Journal of the Korean Geotechnical Society (한국지반공학회논문집)

Korean Geotechnical Society (한국지반공학회)
권호 표지
DOI QR코드

DOI QR Code

Quantification of 3D Pore Structure in Glass Bead Using Micro X-ray CT

Micro X-ray CT를 이용한 글라스 비드의 3차원 간극 구조 정량화

  • Jung, Yeon-Jong (Dept. of Civil and Environmental Engineering, Yonsei Univ.) ;
  • Yun, Tae-Sup (Dept. of Civil and Environmental Engineering, Yonsei Univ.)
  • 정연종 (연세대학교 사회환경시스템공학부) ;
  • 윤태섭 (연세대학교 사회환경시스템공학부)
  • Received : 2011.09.26
  • Accepted : 2011.10.25
  • Published : 2011.11.30
Download PDF
⟨ Previous Next ⟩

Abstract

The random and heterogeneous pore structure is a significant factor that dominates physical and mechanical behaviors of soils such as fluid flow and geomechanical responses driven by loading. The characterization method using non-destructive testing such as micro X-ray CT technique which has a high resolution with micrometer unit allows to observe internal structure of soils. However, the application has been limited to qualitatively observe 2D and 3D CT images and to obtain the void ratio at macro-scale although the CT images contain enormous information of materials of interests. In this study, we constructed the 3D particle and pore structures based on sequentially taken 2D images of glass beads and quantitatively defined complex pore structure with void cell and void channel. This approach was enabled by implementing image processing techniques that include coordinate transformation, binarization, Delaunay Triangulation, and Euclidean Distance Transform. It was confirmed that the suggested algorithm allows to quantitatively evaluate the distribution of void cells and their connectivity of heterogeneous pore structures for glass beads.

무질서하고 불균질한 형상을 갖는 지반 재료 내 간극 구조는 하중에 의한 재료의 변형 및 간극 내 유체의 흐름 등 물리 역학적 거동에 중요한 영향 인자이다. 최근 들어 X-ray CT에 의한 비파괴 검사를 통해 지반 재료의 내부 구조를 마이크로미터 단위의 높은 해상도를 통해 평가하는 기법이 사용되고 있다. CT 이미지는 재료의 많은 정보를 포함하고 있음에도 그에 따른 이미지 해석 기법의 개발이 다소 미흡하여 2, 3차원 이미지의 정성적 관찰 및 간극비와 같은 거시적인 물성치 획득만이 이루어지고 있다. 본 연구에서는 연속적으로 획득된 글라스 비드의 2차원 CT 이미지에 기반하여 3차원 입자 및 간극 구조를 형성하고, 복잡한 간극구조를 간극셀과 간극채널로 정량적 분리를 실시하였다. 이를 위해 좌표 변환법, 이진화, 들로네 삼각망, 그리고 유클리디안 거리변환법과 같은 이미지 프로세싱 기법을 3차원 CT 이미지에 적용하였고 불균질한 글라스 비드의 간극구조에 대해 정량적으로 간극셀의 분포 및 간극간의 연결도 평가가 가능함을 확인하였다.

Keywords

References

  1. 김광염, 신휴성, 허성준, 임성빈, 권영철, 김홍택 (2011), "X-ray CT 스캔을 이용한 사질토 간극비 측정", 한국지반공학회논문집,27(1), pp.87-98.
  2. 정교철, Takahashi, M. (2010), "미소 촛점 X선 CT를 이용한 암석 내 공극의 분포 및 공극률 분석 " The Journal of Engineering Geology, 20(4), pp.461-465
  3. 김종태, Takahashi, M., 추창오, 노병돈, 정교철 (2011), "암석의X-ray CT 분석 결과와 저 투수성의 비료", Korean Society of Engineering Geology, Jeju, Korea, pp.169-172
  4. 정상엽, 김영진, 윤태섭, 전현규 (2011), "Micro CT 이미지 분석을 통한 경량 골재 콘크리트의 공극 분포 분석", 대한토목학회논문집, 31(2A), pp.121-127
  5. Abichou, T., Benson, C. H., and Edil, T. B. (2004), "Network model for hydraulic conductivity of sand-bentonite mixtures", Canadian Geotechnical Journal, 41(4), pp.698-712. https://doi.org/10.1139/t04-016
  6. Al-Raoush, R. I., Thompson, K., and Wilson, C. S. (2003), "Comparison of network generation techniques for unconsolidated porous media", Soil Science Society of American Journal, 67(6), pp.1687 -1700. https://doi.org/10.2136/sssaj2003.1687
  7. AI-Raoush, R. I. and Willson, C. S. (2005), "Extraction of physically realistic pore network properties from three-dimensional synchrotron X-ray microtomography images of unconsolidated porous media systems", Journal of Hydrology, 300(1-4), pp.44-64. https://doi.org/10.1016/j.jhydrol.2004.05.005
  8. Barboczi, E. J. (2010), "Quantifying particle shape in 3D.", Advances in computed tomography for geomaterials, GEOX 2010, New Orleans, LA, USA, pp.94-100.
  9. Bosl, W. J., Dvorkin, J., and Nur, A (1998), "A study of porosity and permeability using a Lattice-Boltzmann simulation", Geophysical Research Letters, 25(9), pp.1475-1478. https://doi.org/10.1029/98GL00859
  10. Bryant, S. 1., King, P. R., and Mellor, D. W. (1993), "Network model evaluation of permeability and spatial correlation in a real random sphere packing", Transport in Porous Media, 11(1), pp.53-70. https://doi.org/10.1007/BF00614635
  11. Fredrich, J. T., DiGiovanni, A A, and Noble, D. R. (2006), "Predictin macroscopic transport properties using microscopic image data", Journal of geophysical research, 111(B03201), pp.1-14.
  12. Hall, S. A, Lenoir, N., Viggini, G., Besuelle, P., and Desrues, J. (2010), "Characterization of the evolving grain-scale structure in a sand deforming under triaxial compression.", Advances in computed tomography for geomaterials, GEOX 2010, New Orleans, LA, USA, pp.34-42.
  13. Kikuchi, Y., Hidaka, T., Sato, T., and Hazarika, H. (2010), "Deformation characteristics of tire chips-sand mixture in triaxial compression test by using X-ray CT scanning.", Advances in computed tomography for geomaterials, GEOX 2010, New Orleans, LA, USA, pp.67-75.
  14. Kress, J., Yun, T. S., Narsilio, G., Evans, M., and Lee, D.-S. (2011), "Evaluation of hydraulic conductivity in 3D random and heterogeneous particulate materials using network model", Computers and Geotechnics, in press.
  15. Man, H. N. and Jing, X. D. (1999), "Network modelling of wettability and pore geometry effects on electrical resistivity and capillary pressure", Journal of Petroleum Science and Technology,24, pp.255-267.
  16. Narsilio, G., Buzzi, 0., Fityus, S., Yun, T. S., and Smith, D. W. (2009), "Upscaling of Navier-Stokes equations in porous media: Theoretical, numerical and experimental approach", Computers and Geotechnics, 36, pp.1200-1206. https://doi.org/10.1016/j.compgeo.2009.05.006
  17. Narsilio, G., Kress, J., and Yun, T. S. (2010), "Characterization of conduction phenomena in soils at the particle-scale: Finite element analyses in conjunction with synthetic 3D imaging", Computers and Geotechnics, 37, pp.828-836. https://doi.org/10.1016/j.compgeo.2010.07.002
  18. Nordhaug, H. F., Celia, M., and Dahle, H. K. (2003), "A pore network model for calculation of interfacial velocities", Advances in Water Resources, 26, pp.1061-1074 https://doi.org/10.1016/S0309-1708(03)00100-3
  19. Otsu, N. (1979), "A threshold selection method from gray-level histogram", lEE Transactions on Systems, Man, and Cybernetics, 9, pp.62-66.
  20. Rafael, C. G. and Woods, R. E. (2002), Digital Image Processing: Prentice Hall.
  21. Svensson, S. and Borgefors, G. (2002), "Digital distance transforms in 3D images using information from neighbourhoods up to 5x5x5", Computers Vision and Image Understanding, 88, pp.24-53. https://doi.org/10.1006/cviu.2002.0976
  22. Thompson, K. E., Willson, C. S., White, C. D., Nyman, S., Bhattacharya, J. P., and Reed, A H. (2008), "Application of a new grain based reconstruction algorithm to microtomography images for quantitative characterization and flow modeling", SPE Journal, 13(2), pp.l64-176.
  23. Vogel, H. J. and Roth, K. (2001), "Quantitative morphology and network representation of soil pore structure", Advances in Water Resources, 24(3-4), pp.233-242. https://doi.org/10.1016/S0309-1708(00)00055-5
  24. Watanabe, Y., Lenoir, N., Hall, S. A, and Otani, J., (2010), "Strain field measurements in sand under triaxial compression using X-ray CT data and digital image correlation.", Advances in computed tomography for geomaterials, GEOX 2010, New Orleans, LA, USA, pp.76-83.

Cited by

  1. Estimation the Porosity of Pervious Concretes based on X-Ray CT and Submerged Weight vol.13, pp.4, 2013, https://doi.org/10.9798/KOSHAM.2013.13.4.077
  2. Micro X-ray CT 촬영을 통한 동결 사질토 시료의 세립분 함유량에 따른 입자간 거리 분석 vol.18, pp.1, 2011, https://doi.org/10.14481/jkges.2017.18.1.31