Generalized relationship for determining soil electrical resistivity from its thermal resistivity

Sreedeep, S.; Reshma, A C; Singh, Devendrá

doi:10.1016/j.expthermflusci.2004.04.001

Cited by 48 publications

(33 citation statements)

References 12 publications

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“…This may be due to the improvement in contact between soil particles which leads to better conduction of heat. This agrees with previous works reported by literatures [26,[37][38][39]. Table 2 have been used to establish the influence of porosity of the soil on its thermal resistivity as depicted in Figure 9.…”

Section: Degree Of Saturationsupporting

confidence: 80%

In Situ Determination of Thermal Resistivity of Soil: Case Study of Olorunsogo Power Plant, Southwestern Nigeria

Oladunjoye

Sanuade

2012

ISRN Civil Engineering

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This study measured in situ the thermal resistivity of soils at Olorunsogo Gas Turbine Power Station (335 MW Phase 1) which is located in Ogun State, Southwestern Nigeria. Ten pits, each of about 1.5 m below the ground surface, were established in and around the power plant in order to measure the thermal resistivity of soils in situ. A KD 2-Pro was used for the in situ measurement of thermal properties. Samples were also collected from the ten pits for laboratory determination of the physical parameters that influence thermal resistivity. The samples were subjected to grain size distribution analysis, compaction, specific gravity and porosity tests, moisture content determination, and XRD analysis. Also, thermal resistivity values were calculated by an algorithm using grain size distribution, dry density, and moisture content for comparison with the in situ values. The results show that thermal resistivity values range from 34.07 to 71.88 • C-cm/W with an average of 56.43 • C-cm/W which falls below the permissible value of 90 • C-cm/W for geomaterials. Also, the physical parameters such as moisture content, porosity, degree of saturation, and dry density vary from 13.00 to 16.20%, 39.74 to 45.64%, 40.72 to 63.52%, and 1725.05 to 1930.00 Kg/m 3 , respectively. The temperature ranges from 28.92 to 35.39 • C with an average of 32.11 • C in the study area. The calculated thermal resistivity from an algorithm was found to vary from 48.43 to 81.22 • C-cm/W with an average of 65.56 • C-cm/W which is close to the thermal resistivity values measured in situ. Good correlation exists between the in situ thermal resistivity and calculated thermal resistivity with R = +0.85 suggesting that both methods are reliable.

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Section: Degree Of Saturationsupporting

confidence: 80%

In Situ Determination of Thermal Resistivity of Soil: Case Study of Olorunsogo Power Plant, Southwestern Nigeria

Oladunjoye

Sanuade

2012

ISRN Civil Engineering

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“…Z ¼ h 0:02 þ 0:0006 Â e ðF=25Þ i (6) Though, the utility and efficiency of these relationships was demonstrated by Sreedeep et al [18], these relationships are derived based on simple interpolation and extrapolation of experimental results obtained by testing different types of locally available soils compacted at different densities and moisture content. Hence, in order to generate much confidence in using these relationships, better computational algorithms (viz., artificial neural networks) that are capable of incorporating the interdependence of several parameters must be employed.…”

Section: Introductionmentioning

confidence: 98%

“…(2) does not take into account the saturation, S r , of the soil, which influences both R E and R T [18], quite substantially. To overcome this limitation, Sreedeep et al [18] proposed Eq. (3).…”

Section: Introductionmentioning

confidence: 99%

Artificial neural network models for predicting electrical resistivity of soils from their thermal resistivity

Erzin

Rao

Patel

et al. 2010

International Journal of Thermal Sciences

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“…Several similar approaches have been carried out (Liu et al, 2013;Logsdon et al, 2010;Rhoades et al, 1976;Singh et al, 2001;Sreedeep et al, 2005). Many approaches had their focus on one soil type like clay (Giao et al, 2003;Kaufhold et al, 2014) or on the heat propagation within porous media and usually the analyses are carried out only in dependence of the water content (Giordano et al, 2013).…”

Section: (10)mentioning

confidence: 99%

“…Most of the mentioned soil parameters like mineralogy, grain size distribution, soil moisture, and bulk density are affecting thermal and electrical conductivity (Logsdon et al, 2010;Sreedeep et al, 2005). In this context Singh et al (2001) expressed a general relationship Eq.…”

Section: Introductionmentioning

confidence: 99%

Laboratory device to analyse the impact of soil properties on electrical and thermal conductivity

Bertermann¹,

Schwarz²

2017

International Agrophysics

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Gathering information about soil properties in an efficient way is essential for many soil applications also for very shallow geothermal systems (e.g. collector systems or heat baskets). In the field, electrical resistivity tomogramphy measurements enable non-invasive and extensive analyses regarding the determination of soil properties. For a better understanding of measured electrical resistivity values in relation to soil properties within this study, a laboratory setup was developed. The structure of this laboratory setup is geared to gather electrical resistivity or rather electrical conductivity values which are directly comparable to data measured in the field. Within this setup grain size distribution, moisture content, and bulk density, which are the most important soil parameters affecting the electrical resistivity, can be adjusted. In terms of a better estimation of the geothermal capability of soil, thermal conductivity measurements were also implemented within the laboratory test sequence. The generated data reveals the serious influence of the water content and also provides a huge impact of the bulk density on the electrical as well as on the thermal conductivity. Furthermore, different behaviour patterns of electrical and thermal conductivity in their particular relation to the different soil parameters could be identified.

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Generalized relationship for determining soil electrical resistivity from its thermal resistivity

Cited by 48 publications

References 12 publications

In Situ Determination of Thermal Resistivity of Soil: Case Study of Olorunsogo Power Plant, Southwestern Nigeria

In Situ Determination of Thermal Resistivity of Soil: Case Study of Olorunsogo Power Plant, Southwestern Nigeria

Artificial neural network models for predicting electrical resistivity of soils from their thermal resistivity

Laboratory device to analyse the impact of soil properties on electrical and thermal conductivity

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