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A new Delaunay triangulation-based approach to characterize the pore network in granular materials

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Abstract

The ability of granular materials to retain fine particles transported within their void space by seepage flow depends strongly on the geometric characteristics of their pore network (pore sizes and constriction sizes). Hence, characterizing the pore network of a granular assembly obtained by means of a micro-tomography scanning or a numerical discrete simulation is of great importance in assessment of its filtration efficiency. Here, we determine characteristics of the pore network of virtual samples composed of spherical particles simulated by using the DEM. A new criterion is proposed to merge neighboring tetrahedra issued from the weighted Delaunay triangulation. To do so, we extend the concept of inscribed void sphere, initially defined for each tetrahedron, to each polyhedral sub-domain constituted of merged tetrahedra. This inscribed void sphere fits the best the void space within the sub-domain. Flat tetrahedra are first eliminated by a primary merging procedure taking into account two basic geometric conditions required for each pore. Adjacent sub-domains are then merged depending on the level of overlap between their inscribed void spheres. The pore size distributions and constriction size distributions (CSD) of granular samples with different grain size distributions obtained with the new merging criterion are compared to those given by two other criteria often used in the literature. The new criterion allows us to reduce greatly the inherent subjectivity in characterizing the granular pore network and to remediate the drawbacks of the two considered criteria in the literature. Moreover, CSDs given by these different criteria tend to converge for gap-graded and widely graded materials. The CSDs obtained with the new merging criterion are used to estimate the controlling constriction sizes \(D_c^*\) of the considered samples, and the estimated values of \(D_c^*\) are compared to Kenney and Lau’s empirical rule.

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References

  1. Al-Kharusi AS, Blunt MJ (2007) Network extraction from sandstone and carbonate pore space images. J Pet Sci Eng 56(4):219–231

    Article  Google Scholar 

  2. Al-Raoush R, Thompson K, Willson C (2003) Comparison of network generation techniques for unconsolidated porous media. Soil Sci Soc Am J 67(6):1687–1700

    Article  Google Scholar 

  3. Catalano E (2012) A pore–scale coupled hydromechanical model for biphasic granular media. application to granular sediment hydrodynamics. Ph.D. thesis, Université de Grenoble

  4. Chang DS, Zhang LM (2013) Extended internal stability criteria for soils under seepage. Soils Found 53(4):569–583

    Article  Google Scholar 

  5. Csardi G, Nepusz T et al (2006) The igraph software package for complex network research. InterJ Complex Syst 1695(5):1–9

    Google Scholar 

  6. Das N (2007) Modeling three-dimensional shape of sand grains using discrete element method. Ph.D. thesis, University of South Florida

  7. Dong H, Blunt MJ (2009) Pore-network extraction from micro-computerized-tomography images. Phys Rev E 80(3):036307

    Article  Google Scholar 

  8. Gao S, Meegoda JN, Hu L (2012) Two methods for pore network of porous media. Int J Numer Anal Methods Geomech 36(18):1954–1970

    Article  Google Scholar 

  9. Homberg U, Baum D, Prohaska S, Kalbe U, Witt K (2012) Automatic extraction and analysis of realistic pore structures from CT data for pore space characterization of graded soil. In: Proceedings of 6th international conference on scour and erosion (ICSE-6), pp 345–352

  10. Indraratna B, Raut AK, Khabbaz H (2007) Constriction-based retention criterion for granular filter design. J Geotech Geoenviron Eng 133(3):266–276

    Article  Google Scholar 

  11. Kenney T, Chahal R, Chiu E, Ofoegbu G, Omange G, Ume C (1985) Controlling constriction sizes of granular filters. Can Geotech J 22(1):32–43

    Article  Google Scholar 

  12. Kenney T, Lau D (1985) Internal stability of granular filters. Can Geotech J 22(2):215–225

    Article  Google Scholar 

  13. Kenney T, Lau D (1986) Internal stability of granular filters: Reply. Can Geotech J 23(3):420–423

    Article  Google Scholar 

  14. Lafleur J, Mlynarek J, Rollin AL (1989) Filtration of broadly graded cohesionless soils. J Geotech Eng 115(12):1747–1768

    Article  Google Scholar 

  15. Li Z, Wang Y, Chow J, Su Z, Li X (2018) 3D pore network extraction in granular media by unifying the Delaunay tessellation and maximal ball methods. J Pet Sci Eng 167:692–701

    Article  Google Scholar 

  16. Lindow N, Baum D, Hege HC (2011) Voronoi-based extraction and visualization of molecular paths. IEEE Trans Vis Comput Graph 17(12):2025–2034

    Article  Google Scholar 

  17. Locke M, Indraratna B, Adikari G (2001) Time-dependent particle transport through granular filters. J Geotech Geoenviron Eng 127(6):521–529

    Article  Google Scholar 

  18. Marot D, Rochim A, Nguyen HH, Bendahmane F, Sibille L (2016) Assessing the susceptibility of gap-graded soils to internal erosion: proposition of a new experimental methodology. Nat Hazards 83(1):365–388

    Article  Google Scholar 

  19. O’Sullivan C, Bluthé J, Sejpar K, Shire T, Cheung L (2015) Contact based void partitioning to assess filtration properties in DEM simulations. Comput Geotech 64:120–131

    Article  Google Scholar 

  20. Reboul N, Vincens E, Cambou B (2008) A statistical analysis of void size distribution in a simulated narrowly graded packing of spheres. Granul Matter 10(6):457–468

    Article  Google Scholar 

  21. Reboul N, Vincens E, Cambou B (2010) A computational procedure to assess the distribution of constriction sizes for an assembly of spheres. Comput Geotech 37(1–2):195–206

    Article  Google Scholar 

  22. Schuler U (1996) Scattering of the composition of soils—an aspect for the stability of granular filters. Geofilters, vol 96. Bitech Publications, Montreal, pp 21–34

    Google Scholar 

  23. Seblany F (2018) Filter criterion for granular soils based on the constriction size distribution. Ph.D. thesis, Ecole Centrale de Lyon

  24. Seblany F, Homberg U, Vincens E, Winkler P, Witt K (2018) Merging criteria for defining pores and constrictions in numerical packing of spheres. Granul Matter 20(3):37

    Article  Google Scholar 

  25. Sherard JL, Dunnigan LP, Talbot JR (1984) Basic properties of sand and gravel filters. J Geotech Eng 110(6):684–700

    Article  Google Scholar 

  26. Shire T, O’Sullivan C (2016) Constriction size distributions of granular filters: a numerical study. Géotechnique 66(10):826–839

    Article  Google Scholar 

  27. Shire T, O’Sullivan C (2017) A network model to assess base-filter combinations. Comput Geotech 84:117–128

    Article  Google Scholar 

  28. Silin D, Jin G, Patzek T (2004) Robust determination of the pore space morphology in sedimentary rocks. J Pet Technol 56(5):69–70

    Article  Google Scholar 

  29. Silveira A (1965) An analysis of the problem of washing through in protective filters. In: Proceedings of the sixth international conference on soil mechanics and foundation engineering, vol 2, pp 551–555

  30. Sufian A, Russell A, Whittle A, Saadatfar M (2015) Pore shapes, volume distribution and orientations in monodisperse granular assemblies. Granul Matter 17(6):727–742

    Article  Google Scholar 

  31. Šmilauer V et al (2015) Yade Documentation 2nd ed. The Yade Project. https://doi.org/10.5281/zenodo.34073.

  32. The CGAL Project: CGAL User and Reference Manual, 4.14.1 edn. CGAL Editorial Board (2019). https://doc.cgal.org/4.14.1/Manual/packages.html

  33. van der Linden JH, Sufian A, Narsilio GA, Russell AR, Tordesillas A (2018) A computational geometry approach to pore network construction for granular packings. Comput Geosci 112:133–143

    Article  Google Scholar 

  34. Vincens E, Witt K, Homberg U (2015) Approaches to determine the constriction size distribution for understanding filtration phenomena in granular materials. Acta Geotechnica 10(3):291–303

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge Prof. Eric Vincens and Dr. Feda Seblany at Ecole Centrale de Lyon for valuable discussion about the \(\mathrm {L}_1\) and \(\mathrm {L}_2\) criteria and for having provided some data so that the authors could validate the implementation of these criteria in their own code. This work was partially supported by Cedre program of the French and Lebanese scientific cooperation (Grant No. 40188UD).

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Correspondence to Ngoc-Son Nguyen.

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Nguyen, NS., Taha, H. & Marot, D. A new Delaunay triangulation-based approach to characterize the pore network in granular materials. Acta Geotech. 16, 2111–2129 (2021). https://doi.org/10.1007/s11440-021-01157-1

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