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.