• Tunnel and Underground Space
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• v.17 no.4
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• pp.301-310
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• 2007

The prediction of temperature in the workings for the propriety examination for the development of a deep coal bed and the ventilation design is fairly important. It is quite demanding to obtain precise thermal conductivity of rock due to the variety and the complexity of the rock types contiguous to the coal bed. Therefore, to estimate the thermal conductivity corresponding to this geological situation and complex gallery conditions, a computing program which is TemPredict, is developed in this study. It employs Artificial Neural Network and calculates the climatic conditions in galleries. This advanced neural network is based upon the Back-Propagation Algorithm and composed of the input layers that are acceptant of the physical and geological factors of the coal bed and the hidden layers each of which has the 5 and 3 neurons. To verify TemPredict, the calculated result is compared with the measured one at the entrance of -300 ML 9X of Jang-sung production department, Jang-sung Coal Mine. The difference between the results calculated by TemPredict ($25.65^{\circ}C$) and measured ($25.7^{\circ}C$) is only $0.05^{\circ}C$, which is less than the allowable error 5%. The result has more than 95% of very high reliability. The temperature prediction for the main carriage gallery 9X in -425 ML under construction when it is completed is made. Its result is $28.2^{\circ}C$. In the future, it would contribute to the ventilation design for the mine and the underground structures.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.8
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• pp.798-804
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• 2009

A high-resolution electro-optical camera system, EOS-C, is under development in Satrec Initiative. This system is the mission payload of a 400-kg Earth observation satellite. We designed this system to give improved opto-mechanical and thermal performance compared with a similar camera system to be flown on the DubaiSat-1 system. The thermal control subsystem (TCS) of the EOS-C system uses heaters to meet the opto-mechanical requirements during in-orbit operation and it uses different thermal coating materials and multi-layer insulation (MLI) blankets to minimize the heater power consumption. We performed its thermal analysis for the mission orbit using a thermal analysis model and the result shows that its TCS satisfies the design requirements.

• Journal of Sensor Science and Technology
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• v.5 no.2
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• pp.37-46
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• 1996

This paper describes a system that can be used to recognize unknown materials regardless of the change in ambient temperature by using temperature response curve fitting and fuzzy neural network(FNN). There are problems with a recognition system which utilize temperature responses. It requires too many memories to store the vast temperature response data and it has to be filtered to remove the noise which occurs in experiments. Thus, this paper proposes a practical method using curve fitting to remove the above problems of memories and noise. Also, the FNN is proposed to overcome the problem caused by the change of ambient temperature. Using the FNN which is learned by temperature responses on fixed ambient temperatures and known thermal conductivity, the thermal conductivity of the material can be inferred on various ambient temperatures. So the material can be recognized via its thermal conductivity.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.183-192
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• 2023

Radiofrequency ablation (RFA) is an alternative treatment for liver cancer to the surgical intervention preferred by surgeons. However, the main challenge remains the use of RF for the ablation of large tumours (i.e., tumours with a diameter of >3 cm). For large tumours, RFA takes a large duration in the ablation process compared with surgery, which increases patient pain. Therefore, RFA for large tumours is not preferred by surgeons. The currently materials used in RF electrodes, such as the nickeltitanium alloy (nitinol), are characterized by low thermal and electrical conductivities. On the other hand, the use of materials that have high thermal and electrical conductivities, such as titanium aluminide alloy (gamma titanium), produces more thermal energy for tumours. In this paper, we developed a cool-tip RF electrode model that uses nickel-titanium alloy and replaced it with titanium aluminide alloy by using the finite element model (FEM). The aim of this paper is to study the effect of the thermal and electrical conductivities of gamma titanium on the ablation volume. Results showed that the proposed design of the electrode increased the ablation rate by 1 cm³ /minute and 6.3 cm³/10 minutes, with a decrease in the required time ablation. Finally, the proposed model reduces the ablation time and damages healthy tissue while increasing the ablation volume from 22.5% cm³ to 62.5% cm³ in ten minutes compared to recent studies.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.123.1-123.1
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• 2010

수평형 지중열교환기의 최적설계를 위해서는 되메움재의 광물특성 및 입자크기, 열전도도(thermal conductivity), 열용량(heat capacity)등과 같은 열적 특성을 파악 하는 것은 중요하다. 수평형 지중 열교환기용 되메움재의 열전도도를 파악하기 위해 비정상 열선법을 적용한 QTM-500을 사용하여 포화도에 따른 천연규사-물-공기 혼합물의 열전도도를 측정하였다. 측정된 열전도도를 개별요소법(Discrete Element Mothod)에 근거한 2차원 수치해석 프로그램인 PFC2D(Particle Flow Code in 2 Dimension)를 이용하여 비교 분석하였다. 수치해석에서는 혼합물의 건조밀도를 일정하게 유지한 상태에서 포화도에 따라 가상의 물 입자 개수를 변화시켰다. 개별요소법을 이용한 열전달 수치해석에서는 입자의 접촉을 통해 발생한 thermal pipe에 의해 열전달이 이루어진다. 이러한 thermal pipe의 열전도도는 접촉된 두 입자의 열전도도와 접촉면의 평균 열전도도를 고려하여 적용하였다.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.4
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• pp.297-301
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• 2014

The biggest factors, which lower the machining accuracy of machine, are thermal deformation and chatter vibration. In this article, we introduce the development case of a device and technology that can automatically compensate thermal deformation errors of machine during long-time processing on the machine tool's CNC (Computerized Numerical Controller) in real time. In machine processing, the data acquisition of temperature signal in real time and auto-compensation of the machine origin of machine tools depending on thermal deformation have significant influence on improving the machining accuracy and the rate of operation. Thus, we attempts to introduce the related contents of the development we have made in this article : The development of a device that embedded the acquisition part of temperature data, linear regression to get compensation value, compensation model of neural network and a system that compensates the machine origin of machine tool automatically during manufacturing process on the CNC.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.115-120
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• 2008

Use of the carbon nanotube is superior to general powder state materials of mechanical and electrical properties. Because its ratio of diameter and length (aspect ratio) is very large, it has been known as a type of ideal nano-reinforcement material. Based on this advantage, the existing carbon black of semiconductive shield materials used in power cables can acquire excellent properties by using a small amount of carbon nanotubes. Thus, we investigated the thermal properties of the carbon nanotube, such as thermal conductivity, specific heat, and DSC (Differential Scanning Calorimetry). We found that a high thermal resistance level is demonstrated by using a small amount of carbon nanotubes. As a result, this tendency confirms high cross-linking density in a new network in which the carbon nanotube between carbon black constitute molecules shows a bond by similar constructive properties.

• Geomechanics and Engineering
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• v.10 no.1
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• pp.49-57
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• 2016

The high permeability-high strength concrete belongs to the typical of porous materials. It is mainly used in underground engineering for cold area, it can act the role of heat preservation, also to be the bailing and buffer layer. In order to establish a suitable model to predict the thermal conductivity and directly applied for engineering, according to the structure characteristics, the thermal conductivity predicting model was built by resistance network model of parallel three-phase medium. For the selected geometric and physical cell model, the thermal conductivity forecast model can be set up with aggregate particle size and mixture ratio directly. Comparing with the experimental data and classic model, the prediction model could reflect the mixture ratio intuitively. When the experimental and calculating data are contrasted, the value of experiment is slightly higher than predicting, and the average relative error is about 6.6%. If the material can be used in underground engineering instead by the commonly insulation material, it can achieve the basic requirements to be the heat insulation material as well.

• Fire Science and Engineering
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• v.12 no.4
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• pp.51-57
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• 1998

The thermal behavior and the flammability characteristics of four different unsaturated polyester resins were studied by performing a series of thermal analysis experiments and laboratory scale fire tests. The results of TGA and DSC reveals that the vinylester type resins have superior thermal performances when compared to the isophthalic type resins. The vinylester type resins formed a network shaped char surface after the thermal decomposition up to 55$0^{\circ}C$. Consequently, the vinylester type resings have shown lower value of burning rate than that of iso type resins. Due to the high level of flammability and toxic smoke emission, the appropriate flame retardant system should be applied to the unsaturated polyester resings.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.386-398
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• 2019

The transmission capacity of transmission lines is affected by environmental parameters such as ambient temperature, wind speed, wind direction and so on. The environmental parameters can be measured by the installed measuring devices. However, it is impossible to install the environmental measuring devices throughout the line, especially considering economic cost of power grid. Taking into account the limited number of measuring devices and the distribution characteristics of environment parameters and transmission lines, this paper first studies the environmental parameter estimating method of inverse distance weighted interpolation and ordinary Kriging interpolation. Dynamic thermal rating of transmission lines based on IEEE standard and CIGRE standard thermal equivalent equation is researched and the key parameters that affect the load capacity of overhead lines is identified. Finally, the distributed thermal rating of transmission line is realized by using the data obtained from China meteorological data network. The cost of the environmental measurement device is reduced, and the accuracy of dynamic rating is improved.