Void size distribution and hydraulic conductivity of a binary granular soil mixture.

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Title: Void size distribution and hydraulic conductivity of a binary granular soil mixture.
Authors: Chang, C. S.1 (AUTHOR) chang@ecs.umass.edu, Ma, T. T.1 (AUTHOR)
Source: Acta Geotechnica. Apr2024, Vol. 19 Issue 4, p2175-2189. 15p.
Subjects: Potting soils, Hydraulic conductivity, Soil granularity, Porosity, Binary mixtures, Rock permeability
Abstract: Permeability of binary mixtures of soils is important for several industrial and engineering applications. Previous models for predicting the permeability of a binary mixture of soils were primarily developed from Kozeny–Carman equation with an empirical approach. The permeability is predicted based on an equivalent particle size of the two species. This study is aimed to develop a model using a more fundamental approach. Instead of an equivalent particle size, the permeability is predicted based on the bimodal void sizes of the binary mixture. Because the bimodal void sizes are not available as commonly measured physical properties. We first develop an analytical method that has the capability of predicting the bimodal void sizes of a binary mixture. A permeability model is then developed based on the bimodal void sizes of the binary mixture. The developed permeability model is evaluated by comparing the predicted and experimentally measured results for binary mixtures of glass beads, crush sand, and gravel sand. The findings can contribute to a better understanding of the important influence of pore structure on the prediction of permeability. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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Abstract:Permeability of binary mixtures of soils is important for several industrial and engineering applications. Previous models for predicting the permeability of a binary mixture of soils were primarily developed from Kozeny–Carman equation with an empirical approach. The permeability is predicted based on an equivalent particle size of the two species. This study is aimed to develop a model using a more fundamental approach. Instead of an equivalent particle size, the permeability is predicted based on the bimodal void sizes of the binary mixture. Because the bimodal void sizes are not available as commonly measured physical properties. We first develop an analytical method that has the capability of predicting the bimodal void sizes of a binary mixture. A permeability model is then developed based on the bimodal void sizes of the binary mixture. The developed permeability model is evaluated by comparing the predicted and experimentally measured results for binary mixtures of glass beads, crush sand, and gravel sand. The findings can contribute to a better understanding of the important influence of pore structure on the prediction of permeability. [ABSTRACT FROM AUTHOR]
ISSN:18611125
DOI:10.1007/s11440-023-02025-w