• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.263-268
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• 2010

Thermal characterization of geomaterials has significant implication on the geothermal energy, disposal of nuclear wastes, geological sequestration of carbon dioxides and recovery of hydrocarbon resources. Heat transfer in multiphase materials is dominated by the thermal conductivity of consisting components, porosity, degree of saturation and overburden pressure, which have been investigated by the empirical correlation at macro-scale. The thermal measurement by Transient Plane Source (TPS) and associated algorithm for interpretation of thermal behavior in geomaterials corroborate the robustness of sensing techniques. The method simultaneously provides thermal conductivity, diffusivity and volumetric heat capacity. The newly introduced thermal network model enables estimating thermal conductivity of geomaterials subjected to the effective stress, which has not been evaluated using previous thermal models. The proposed methods shows the applicability of reliability of TPS technique and thermal network model.

• Fire Science and Engineering
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• v.10 no.2
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• pp.28-39
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• 1996

A recently developed electro-thermal simulation methodology is used to analyze the behavior of a PWM(Pulse-Width-Modulated) voltage source inverter which uses IGBT(Insulated Gate Bipolar Transistor) as the switching devices. In the electro-thermal network simulation methdology, the simulator solves for the temperature distribution within the power semiconductor devices(IGBT electro-thermal model), control logic circuitry, the IGBT gate drivers, the thermal network component models for the power silicon chips, package, and heat sinks as well as the current and voltage within the electrical network. The thermal network describes the flow of heat form the chip surface through the package and heat sink and thus determines the evolution of the chip surface temperature used by the power semiconductor device models. The thermal component model for the device silicon chip, packages, and heat sink are developed by discretizing the nonlinear heat diffusion equation and are represented in component from so that the thermal component models for various package and heat sink can be readily connected to on another to form the thermal network.

• Journal of computational fluids engineering
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• v.19 no.1
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• pp.47-56
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• 2014

Since a typical plate heat exchanger is made up of a huge number of unitary cells, it may be impossible to predict the aero-thermal performance of the full scale heat exchanger through three-dimensional numerical simulation due to the enormous amount of computing resources and time required. In the present study, a simple flow-network model using the friction factor correlation and a thermal-network model based on the effectiveness-number of transfer units (${\varepsilon}$-NTU) method has been developed. The complicated flow pattern inside the cross-corrugated heat exchanger has been modeled into flow and thermal networks. Using this model, the heat transfer between neighboring streams can be considered, and the pressure drop and the heat transfer rate of full-scale heat exchanger matrix are calculated. In the calculation, the aero-thermal performance of each unitary cell of the heat exchanger matrix was evaluated using correlations of the Fanning friction factor f and the Nusselt number Nu, which were calculated by unitary-cell CFD model.

• 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.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2276-2283
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• 2018

A 50kW-4000rpm interior permanent magnet synchronous machine (IPMSM) applied to the high-performance electric vehicle (EV) is introduced in this paper. The main work of this paper is that a 2-D T-type lumped-parameter thermal network (LPTN) model is presented for IPMSM temperature rise calculation. Thermal conductance matrix equation is generated based on calculated thermal resistance and loss. Thus the temperature of each node is obtained by solving thermal conductance matrix. Then a 3-D liquid-solid coupling model is built to compare with the 2-D T-type LPTN model. Finally, an experimental platform is established to verify the above-mentioned methods, which obtains the measured efficiency map and current wave at rated load case and overload case. Thermocouple PTC100 is used to measure the temperature of the stator winding and iron core, and the FLUKE infrared-thermal-imager is applied to measure the surface temperature of IPMSM and controller. Test results show that the 2-D T-type LPTN model have a high accuracy to predict each part temperature.

• 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

• Progress in Superconductivity and Cryogenics
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• v.24 no.4
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• pp.78-83
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• 2022

REBCO coated conductors are widely used for HTS power application, high magnetic field magnet application, and etc. A thermal stability of the REBCO conductor is essential for the operation of HTS-based device, and thermal conductivities of the conductor are relevant parameters for modeling cryogenic heat transfer. REBCO conductors consist of a REBCO layer, copper layers for electrical stabilization and a hastelloy substrate. At cryogenic temperature, thermal conductivity of copper and silver strongly depend on the purity of the material and the intensity of the magnetic field. In this study, thermal conductivities of the laminated composite structure of REBCO conductor are evaluated by using the thermal network model and the multidimensional heat conduction analysis. As a result, the thermal network model is applicable to REBCO conductors configured in series or parallel alone and multidimensional heat conduction analysis is necessary for complex cases of series and parallel configuration.

• Korean Chemical Engineering Research
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• v.55 no.3
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• pp.322-331
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• 2017

District heating was first introduced in Korea in 1985. As the service life of the underground thermal piping network has increased for more than 30 years, the maintenance of the underground thermal pipe has become an important issue. A variety of complex technologies are required for periodic inspection and operation management for the maintenance of the aged thermal piping network. Especially, it is required to develop a model that can be used for decision making in order to derive optimal maintenance and replacement point from the economic viewpoint in the field. In this study, the analysis was carried out based on the repair history and accident data at the operation of the thermal pipe network of five districts in the Korea District Heating Corporation. A failure probability model was developed by introducing statistical techniques of qualitative analysis and binomial logistic regression analysis. As a result of qualitative analysis of maintenance history and accident data, the most important cause of pipeline damage was construction erosion, corrosion of pipe and bad material accounted for about 82%. In the statistical model analysis, by setting the separation point of the classification to 0.25, the accuracy of the thermal pipe breakage and non-breakage classification improved to 73.5%. In order to establish the failure probability model, the fitness of the model was verified through the Hosmer and Lemeshow test, the independent test of the independent variables, and the Chi-Square test of the model. According to the results of analysis of the risk of thermal pipe network damage, the highest probability of failure was analyzed as the thermal pipeline constructed by the F construction company in the reducer pipe of less than 250mm, which is more than 10 years on the Seoul area motorway in winter. The results of this study can be used to prioritize maintenance, preventive inspection, and replacement of thermal piping systems. In addition, it will be possible to reduce the frequency of thermal pipeline damage and to use it more aggressively to manage thermal piping network by establishing and coping with accident prevention plan in advance such as inspection and maintenance.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.975-983
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• 2013

This study proposes a low order dynamic model of a building system in order to predict thermal behavior within a building and its energy consumption. The building system includes a thermally well-insulated room and an electric heater. It is modeled by a second order lumped RC thermal network based on the thermal-electrical analogy. In order to identify unknown parameters of the model, an experimental procedure is firstly detailed. Then, the different linear parametric models (ARMA, ARX, ARMAX, BJ, and OE models) are recalled. The parameters of the parametric models are obtained by the least square approach. The obtained parameters are interpreted to the parameters of the physically based model in accordance with their relationship. Afterwards, the obtained models are implemented in Matlab/Simulink(R) and are evaluated by the mean of the sum of absolute error (MAE) and the mean of the sum of square error (MSE) with the variable of indoor temperature of the room. Quantities of electrical energy and converted thermal energy are also compared. This study will permit a further study on Model Predictive Control adapting to the proposed model in order to reduce energy consumption of the building.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.17-22
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• 2023

In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.