Spectral Analysis of the Response of Coarse Granular Material to Dynamic Penetration Test Modelled with DEM

  • Quoc Anh Tran
  • Bastien ChevalierEmail author
  • Pierre Breul
Original Paper


Dynamic penetration tests are often used to determine the strength properties of surface soils. The paper presents a study on the use of spectral analysis on dynamic cone penetration tests results, modelled with discrete element method. This method is applied to assess the effect of the variation of the grain size distribution of the soil on test results. A two-dimensional discrete model is used to reproduce cone penetration tests in dynamic conditions: the tip of the penetrometer is driven in the material by successive impacts of a hammer on the penetrometer. For each impact of the hammer, a curve of the load applied by the tip on the soil is obtained versus the penetration distance of the tip. The curves of the load versus penetration traditionally used to calculate the tip resistance of the soil are analyzed with discrete Fourier transform in order to investigate curve’s shape. The effect of the variation of the grain size distribution of the soil on these curves is investigated, i.e. average particle diameter and span of particle size distribution. It was found out that the grain size distribution influences tip resistance but also the shape and oscillation modes of the curve of the stress–penetration curve. Based on these indicators, the exploitation of the load–displacement curve obtained with dynamic penetration tests could be enlarged to determine other properties of the soils.


Dynamic cone penetration Discrete element method Granular material Particle size distribution Discrete Fourier transform 


  1. 1.
    Chaigneau L (2001) Caractérisation des milieux granulaires de surface à l’aide d’un pénétromètre. PhD thesis, Université Blaise Pascal, Clermont-FerrandGoogle Scholar
  2. 2.
    Breul P, Benz M, Gourvès R, Saussine G (2009) Penetration test modelling in a coarse granular medium. In: Powders and grains 2009: proceedings of the 6th international conference on micromechanics of granular media, 1145(1), pp 173–176. AIP PublishingGoogle Scholar
  3. 3.
    Benz Navarrete M (2009) Mesures dynamiques lors du battage du pénétromètre Panda 2. PhD thesis, Université Blaise Pascal, Clermont-FerrandGoogle Scholar
  4. 4.
    Escobar E, Benz Navarrete M, Gourvès R, Haddani Y, Breul P, Chevalier B (2016) Dynamic characterization of the supporting layers in railway tracks using the dynamic penetrometer Panda 3®. Procedia Eng 143:1024–1033. CrossRefGoogle Scholar
  5. 5.
    Benz MA, Escobar E, Gourvès R, Haddani Y, Breul P, Bacconnet C (2013) Dynamic measurements of the penetration test—determination of the tip’s dynamic load penetration curve. In: Proceedings of the 18th international conference on soil mechanics and geotechnical engineering, Paris, pp 499–502Google Scholar
  6. 6.
    Escobar Valencia EJ (2015) Mise au point et exploitation d’une nouvelle technique pour la reconnaisance des sols: le PANDA 3. PhD thesis, Université Blaise Pascal, Clermont-FerrandGoogle Scholar
  7. 7.
    Tran QA, Chevalier B, Breul P (2016) Discrete modeling of penetration tests in constant velocity and impact conditions. Comput Geotech 71:12–18CrossRefGoogle Scholar
  8. 8.
    Huang AB, Ma MY (1994) An analytical study of cone penetration test in granular material. Can Geotech J 31(1):91–103CrossRefGoogle Scholar
  9. 9.
    Huang AB, Hsu HH (2004) Advanced calibration chambers for cone penetration testing in cohesionless soils. In: ISC-2 geotechnical and geophysical site characterization, Porto, pp 147–166Google Scholar
  10. 10.
    Calvetti F, Nova R (2005) Micro–macro relationships from DEM simulated element and in-situ tests. In: Proceedings of the 5th international conference on micromechanics of granular media: powders and grains 2005, Stuttgart, pp 245–250Google Scholar
  11. 11.
    Jiang MJ, Yu H-S, Harris D (2006) Discrete element modeling of deep penetration in granular soils. Int J Numer Anal Methods Geomech 30(4):335–361CrossRefGoogle Scholar
  12. 12.
    Jiang MJ, Harris D, Zhu H (2007) Future continuum models for granular materials in penetration analyses. Granul Matter 9(1):97–108zbMATHGoogle Scholar
  13. 13.
    Jiang M, Dai Y, Cui L, Shen Z, Wang X (2014) Investigating mechanism of inclined CPT in granular ground using DEM. Granul Matter 16(5):785–796CrossRefGoogle Scholar
  14. 14.
    Tran QA, Chevalier B, Breul P (2015) A numerical study of the penetration test at constant rod velocity. In: Oka F, Murakami A, Uzuoka R, Kimoto S (eds) Computer methods and recent advances in geomechanics, Kyoto, pp 193–198Google Scholar
  15. 15.
    Janda A, Ooi JY (2015) DEM modeling of cone penetration and unconfined compression in cohesive solids. Powder Technol. CrossRefGoogle Scholar
  16. 16.
    Arroyo M, Butlanska J, Gens A, Calvetti F, Jamiolkowski M (2011) Cone penetration tests in a virtual calibration chamber. Géotechnique 61(6):525–531CrossRefGoogle Scholar
  17. 17.
    Butlanska J, O’Sullivan C, Arroyo M, Gens A, Jiang M, Liu F, Bolton M (2011) Mapping deformation during CPT in a virtual calibration chamber. In: Proceedings of the international symposium on geomechanics and geotechnics: from micro to macro. Taylor & Francis Group, pp 559–564Google Scholar
  18. 18.
    McDowell GR, Falagush O, Yu HS (2012) A particle refinement method for simulating DEM of cone penetration testing in granular materials. Geotech Lett 2:141–147CrossRefGoogle Scholar
  19. 19.
    Quezada JC, Breul P, Saussine G, Radjai F (2014) Penetration test in coarse granular material using contact dynamics method. Comput Geotech 55:248–253CrossRefGoogle Scholar
  20. 20.
    Ciantia MO, Arroyo M, Butlanska J, Gens A (2016) DEM modelling of cone penetration tests in a double-porosity crushable granular material. Comput Geotech 73:109–127CrossRefGoogle Scholar
  21. 21.
    Cundall PA, Strack ODL (1979) A discrete numerical model for granular assemblies. Géotechnique 29(1):47–65CrossRefGoogle Scholar
  22. 22.
    Combe G (2002) Mécanique des matériaux granulaires et origines microscopiques de la déformation. Etudes et Recherches du Laboratoire Central des Ponts et Chaussées. SI8Google Scholar
  23. 23.
    Roux J-N, Chevoir F (2005) Discrete numerical simulation and the mechanical behavior of granular materials. Bulletin du Laboratoire des Ponts et Chaussées 254:109–138Google Scholar
  24. 24.
    Tran QA (2015) Modélisation numérique du comportement des milieux granulaires à partir de signaux pénétrométriques: approche micromécanique par la méthode des éléments discrets. PhD thesis, Université Blaise Pascal, Clermont-Ferrand IIGoogle Scholar

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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Université Clermont Auvergne, CNRS, SIGMA Clermont, Institut PascalClermont-FerrandFrance

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