• Journal of the Korean Solar Energy Society
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• v.26 no.4
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• pp.1-7
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• 2006

This study is to develop a model to predict the soil temperature variation in Korea Institute of Energy Research using its thermal properties, such as thermal conductivity and diffusivity. Soil depth temperature variation is very important in the design of a proper Ground Source Heat Pump (GSHP) system. This is because the size of the borehole depends on the soil temperature distribution, and this can decrease GSHP system cost. If the thermal diffusivity and thermal conductivity are known, the soil temperature can be predicted by either the Krarti equation or the Spitler equation. Then a comparison with the Krarti equation and Spitler equation data with the real measured data can be performed. Also, the thermal properties can be reasonably approximated by performing a fit of the Krarti and Spitler equations with measured temperature data. This was done and, as a result, the Krarti equation and Spitler equation predicted values very close to the measured data. Although there is about a $0.5^{\circ}C$ difference between the deep subsurface prediction (16m - 60m), with this equation, were expected to have model this Non-Homogeneous Soil Temperature phenomenon properly. So, it has been shown that a prediction of non-homogeneous soil temperature variation influenced by solar radiation can be achieved with a model.

• Progress in Superconductivity and Cryogenics
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• v.16 no.1
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• pp.36-41
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• 2014

Since glass microsphere has high crush strength, low density and small particle size, it becomes alternative thermal insulation material for cryogenic systems, such as storage and transportation tank for cryogenic fluids. Although many experiments have been performed to verify the effective thermal conductivity of microsphere, prediction by calculation is still inaccurate due to the complicated geometries, including wide range of powder diameter distribution and different pore sizes. The accurate effective thermal conductivity model for microsphere is discussed in this paper. There are four mechanisms which contribute to the heat transfer of the evacuated powder: gaseous conduction ($k_g$), solid conduction ($k_s$), radiation ($k_r$) and thermal contact ($k_c$). Among these components, $k_g$ and $k_s$ were calculated by Zehner and Schlunder model (1970). Other component values for $k_c$ and $k_r$, which were obtained from experimental data under high vacuum conditions were added. In this research paper, the geometry of microsphere was simplified as a homogeneous solid sphere. The calculation results were compared with previous experimental data by R. Wawryk (1988), H. S. Kim (2010) and the experiment of this paper to show good agreement within error of 46%, 4.6% and 17 % for each result.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.6
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• pp.2618-2623
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• 2013

A hybrid model is proposed to easily predict the effective thermal conductivity of composites with aligned- and coated-short fibers, whose aspect ratio is not constant. The thermal conductivities of coated fillers are computed by using the generalized self-consistent model, resulting in that composites are simply simulated by the matrix with the equivalent short fibers. Finally, the thermal conductivity of the composites is predicted using the modified Eshelby model. The predicted results by the representative models and hybrid model are compared for the composite with aligned- and coated-short fibers of single aspect ratio. It is demonstrated that the hybrid model can be applied to the composite with aligned- and short-fibers of aspect ratios, 2 and 10, without any difficulties.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.629-639
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• 2011

Based on Maxwell-Eucken(ME) model, which is one of structural models, a new model for predicting the effective thermal conductivity of variably saturated porous materials is proposed. The new model is a linear combination of three ME models having matrix, water, and air as a continuous phase. The coefficient of the corresponding linear equation is defined by a parameter referred to as 'the continuity coefficient', which provides a relative degree of continuity of each phase. The continuity coefficient of matrix is assumed to be linearly proportional to porosity. The model can be linear or nonlinear depending on how the continuity coefficients of water and air vary with water saturation. The feasibility of the proposed model was examined by both numerical and experimental results. Both linear and nonlinear models showed a high accuracy of prediction with $R^2$ values of 0.86-0.98 and 0.88-0.99, respectively. The numerical and experimental results also showed that the continuity coefficient of matrix was linearly proportional to porosity. Therefore, the proposed prediction model can be effectively used to estimate effective thermal conductivity of unsaturated porous materials by measuring porosity, water content and mineralogical compositions of matrix.

• Journal of Soil and Groundwater Environment
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• v.13 no.3
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• pp.27-36
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• 2008

This paper presents a comprehensive laboratory study that examines the effects of porosity, water content, density and grain size distribution on the thermal conductivity of soils which were sampled from 16 synoptic stations of Korea. The experimental results clearly demonstrate that porosity and water content are important parameters which strongly affect the thermal conductivity of soils. Soils with lower porosities and higher water contents have higher thermal conductivities. On the contrary, increase of the matrix density slightly increases the thermal conductivity, and grain size distribution hardly affects the thermal conductivity. Dry soils with the same porosity tend to have more scattered values of thermal conductivity than wet soils. Based on the experimental results, a multiple linear regression model and a nonlinear regression model, having two regression variables of porosity and water content, were presented to predict thermal conductivity. Both models show a high accuracy of prediction with $R^2$ values of 0.74 and 0.82, respectively. Thus, it is expected that the suggested empirical models can be used for predicting thermal conductivity of soils by measuring porosity and water content.

• Composites Research
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• v.15 no.5
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• pp.27-34
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• 2002

The purpose of this study is to measure and predict the thermal conductivity of CF3327 plain-weave fabric composite made by Hankuk Fiber, Co. An experiment apparatus based on the comparative method has been made to measure the thermal conductivities of the composite material. Its accuracy was proved by measuring the thermal conductivity of graphite which is well-known. Micro-mechanical approaches are useful to assess the effect of parameters such as fiber and matrix material properties, fiber volume fraction and fabric geometric parameters on the effective material properties of composites. In this study, prediction was based on the concept of three dimensional series-parallel thermal resistance network. Thermal resistance network was applied to unit ceil model that characterized the periodically repeated pattern of a plain weave. The numerical results were compared with experimental one and good agreement was observed. Also, the effects of fiber volume fraction on the thermal conductivity of several composites has been investigated.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.52-55
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• 2002

This paper examines the effective thermal conductivity of 3-D braided glass/epoxy composites. 3-D braided composites have a number of advantage over conventional laminate composites, including through-thickness reinforcement, and high damage tolerance and processability. The thermal properties of composites depend primarily on the microstructure of the braided preform and properties of constituent materials. A thermal resistance network model based on structure of the braided preform is proposed by using thermal-electrical analogy. In order to affirm the applicability theses solutions, thermal conductivities of 3-D braided glass/epoxy composites are measured

• Journal of the Korean Geotechnical Society
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• v.33 no.7
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• pp.55-64
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• 2017

A geological repository has been considered one of the most adequate options for the disposal of high-level radioactive waste. A geological repository will be constructed in a host rock at a depth of 500~1,000 meters below the ground surface. The geological repository system consists of a disposal canister with packed spent fuel, buffer material, backfill material, and intact rock. The buffer is very important to assure the disposal safety of high-level radioactive waste. It can restrain the release of radionuclide and protect the canister from the inflow of groundwater. High temperature in a disposal canister is released into the surrounding buffer material, and thus the thermal transfer behavior of the buffer material is very important to analyze the entire disposal safety. Therefore, this paper presents a thermal conductivity prediction model for the Kyungju compacted bentonite buffer material which is the only bentonite produced in Korea. Thermal conductivity of Kyungju bentonite was measured using a hot wire method according to various water contents and dry densities. With 39 data obtained by the hot wire method, a regression model to predict the thermal conductivity of Kyungju bentonite was suggested.

• Proceedings of the KSME Conference
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• 2001.06d
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• pp.240-245
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• 2001

Phenomena of direct contact condensation (DCC) heat transfer between steam and water are characterized by the transport of heat and mass through a moving steam/water interface. Application of the phenomena of DCC heat transfer to the engineering industries provides some advantageous features in the viewpoint of enhanced heat transfer. This study proposes a simple condensation model on the steam jets discharging into subcooled water from a single horizontal pipe for the prediction of the steam jet shapes. The analysis model was derived from the mass, momentum and energy equations as well as a thermal balance equation with condensing characteristics at the steam/water interface for the axi-symmetric coordinates. The extremely large heat transfer rate at the steam/water interface was reflected in the effective thermal conductivity estimated from the previous experimental results. The analysis results were compared with the experimental ones. The analysis model predicted that the steam jet shape (i. e. radius and length) was increasing as the steam mass flux and the pool temperature were increasing, which was similar in trend to that observed in the experiment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.2
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• pp.123-131
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• 2021

The buffer is a key component of an engineered barrier system that safeguards the disposal of high-level radioactive waste. Buffers are located between disposal canisters and host rock, and they can restrain the release of radionuclides and protect canisters from the inflow of ground water. Since considerable heat is released from a disposal canister to the surrounding buffer, the thermal conductivity of the buffer is a very important parameter in the entire disposal safety. For this reason, a lot of research has been conducted on thermal conductivity prediction models that consider various factors. In this study, the thermal conductivity of a buffer is estimated using the machine learning methods of: linear regression, decision tree, support vector machine (SVM), ensemble, Gaussian process regression (GPR), neural network, deep belief network, and genetic programming. In the results, the machine learning methods such as ensemble, genetic programming, SVM with cubic parameter, and GPR showed better performance compared with the regression model, with the ensemble with XGBoost and Gaussian process regression models showing best performance.