Permeability assessment of some granular mixtures

Feng, Shuyin; Vardanega, Paul J.; Ibraim, Erdin; Widyatmoko, Iswandaru; Ojum, Chibuzor

doi:10.1680/jgeot.17.t.039

Cited by 24 publications

(6 citation statements)

References 22 publications

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“…The use of grading entropy in assessing granular physical properties (eg., soil hydraulic conductivity, dry density, soil water retention model parameters [48][49][50][51] is more and more accepted and the measurements related to the statistical relations are worthy to be made on fractal grading curves.…”

Section: 3mentioning

confidence: 99%

The Finite Fractal Distributions as Mean Grain Size Distributions of Granular Matter

Imre,

Pal Singh

2024

Fractal Analysis - Applications and Updates

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The grading entropy is the statistical entropy of the finite discrete grain size distribution on N uniform statistical cells in terms of the N sieve cells, consisting of two terms, the base entropy and the entropy increment (depending on N), which have normalized forms as well (basically independent of N). Being the most adequate statistical variables, both physical phenomena and physical model parameters can be best described by their use. Among others, the normalized base entropy A can be used to measure internal stability, being related to erosion, piping and liquefaction phenomena. Its value classifies the grading curves. Each class (with a fixed value of A) has a mean grading curve with finite fractal distribution, the fractal dimension varies from minus to plus infinity. (These mean gradings indicate a unique relation between the four entropy coordinates and four central moments). The internally stable fractal dimensions - between 2 and 3 – are occurring in nature verifying the internal stability rule of grading entropy. The widespread fractal soils are formed by degradation, which has a directional grading entropy path, with different features in terms of non-normalized and normalized grading entropy coordinates.

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Section: 3mentioning

confidence: 99%

The Finite Fractal Distributions as Mean Grain Size Distributions of Granular Matter

Imre,

Pal Singh

2024

Fractal Analysis - Applications and Updates

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“…The normalised grading entropy coordinates are not unique, zero fractions may change their value, but this is not the case for the non-normalised grading entropy coordinates, which are unique. The normalised and nonnormalised diagram representations are equivalent in case of applying zero fractions up to fixed maximum and minimum diameters [4,17,18]. The representation is simpler and theoretically more precise in the nonnormalized diagram since no zero fractions are needed.…”

Section: Type Of the Entropy Diagrammentioning

confidence: 99%

Soil parameters in terms of entropy coordinates

et al. 2023

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In the ongoing research, an approximate, grading entropy based, advanced interpolation method is applied to establish empirical functions between the grading curves and the model parameters of sands. The space of the grain size distribution curves with N fractions is isomorphic to the space of the unit-sided simplex with dimension N-1. The traditional interpolation over the simplex with dimension N-1 is problematic since the number of the sub-simplexes (and the interpolation points) may increase exponentially with N. To overcome this difficulty, the function is approximately interpolated, which means that the interpolation is made on some 2-dimensional sections of the simplex and is extended to the whole simplex, using the grading entropy map. Two kinds of 2-dimensional sections can be used based on either fractal distributions or partly fractal partly on some maximal gap-graded distributions. In this paper the experiments were made on the artificial mixtures of natural sand grains earlier. Two kinds of functions were approximately interpolated for the minimum dry density using the measured data. One kind of function was determined for the parameters of an SWCC model directly from the level lines previously graphically interpolated from fractal distribution data.

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“…samples: for each average grain size, the measured permeability values increased with gradation, at a ratio ranging from ~ 25 for larger grain sizes to ~ 500 for smaller grain sizes. The influence of this distribution has been considered in the literature in different ways (Wang et al 2017), with the grading entropy being the most widely used in recent decades (Boadu 2000;Lörincz et al 2008;McDougall et al 2013;Feng et al 2018;Arshad et al 2019). To analyse the particular case of drainage packing, the expressions derived by Krumbein and Monk (1942) and Alyamani and Sen (1993) are considered in this study.…”

Section: Estimate Permeability From Granulometric Datamentioning

confidence: 99%

New granulometric expressions for estimating permeability of granular drainages

Díaz-Curiel

Miguel²,

Biosca

et al. 2022

Bull Eng Geol Environ

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This paper describes a new formulation for estimating the permeability of drainages composed of natural sands with no clay content, starting from the parameters obtained from the grain size distribution. The conventional relationships for estimating permeability are functions of granulometric factors and porosity. However, for media typically used as drainage, the grain size grading is a determinant factor, so the porosity dependence can be replaced by a function of the average grain size and grading. The methodology used in this study consists of fitting a set of measured permeability values to a joint expression of the average grain size and the granulometric grading coefficient. To this end, a new effective diameter that can be obtained numerically and graphically is defined, and the permeability relationship is solely dependent on this diameter. To estimate later changes in drainage packing and the consequent variations in porosity, a contrasting modification of the Kozeny–Carman equation is established. This equation considers the grain size grading and is applicable to any granular media.

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Permeability assessment of some granular mixtures

Cited by 24 publications

References 22 publications

The Finite Fractal Distributions as Mean Grain Size Distributions of Granular Matter

The Finite Fractal Distributions as Mean Grain Size Distributions of Granular Matter

Soil parameters in terms of entropy coordinates

New granulometric expressions for estimating permeability of granular drainages

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