Atterberg Limits as Indices of External Surface Areas of Soils

Hammel, J. E.; Sumner, M. E.; Burema, Jiske

doi:10.2136/sssaj1983.03615995004700050047x

Cited by 13 publications

(5 citation statements)

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“…As shown above with particle density, it is well known that clay content, SOM content, and clay mineralogy also strongly infl uence the soil consistency limits, largely by way of their infl uence on the specifi c surface (Hammel et al, 1983;Dolinar et al, 2007). Th ese inter-relationships are clearly shown in Table 2 by the strong correlations involving the consistency limits and both clay and SOM contents, with the exception of w P and clay content.…”

Section: Soil Mechanical Propertiesmentioning

confidence: 81%

Estimating the Particle Density of Clay-rich Soils with Diverse Mineralogy

McBride

Slessor

Joosse

2012

Soil Science Society of America Journal

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Agri-Environment Services Branch, ' • Agriculture and Agri-Food Canada 174 Stone Road West Cuelph, ON, Canada NIC 4S9This study examined the utility of nonlinear regression as a means of developing a statistically-based function for fhe estimation of particle density (Dp) of clay-rich mineral soils where the <0.002 mm fraction was mineralogically diverse. Physical and chemical soil property data (including semi-quantitative clay mineralogy) were analyzed for 54 mineral soil horizons sampled from 18 soil profiles af seven different locations across North America. Plausible estimates of particle density for the mineral component (2.72 Mg m~^), and particularly for the humic component (1.48 Mg m"^), were obtained (r^ = 0.856, root mean square error IRMSE] = 0.035 Mg m"', P < 0.0001) even though fhe calibration data set had a limited range of soil organic matter content (<237o). Particle density was shown to vary with clay content (P < 0.05), and Dp of different mineral particle-size fractions could also be distinguished statistically. The convenient and traditional assumption of Dp = 2.65 Mg m"' for silicate-based soils in the absence of Dp measurements is challenged, given the considerable observed variability in Dp with changes in soil organic matter content and texture.

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Section: Soil Mechanical Propertiesmentioning

confidence: 81%

Estimating the Particle Density of Clay-rich Soils with Diverse Mineralogy

McBride

Slessor

Joosse

2012

Soil Science Society of America Journal

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“…They stated that the external surface of particles, quality of pore water and the valence of exchangeable cation are important factors that influence on the soil plasticity. Hammel et al (1983) presented a relationship between the external surface and Atterberg limits. It can be said that the type of the soil minerals, pore fluid salt concentration and cation valance affect the surface area of soil and thickness of DDL.…”

Section: Discussionmentioning

confidence: 99%

Effect of thermal history on the properties of bentonite

Estabragh

Khosravi²

2016

Environ Earth Sci

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The effect of thermal history on the properties of bentonite was studied through a number of experimental tests. The desired thermal history was created on samples of bentonite by keeping them at a fixed temperature (50, 100, 150, 200 and 250 o C) for a specific duration (3, 7, 14 and 30 days). Standard compaction, Atterberg limits, free swelling and swelling pressure tests were carried out on the samples on the dry side of optimum, optimum and wet side of optimum of the compaction curve with desired thermal history. In addition chemical tests were carried out on the flooding water at the end of the swelling test. The results showed that the changes in compaction characteristics were not considerable but the Atterberg limits, free swelling and swelling pressure of the soil were changed due to the thermal history in comparison with the soil without any thermal history. The magnitudes of free swelling and swelling pressure were dependent on the location of prepared sample on the compaction curve. In addition, the changes in Atteberg limits and swelling parameters (amount of free swelling and swelling pressure) were functions of magnitude of temperature and duration of time that the sample experienced the temperature in its temperature history. The effects of temperature and also duration of exposure of the soil to temperature was discussed with the aid of the Diffuse Double Layer (DDL) theory. It was found that the temperature may change the gradation of soil due to cementation of particles as a result of formation of some salts and oxides that help to paste the particles together and change the properties of the soil.

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“…The physical properties of soil are not isolated and often associated with each other. Many researchers have found that the SSA of clay is closely related to the LL, e.g., finding a linear relationship between the SSA and LL [23,24,[37][38][39][40][41][42] or that the reciprocal of the SSA has a linear relationship with the reciprocal of the LL [21,32,43], and a good power function relationship between the SSA and LL [38,[44][45][46][47]].…”

Section: Definition and Application Of Specific Surface Area (Ssa) Inmentioning

confidence: 99%

Using the Effective Void Ratio and Specific Surface Area in the Kozeny–Carman Equation to Predict the Hydraulic Conductivity of Loess

Hong

Wang

et al. 2019

Water

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Many modified Kozeny-Carman (KC) equations have been used to predict the saturated permeability coefficient (K s ) of porous media in various fields. It is widely accepted that the KC equation applies to sand but does not apply to clay. Little information is available to clarify this point. The effectiveness of the KC equation will be evaluated via laboratory penetration tests and previously published data, which include void ratio, specific surface area (SSA), liquid limit (LL), and permeability coefficient values. This paper demonstrates how to estimate the SSA of cohesive soil from its LL. Several estimation algorithms for determining the effective void ratio (e e ) of cohesive soil are reviewed. The obtained results show that, compared to the KC equation based on porosity and geometric mean particle size (D g ), the KC equation based on the SSA and the e e estimation algorithm can best predict the K s of remolded loess. Finally, issues associated with the predictive power of the KC equation are discussed. Differences between measured and the predicted K s values may be caused by the uniformity of the reconstructed specimen or insufficient control of the test process and errors in the SSA and e e .

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Atterberg Limits as Indices of External Surface Areas of Soils

Cited by 13 publications

References 0 publications

Estimating the Particle Density of Clay-rich Soils with Diverse Mineralogy

Estimating the Particle Density of Clay-rich Soils with Diverse Mineralogy

Effect of thermal history on the properties of bentonite

Using the Effective Void Ratio and Specific Surface Area in the Kozeny–Carman Equation to Predict the Hydraulic Conductivity of Loess

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