Using Grain‐Size Distribution Methods for Estimation of Air Permeability. Issue 1 (9th February 2015)

• Record Type: Journal Article
• Authors: Wang, Tiejun; Huang, Yuanyang; Chen, Xunhong; Chen, Xi
• Is Part Of: Ground water. Volume 54:Issue 1(2016:Jan./Feb.)
• Page Start: 131
• Page End: 142
• Publication Date: 2015-02-09
• Subjects: Groundwater -- Periodicals; Wells -- Periodicals; Eau souterraine -- Périodiques; Puits -- Périodiques; Grondwater; Eau souterraine; Puits; Electronic journals; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 551.49
• DOI: 10.1111/gwat.12323
• Languages: English
• ISSNs: 0017-467X

Abstract

Abstract: Knowledge of air permeability ( ka ) 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 ka at dry conditions. It is thus desirable to estimate ka at dry conditions from other readily obtainable properties. In this study, the feasibility of using information derived from grain‐size distributions (GSDs) for estimating ka at dry conditions was examined. Fourteen GSD‐based equations originally developed for estimating saturated hydraulic conductivity were tested using ka measured at dry conditions in both undisturbed and disturbed river sediment samples. On average, the estimated ka from all the equations, except for the method of Slichter, differed by less than ± 4 times from the measured ka 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 ka . 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 ka estimates. Moreover, after adjusting the values of the coefficient C in the GSD‐based equations, the estimation of ka was significantly improved with the differences between the measured and estimated ka 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 ka at dry conditions.