J. Am. Chem. Soc. 73(11), 5456–5457 (1951)CrossRefGoogle Scholar
  27. 27.
    Nachson, U., Weisbrod, N., Dragila, M.I., Grader, A.: Combined evaporation and salt precipitation in homogeneous and heterogeneous porous media. Water Resour. Res. 47, W03513 (2011)Google Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Management, Information and Production EngineeringUniversity of BergamoDalmineItaly
  2. 2.Department of Engineering and Applied SciencesUniversity of BergamoDalmineItaly

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