• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.761-768
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• 2008

This paper presents the results of a laboratory study on the thermal conductivity of sand(silica, quartzite, limestone, sandstone, granite and masonry sand)-water mixtures used in ground heat exchanger backfilling materials. Nearly 260 tests were performed in a thermal conductivity measuring system to characterize the relationships between the thermal conductivity of mixtures and the water content. The experimental results show that the thermal conductivity of mixtures increases with increasing dry density and with increasing water content. The most widely used empirical prediction models for thermal conductivity of soils were found inappropriate to estimate the thermal conductivity of unsaturated sand-water mixtures. An improved model using a exponential relationship to compute the thermal conductivity of dry sands and empirical relationship to assess the normalized thermal conductivity of unsaturated sand-water mixtures is presented.

• Journal of Korea Water Resources Association
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• v.41 no.6
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• pp.565-574
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• 2008

Fire-enhanced soil hydrophobicity often increases runoff and erosion in the mountain hillslope following severe wildfires. Estimation techniques for WEPP's parameters were studied in burnt mountain slopes. In burnt mountain slopes, the model over-predicted runoff in the small runoff and under-predicted runoff in the great runoff, and in the lower sediment runoff it had a tendency to over-predict soil loss. The effective hydraulic conductivity was most sensitive in the WEPP's runoff and its sediment runoff was mainly effected by the effective hydraulic conductivity, initial saturation, rill erodibility, and interrill erodibility. To improve the applicability of the WEPP, the adjustment coefficient of effective hydraulic conductivity was defined for runoff and the adjustment coefficient of rill erodibility and interrill erodibility was presented for sediment runoff. The adjustment coefficient of effective hydraulic conductivity in wildfire mountain slopes increased with maximum rainfall intensity of single storm and the vegetation height index. The adjustment coefficients of rill erodibility depended on soil components of size distribution curve and total rainfall depths in single storm. The adjustment coefficients of interrill erodibility decreased with increases of maximum rainfall intensity and vegetation height index. These results may be used in the application of WEPP model for wildfire mountain slopes.

• Advances in nano research
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• v.1 no.3
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• pp.171-182
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• 2013

The alternating current (AC) conductivity in semiconductor crystals with an open-core screw dislocation is studied in the current work. The screw dislocation in crystalline media results in an effective potential field which affects the electronic transport properties of the system. Therefore, from a technological view point, it is interesting to investigate properties of AC conductivity at frequencies of a few terahertz. To quantify the screw-induced potential effect, we calculated the AC conductivity of dislocated crystals using the Kubo formula. The conductivity showed peaks within the terahertz frequency region, where the amplitude of the AC conductivity was large enough to be measured in experiments. The measurable conductivity peaks did not arise in dislocation-free crystals threaded by a magnetic flux tube. These results imply different conductivity mechanisms in crystals with a screw dislocation than those threaded by a magnetic flux tube, despite the apparent similarity in their electronic eigenstates.

• Journal of the Korean Geotechnical Society
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• v.29 no.1
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• pp.93-107
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• 2013

Thermal conduction of the particulate composites or granular materials can be widely used in porous materials and geotechnical engineering. And it has continued to develop "effective thermal conductivity" of medium by modeling energy relationship among particles in medium. This study focuses on the development of the effective thermal conductivity at the unsaturated conditions of soils using the modified network model approach assisted by synthetic 3D random packed systems (DEM method, Discrete Element Method) at the particle scale. To verify the network model, three kinds of glass beads and the Jumunjin sand are used to obtain experimental values at various unsaturated conditions. The PPE (Pressure Plate Extractor) test is then performed to obtain SWCC (Soil-Water Characteristic Curve) of soil samples. In the modified network model, SWCC is used to adjust the equivalent radius of thermal cylinder at contact area between particles. And cutoff range parameter to define the effective zone is also adjusted according to the SWCC at given conditions. From a series of laboratory tests and the proposed network model, the modified network model which adopts a SWCC shows a good agreement in modeling thermal conductivity of granular soils at given conditions. And an empirical correlation between the fraction of the mean radius (${\chi}$) and thermal conductivity at given saturated condition is provided, which can be used to expect thermal conductivity of the granular soils, to estimate thermal conductivity of granular soils.

• International Journal of Concrete Structures and Materials
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• v.6 no.3
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• pp.177-186
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• 2012

The temperature distributions of concrete structures strongly depend on the value of thermal conductivity of concrete. However, the thermal conductivity of concrete varies according to the composition of the constituents and the temperature and moisture conditions of concrete, which cause difficulty in accurately predicting the thermal conductivity value in concrete. For this reason, in this study, back-propagation neural network models on the basis of experimental values carried out by previous researchers have been utilized to effectively account for the influence of these variables. The neural networks were trained by 124 data sets with eleven parameters: nine concrete composition parameters (the ratio of water-cement, the percentage of fine and coarse aggregate, and the unit weight of water, cement, fine aggregate, coarse aggregate, fly ash and silica fume) and two concrete state parameters (the temperature and water content of concrete). Finally, the trained neural network models were evaluated by applying to other 28 measured values not included in the training of the neural networks. The result indicated that the proposed method using a back-propagation neural algorithm was effective at predicting the thermal conductivity of concrete.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3860-3865
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• 2023

A metallic microcell UO₂ pellet has a microstructure where a metal wall is connected to overcome the low thermal conductivity of the UO₂ fuel pellet. It has been verified that metallic microcell fuel pellets provide an impressive reduction of the fuel centerline temperature through a Halden irradiation test. However, it is difficult to predict the effective thermal conductivity of these pellets and researchers have had to rely on measurement and use of the finite element method. In this study, we designed a unit microcell model using a thermal resistance circuit to calculate the effective thermal conductivity on the basis of the microstructure characteristics by using the aspect ratio and compared the results with those of reported metallic UO₂ microcell pellets. In particular, using the thermal conductivity calculated by our model, the fuel centerline temperature of Cr microcell pellets on the 5th day of the Halden irradiation test was predicted within 6% error from the measured value.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.315-321
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• 2012

In this study, a sequential multiscale homogenization method to characterize the effective thermal conductivity of nano particulate polymer nanocomposites is proposed through a molecular dynamics(MD) simulations and a finite element-based homogenization method. The thermal conductivity of the nanocomposites embedding different-sized nanoparticles at a fixed volume fraction of 5.8% are obtained from MD simulations. Due to the Kapitza thermal resistance, the thermal conductivity of the nanocomposites decreases as the size of the embedded nanoparticle decreases. In order to describe the nanoparticle size effect using the homogenization method with accuracy, the Kapitza interface in which the temperature discontinuity condition appears and the effective interphase zone formed by highly densified matrix polymer are modeled as independent phases that constitutes the nanocomposites microstructure, thus, the overall nanocomposites domain is modeled as a four-phase structure consists of the nanoparticle, Kapitza interface, effective interphase, and polymer matrix. The thermal conductivity of the effective interphase is inversely predicted from the thermal conductivity of the nanocomposites through the multiscale homogenization method, then, exponentially fitted to a function of the particle radius. Using the multiscale homogenization method, the thermal conductivities of the nanocomposites at various particle radii and volume fractions are obtained, and parametric studies are conducted to examine the effect of the effective interphase on the overall thermal conductivity of the nanocomposites.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.19 no.3
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• pp.331-338
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• 2021

Extensive studies have been conducted on thermal conductivity of bentonite buffer materials, as it affects the safety performance of barriers engineered to contain high-level radioactive waste. Bentonite is composed of several minerals, and studies have shown that the difference in the thermal conductivity of bentonites is due to the variation in their mineral composition. However, the specific reasons contributing to the difference, especially with regard to the thermal conductivity of bentonites with similar mineral composition, have not been elucidated. Therefore, in this study, bentonites with significantly different thermal conductivities, but of similar mineral compositions, are investigated. Most bentonites contain more than 60% of montmorillonite. Therefore, it is believed that the exchangeable cations of montmorillonite could affect the thermal conductivity of bentonites. The effect of bentonite type was comparatively analyzed and was verified through the effective medium model for thermal conductivity. Our results show that Ca-type bentonites have a higher thermal conductivity than Na-type bentonites.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.5
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• pp.241-246
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• 2015

Cellular foamed insulation such as polyurethane foam ages and degrades the thermal conductivity. Aging of foam is a result from the diffusion of gases, initially consisting of $CO_2$ but eventually replaced by air from the environment. The variation of the cell gas content with time is primarily influenced by the increase of thermal conductivity of the cellular foam. The weight of foam also changes as the gas diffuses and exchanges. In this study, a weight measurement method has been proposed to evaluate the effective diffusion coefficients of $CO_2$ and Air, $D_{CO2}=7.08504E-11$ and $D_{air}=4.86086E-12$, respectively and are compared with the gas analysis method.

• Journal of Power System Engineering
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• v.10 no.4
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• pp.133-138
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• 2006

Effective thermal conductivity of particulate reinforced composite has been predicted by Eshelby's equivalent inclusion method modified with Mori-Tanaka's mean field theory. The predicted results are compared with the experimental results from the literature. The model composite is polymer matrix filled with ceramic particles such as silica, alumina, and aluminum nitride. The preliminary examination by Eshelby type model shows that the predicted results are in good agreements with the experimental results for the composite with perfect spherical filler. As the shape of filler deviates from the perfect sphere, the predicted error increases. By using the aspect ratio of the filler deduced from the fixed filler volume fraction of 30%, the predicted results coincide well with the experimental results for filler volume fraction of 40% or less. Beyond this fraction, the predicted error increases rapidly. It can be finally concluded from the study that Eshelby type model can be applied to predict the thermal conductivity of the particulate composite with filler volume fraction less than 40%.