Heat Transfer Model for Predicting Thermal Conductivity of Highly Compacted Bentonite.

Sakashita, Hiroto; Kumada, Toshiaki

doi:10.3327/jaesj.40.235

Cited by 20 publications

(15 citation statements)

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“…The dependences of the thermal conductivity on temperature, moisture and porosity are not contained in the thermal conductivity synchronously as a function of these variables [1][2][3][4][5][6][7][8][9][10][11]. In addition, most of these simple models are empirical relations whose validities are limited to certain ranges of saturation.…”

Section: Introductionmentioning

confidence: 99%

An effective thermal conductivity model of geological porous media for coupled thermo-hydro-mechanical systems with multiphase flow

Tong¹,

Jing²,

Zimmerman³

2009

International Journal of Rock Mechanics and Mining Sciences

139

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Section: Introductionmentioning

confidence: 99%

An effective thermal conductivity model of geological porous media for coupled thermo-hydro-mechanical systems with multiphase flow

Tong¹,

Jing²,

Zimmerman³

2009

International Journal of Rock Mechanics and Mining Sciences

139

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“…Johansen (1975) . They compared their model with Sakashita and Kumada (1998) who proposed empirical equations for thermal conductivity as a function of saturation and porosity.…”

Section: Statistical Comparison Of Thermal Conductivity Measurements mentioning

confidence: 99%

“…A summary of the bias statistics appears in Table 5 (2008), and Sakashita and Kumada (1998) thermal conductivity models. Although dense backfill only includes 5% of bentonite in its composition, thermal conductivity models developed for bentonite are included in the comparisons.…”

Section: Statistical Comparison Of Thermal Conductivity Measurements mentioning

confidence: 99%

“…Similar to Figure 12, thermal conductivity measurements were compared to predicted values and bias statistics were generated (equations [5] and (2008), and Sakashita and Kumada (1998) are used in the statistical comparison. Table 4 includes a summary of the equations used in the thermal conductivity models and the inputs.…”

Section: Statistical Comparison Of Thermal Conductivity Measurements mentioning

confidence: 99%

“…Estimations consisted of a series of sinusoidal curves for thermal conductivity and specific heat capacity as a function of degree of saturation. Barry-Macaulay et al (2015) and Tang et al (2008) reviewed an extensive number of thermal conductivity predictions and evaluated selected thermal conductivity models (Johansen 1975;Cote and Konrad 2005;Lu et al 2007;Sakashita and Kumada 1998;among others). Both papers noted the correlation between quartz content and thermal conductivity.…”

Section: R a F Tmentioning

confidence: 99%

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Thermal properties of engineered barriers for a Canadian deep geological repository

Abootalebi

Siemens

2018

Can. Geotech. J.

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Global energy needs continue to rise along with society’s desire for carbon-reduced energy sources to limit climate change effects. One viable carbon-reduced energy source is nuclear power, which provides more than half the electricity requirements of the province of Ontario. Within Canada there are more than 2.5 million bundles of spent nuclear fuel, which will be stored in a deep geological repository. Efficiency of the repository system depends on dissipation of thermal energy. A comprehensive experimental study is presented on thermal properties of barrier materials. The influence of bentonite type, variability, moisture, and temperature on thermal properties is examined. Results show strong influence of moisture on thermal properties, some influence of temperature on low-density bentonite, minor influence of bentonite type, as well as low variability in the experimental measurements. The extensive database of physical measurements is compared with values from the literature and then used to statistically evaluate thermal property models selected from the literature. Using the base parameters from the literature, thermal property models performed adequately; however, soil-specific calibration of the model inputs improved the fit significantly. These results are now available to perform the numerical models for the proposed Canadian deep geological repository for used nuclear fuel.

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Brackish groundwater and reverse osmosis concentrate influence soil physical and thermal properties and pecan evapotranspiration

Ali

Yang

Shukla

2021

Soil Science Soc of Amer J

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The use of brackish groundwater (BGW) to supplement irrigation shortfalls has increased because of decreasing surface water availability in the arid areas of the southern United States. Reuse of reverse osmosis (RO) concentrate, a by-product resulting from desalination of BGW, can increase irrigation portfolio. This 2-yr greenhouse study aimed to quantify changes in physical and thermal soil properties, and evapotranspiration (ET) rate of pecan [Carya illinoinensis (Wangenh.) K. Koch] irrigated with BGW and RO concentrate. Another objective was to predict soil thermal conductivity (K) using soil electrical conductivity (EC) and soil volumetric water content (VWC) data of 2017-2018. Three irrigation water treatments with four replications were prepared namely, control (EC = 0.8 dS m −1 ), BGW (EC = 4.0 dS m −1 ), and RO concentrate (EC = 8.0 dS m −1 ). Soil physical properties determined were texture, moisture content, bulk density, hydraulic conductivity, and moisture retention. Thermal properties measured were conductivity (K), diffusivity (D), resistivity (ρ), and heat capacity (C). The ET and leaching fractions (LF) were determined using water balance. Pecan irrigated with RO concentrate had the lowest ET among irrigation treatments. Soil thermal conductivities and soil water contents in BGW and RO irrigated pots were higher than the control. However, increases in heat capacity with increasing irrigation water salinity were most pronounced. The new four parametersbased model using EC and VWC explained 96% of variability of K (average R 2 = .96, RMSE = 0.096, normalized RMSE [NRMSE] = 11.14%). The sensitivity analysis showed that the contribution of VWC to K was greater than that of EC. Results indicate that continuous irrigation with RO concentrate can be done for up to 1 yr. A new irrigation scheduling protocol based on optimal LF and soil salinity is needed to sustain pecan production in southern New Mexico.

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Heat Transfer Model for Predicting Thermal Conductivity of Highly Compacted Bentonite.

Cited by 20 publications

References 0 publications

An effective thermal conductivity model of geological porous media for coupled thermo-hydro-mechanical systems with multiphase flow

An effective thermal conductivity model of geological porous media for coupled thermo-hydro-mechanical systems with multiphase flow

Thermal properties of engineered barriers for a Canadian deep geological repository

Brackish groundwater and reverse osmosis concentrate influence soil physical and thermal properties and pecan evapotranspiration

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