Abstract
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 ‘Kozeny-Carman’ and ‘grading entropy’ approaches are preferred.
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Acknowledgements
This first author is grateful for the financial support given by the scholarship from China Scholarship Council (CSC) under the Grant CSC No. 201708060067.
Notation List
The following notations are used in this paper (dimension given in brackets):
A = Relative base entropy;
B = Normalized entropy increment.
CH = Hazen empirical coefficient (Length−1.Time−1);
CHS = Shepherd empirical coefficient;
CK-C= Kozeny-Carman coefficient;
CU= Coefficient of Uniformity, \( C_{U} = \frac{{D_{60} }}{{D_{10} }} \);
\( d_{eff} \) = Representative particle size
D10= Effective particle size, for which 10% of the soil is finer (Length);
e = Void ratio;
k = Coefficient of permeability (Length.Time−1);
K = Intrinsic permeability (Length2);
n = Number of data points;
N = Number of fractions/successively doubled sieves;
p = p-value;
R2= Coefficient of determination;
SA= Specific surface area per unit volume of particles (Length−1);
So= Base entropy;
t = Temperature (in °C)
xi= Relative frequency of fraction i;
\( \gamma \) = Unit weight (Force.Length−3);
\( \mu \) = Dynamic viscosity (Mass.Time−1.Length−1);
\( \rho \) = Density (Mass. Length−3)
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Feng, S., Vardanega, P.J., Ibraim, E. (2019). Comparison of Prediction Models for the Permeability of Granular Materials Using a Database. In: Hemeda, S., Bouassida, M. (eds) Contemporary Issues in Soil Mechanics. GeoMEast 2018. Sustainable Civil Infrastructures. Springer, Cham. https://doi.org/10.1007/978-3-030-01941-9_1
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