Discrete-element modelling of pile penetration to reveal influence of soil characteristics

Gezgin A. T., Soltanbeigi B., Cinicioglu O.

PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-GEOTECHNICAL ENGINEERING, vol.175, no.4, pp.365-382, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 175 Issue: 4
  • Publication Date: 2022
  • Doi Number: 10.1680/jgeen.20.00134
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Communication Abstracts, Compendex, Geobase, ICONDA Bibliographic, INSPEC, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.365-382
  • Keywords: geotechnical engineering, granular materials, piles & piling, CONE PENETRATION, INSTALLATION PROCESS, DEM, BEHAVIOR, SAND, CALIBRATION, DILATANCY, STRENGTH, IMPACT, TESTS
  • Bursa Uludag University Affiliated: No


Soil response to pile penetration has both macro- and micro-mechanical aspects. At both scales, the properties of the particles and their interactions with each other control behaviour. Unfortunately, examination of particle-scale effects during penetration is not possible with either physical modelling or using continuum-based numerical models. The discrete-element method provides a powerful medium for modelling soils as particulate materials and can be used to investigate pile-soil interaction. However, such models are computationally demanding and need extensive optimisation, which in turn requires an understanding of the influences of soil characteristics on the mechanics. For this purpose, a series of pile penetration models was designed using three-dimensional discrete-element models. Structural parameters such as model dimensions and pile properties were kept constant while the soil characteristics were varied one at a time. This allowed uncoupled observation of the influences of individual soil characteristics including stiffness, inter-particle friction, rolling friction, average size, shape, packing density and grain size distribution. The results are presented in graphical form and their implications with respect to modelling are discussed.