Skip to content

Comparison of Prediction Models for the Permeability of Granular Materials Using a Database

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Original languageEnglish
Title of host publicationContemporary Issues in Soil Mechanics
Subtitle of host publicationProceedings of the 2nd GeoMEast International Congress and Exhibition on Sustainable Civil Infrastructures, Egypt 2018 – The Official International Congress of the Soil-Structure Interaction Group in Egypt (SSIGE)
EditorsSayed Hemeda, Mounir Bouassida
Publisher or commissioning bodySpringer, Cham
Number of pages13
ISBN (Electronic)9783030019419
ISBN (Print)9783030019402
DateAccepted/In press - 19 Jul 2018
DateE-pub ahead of print - 28 Oct 2018
DatePublished (current) - 2019

Publication series

NameSustainable Civil Infrastructures
PublisherSpringer, Cham
ISSN (Print)2366-3405


The hydraulic conductivity characteristics of the materials which comprise pavement structures are linked to in service performance. This paper briefly reviews a series of well-known models to predict hydraulic conductivity. An approach which makes use of the grading entropy coordinates is also studied. The database includes information on the gradation, hydraulic conductivity and porosity characteristics for over 150 gravel mixtures. Comparison of the studied models reveals that the ‘Kozeny-Carman’ model gives the best predictions when considering the entire database. The results of the regression analysis reveal that for granular mixtures comprising greater than 50% sand, the ‘Shepherd’ or ‘Hazen’ approaches may be preferred. However, for mixtures comprising less than with 50% sand, the ‘KozenyCarman’ and ‘grading entropy’ approaches are preferred.

Download statistics

No data available



  • Full-text PDF (accepted author manuscript)

    Rights statement: This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Springer at . Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 1.24 MB, PDF document


View research connections

Related faculties, schools or groups