z-logo
Premium
Using Grain‐Size Distribution Methods for Estimation of Air Permeability
Author(s) -
Wang Tiejun,
Huang Yuanyang,
Chen Xunhong,
Chen Xi
Publication year - 2015
Publication title -
groundwater
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 94
eISSN - 1745-6584
pISSN - 0017-467X
DOI - 10.1111/gwat.12323
Subject(s) - soil science , terzaghi's principle , hydraulic conductivity , sediment , grain size , permeability (electromagnetism) , correlation coefficient , mathematics , air permeability specific surface , hydrology (agriculture) , environmental science , mineralogy , geology , statistics , geotechnical engineering , materials science , soil water , chemistry , geomorphology , composite material , pore water pressure , biochemistry , membrane , layer (electronics)
Knowledge of air permeability ( k a ) at dry conditions is critical for the use of air flow models in porous media; however, it is usually difficult and time consuming to measure k a at dry conditions. It is thus desirable to estimate k a at dry conditions from other readily obtainable properties. In this study, the feasibility of using information derived from grain‐size distributions ( GSDs ) for estimating k a at dry conditions was examined. Fourteen GSD ‐based equations originally developed for estimating saturated hydraulic conductivity were tested using k a measured at dry conditions in both undisturbed and disturbed river sediment samples. On average, the estimated k a from all the equations, except for the method of Slichter, differed by less than ± 4 times from the measured k a for both undisturbed and disturbed groups. In particular, for the two sediment groups, the results given by the methods of Terzaghi and Hazen‐modified were comparable to the measured k a . In addition, two methods (e.g., Barr and Beyer) for the undisturbed samples and one method (e.g., Hazen‐original) for the undisturbed samples were also able to produce comparable k a estimates. Moreover, after adjusting the values of the coefficient C in the GSD ‐based equations, the estimation of k a was significantly improved with the differences between the measured and estimated k a less than ±4% on average (except for the method of Barr). As demonstrated by this study, GSD ‐based equations may provide a promising and efficient way to estimate k a at dry conditions.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom