Electrical-hydraulic properties of unsaturated Ottawa sands

Gorman, Thomas M.; Kelly, William E.

doi:10.1016/0022-1694(90)90247-u

Cited by 38 publications

(21 citation statements)

References 6 publications

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“…The electrical properties of a sample of the sand was made using a Solartron 1260A Impedance Analyzer. The electrical and microstructural properties of the sand used in this work were found to agree very well with those obtained by Gorman and Kelly [1990] as shown in Table 1. The only slight difference is that in the measured grain diameter (502 μ m for our work and 260 μ m for the “density” grade Ottawa sand used by Gorman and Kelly [1990]).…”

Section: Sample Materialssupporting

confidence: 83%

“…We have taken this value to represent the steady state permeability in the absence of steady state permeability on the sample. It should be noted that our measurement of κ 10 is larger than that obtained by Gorman and Kelly [1990] for Ottawa sand. They actually measured the hydraulic conductivity K of their samples, obtaining K = [4 ± 1] × 10 −4 m/s for their ‘density sand’ when packed to give a porosity of about 0.325, which is equivalent to κ DC = [0.366 ± 0.091] × 10 −10 m 2 when converted to permeability.…”

Section: Sample Materialscontrasting

confidence: 81%

“…They actually measured the hydraulic conductivity K of their samples, obtaining K = [4 ± 1] × 10 −4 m/s for their ‘density sand’ when packed to give a porosity of about 0.325, which is equivalent to κ DC = [0.366 ± 0.091] × 10 −10 m 2 when converted to permeability. In the absence of specific data from Gorman and Kelly [1990] we have used T = 25°C, η f = 0.84 × 10 −4 Pa s, ρ f = 997 kg/m 3 and g = 9.81 m/s 2 to make the conversion. This is a reasonable step as they used slightly saline Nebraska tap water as their fluid at room temperature.…”

Section: Sample Materialsmentioning

confidence: 99%

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Frequency-dependent streaming potential of Ottawa sand

Tardif¹,

Glover²,

Ruel³

2011

J. Geophys. Res.

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[1] The scientific literature is almost devoid of frequency-dependent electrokinetic measurements on geological materials. An apparatus that allows the measurement of the streaming potential coupling coefficient of unconsolidated and disaggregated materials such as sands, gravels, and soils has been designed, constructed, and tested. The apparatus, which uses an electromagnetic drive, operates in the range 1 Hz to 1 kHz and has a 25.4 mm diameter sample chamber for samples up to 150 mm long. We have made streaming potential coupling coefficient measurements on samples of Ottawa sand as a function of frequency. The results have been analyzed using critically and variably damped second-order vibrational mechanics models as well as the theoretical models of Packard for capillary tubes and Pride for porous media. The best fit was provided by an underdamped second-order model with a damping factor of 0.8561 (R 2 = 0.993). Transition frequencies were derived from the two vibrational models and the Pride model either by fitting the model to the data or directly from the model, giving 230, 273, and 256.58 Hz, respectively. These values are in good agreement with the transition frequency expected for a sand with an independently obtained effective pore radius of 6.76 × 10 −5 m from laser diffraction grain size measurements. The Packard model also agrees extremely well with the experimental data (R 2 = 0.987) directly providing a value of the equivalent capillary radius of 6.75 × 10 −5 m that coincides within experimental errors with the independently obtained effective pore radius measurements.

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Section: Sample Materialssupporting

confidence: 83%

Section: Sample Materialscontrasting

confidence: 81%

Section: Sample Materialsmentioning

confidence: 99%

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Frequency-dependent streaming potential of Ottawa sand

Tardif¹,

Glover²,

Ruel³

2011

J. Geophys. Res.

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“…Because of the strong correlations between σ mix and various properties of soils, including mineralogy, cation exchange capacity, grain size distribution, void ratio and water content (AbuHassanein et al, 1996;Archie, 1942;Boudreau, 1996;Campanella and Weemees, 1990;Choo et al, , 2016Fukue et al, 1999;Gorman and Kelly, 1990;Pfannkuch, 1972;Reynolds, 1997;Samouelian et al, 2005;Shen and Chen, 2007;Tiab and Donaldson, 2004;Urish, 1981;Waxman and Smits, 1968), many studies employed the electrical conductivity measurement technique as a quality monitoring tool for landfill barrier systems, including compacted clay liner (AbuHassanein et al, 1996;Kalinski and Kelly, 1994), geosynthetic clay liner (Sirieix et al, 2015), and landfill cover (Carpenter et al, 1991;Genelle et al, 2012). Therefore, the characterization of the impact of organic phase on the measured electrical conductivity of organoclays is important to use organoclays in barriers.…”

Section: Electrical Conductivitymentioning

confidence: 99%

Review of the fundamental geochemical and physical behaviors of organoclays in barrier applications

Zhao

Choo

Bhatt

et al. 2017

Applied Clay Science

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“…It is influenced by several factors such as soil type, pore fluid chemistry, degree of saturation, bulk density, pore structure, and so on (e.g., Kalinski and Kelly 1994;McCarter 1984). Furthermore, the engineering behavior of soil is also comprehensively determined by all these factors (Mitchell and Soga 2005); thus, electrical resistivity can be adopted as an effective tool to study the physical and mechanical properties of soils (Gorman and Kelly 1990;Kibria and Hossain 2012). On the other hand, the electrical resistivity of a soil is very effective in the evaluation of the degree of contamination.…”

Section: Introductionmentioning

confidence: 99%

Electrical resistivity characteristics of diesel oil-contaminated kaolin clay and a resistivity-based detection method

Liu

Cai

et al. 2014

Environ Sci Pollut Res

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As the dielectric constant and conductivity of petroleum products are different from those of the pore water in soil, the electrical resistivity characteristics of oil-contaminated soil will be changed by the corresponding oil type and content. The contaminated soil specimens were manually prepared by static compaction method in the laboratory with commercial kaolin clay and diesel oil. The water content and dry density of the first group of soil specimens were controlled at 10 % and 1.58 g/cm(3). Corresponding electrical resistivities of the contaminated specimens were measured at the curing periods of 7, 14, and 28 and 90, 120, and 210 days on a modified oedometer cell with an LCR meter. Then, the electrical resistivity characteristics of diesel oil-contaminated kaolin clay were discussed. In order to realize a resistivity-based oil detection method, the other group of oil-contaminated kaolin clay specimens was also made and tested, but the initial water content, oil content, and dry density were controlled at 0~18 %, 0~18 %, 1.30~1.95 g/cm(3), respectively. Based on the test data, a resistivity-based artificial neural network (ANN) was developed. It was found that the electrical resistivity of kaolin clay decreased with the increase of oil content. Moreover, there was a good nonlinear relationship between electrical resistivity and corresponding oil content when the water content and dry density were kept constant. The decreasing velocity of the electrical resistivity of oil-contaminated kaolin clay was higher before the oil content of 12 % than after 12 %, which indicated a transition of the soil from pore water-controlled into oil-controlled electrical resistivity characteristics. Through microstructural analysis, the decrease of electrical resistivity could be explained by the increase of saturation degree together with the collapse of the electrical double layer. Environmental scanning electron microscopy (ESEM) photos indicated that the diesel oil in kaolin clay normally had three kinds of effects including oil filling, coating, and bridging. Finally, a resistivity-based ANN model was established based on the database collected from the experiment data. The performance of the model was proved to be reasonably accepted, which puts forward a possible simple, economic, and effective tool to detect the oil content in contaminated clayey soils just with four basic parameters: wet density, dry density, measured moisture content, and electrical resistivity.

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Electrical-hydraulic properties of unsaturated Ottawa sands

Cited by 38 publications

References 6 publications

Frequency-dependent streaming potential of Ottawa sand

Frequency-dependent streaming potential of Ottawa sand

Review of the fundamental geochemical and physical behaviors of organoclays in barrier applications

Electrical resistivity characteristics of diesel oil-contaminated kaolin clay and a resistivity-based detection method

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