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Factors Influencing Water Retention Characteristics of Granular Materials

  • Gilbert J. Kasangaki
  • Gabriela M. Medero
  • Jin Y. Ooi
Conference paper
Part of the Springer Series in Geomechanics and Geoengineering book series (SSGG)

Abstract

Numerous theoretical and experimental attempts have been made to study the influence of moisture on the behaviour of granular materials and to correlate the measured behaviour to the physical properties of the material whilst recognising the effect of its constituent particle properties. At present there seems to be no clear understanding on how these factors individually and collectively influence the unsaturated behaviour. One common approach has been to compare different materials on the basis of particle size and plasticity characteristics but ignore other factors controlling the inter-particle forces such as particle shape, particle interstices and asperities and physico-chemical phenomena. This paper describes an attempt to investigate the effect of particle size on the drying and wetting water retention characteristics for spherical glass beads. Distilled water and spherical glass beads were chosen to provide simple and well defined wet granular assemblies where the observed response can be attributed to purely glass-glass and glass-water interaction without the presence of other complex inter-particle interactions often present in unsaturated soils. The water retention curves were established for 0.09-0.15mm and 0.25-0.50mm particle sizes of similar-material glass beads. The results show that particle-water interaction alone can produce the hysteretic water retention characteristics with particle size significantly affecting the air- and water-entry values and also the wetting maximum water content. In addition, features of the water retention curve often observed in soils were well captured with glass beads.

Keywords

Glass Bead Granular Material Water Retention Unsaturated Soil Liquid Bridge 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Gilbert J. Kasangaki
    • 1
  • Gabriela M. Medero
    • 1
  • Jin Y. Ooi
    • 2
  1. 1.Institute for Infrastructure and EnvironmentHeriot-Watt UniversityEdinburghUK
  2. 2.Institute for Infrastructure and EnvironmentUniversity of EdinburghEdinburghUK

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