• 에너지공학
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• 제21권2호
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• pp.144-151
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• 2012

지역난방시스템이란 열에너지를 생산하고 만들어진 열에너지를 넓은 지역에 공급하는 시스템이다. 지역난방시스템은 국부난방보다 더 효율적이고 친환경적이라고 할 수 있다. 생산 된 열은 단열 배관 네트워크를 통해 사용자들에게 공급된다. 지역난방시스템의 효율적인 운전을 위해서는 여러 가지 운전 조건에서 배관망 네트워크의 유량, 압력 및 온도 분포를 예측하는 것이 중요하다. 본 연구에서는 지역난방용 지중매설 배관망 네트워크에서의 열-유체 동적거동을 수학적 모델을 사용하여 예측하였다. 수학적 모델은 물질, 운동량 및 에너지 수지식을 사용하였다. 모델링의 결과를 검증하기 위하여 강남지역 지역난방시스템에서 측정한 결과와 모델링의 결과를 비교하였다.

• 전기학회논문지P
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• 제53권2호
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• pp.94-99
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• 2004

In this paper, We design a RF control system capable of handling multiple POS thermal printers. The system has three parts including embedded master controller, RF controller and high-speed thermal printer. Specially the designed linux embedded controller has simple structure and high performance to connect the TCP/IP network. The effectiveness of the developed RF control system is shown by proposed food ordering system.

• 에너지공학
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• 제17권3호
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• pp.125-138
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• 2008

에너지원의 다양화와 효율적인 이용을 위하여 광역지역의 통합에너지관리 시스템 구축이 요구되고 있다. 본 보문에서는 이러한 필요성에 부응하여 광역에너지 네트워크 구축에 필요한 핵심기술을 발굴하여 이를 종합적으로 현장에 적용하는 기술개발 을 수행하고 있다. 이를 위해 IT기술과 접목한 광역 네트워크 열공급 최적화 통합시스템 구축 기술, 발생되는 배열을 이용한 열펌프와 같은 미활용에너지 이용기술, 다양한 열원을 이용한 열수송 및 축열 기술 등 새로운 시스템을 개발하고 이를 현장적용을 통해 경제성을 평가하여 최종적으로 실용화할 수 있는 사업화 모델에 대하여 기술하였다.

• Nuclear Engineering and Technology
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• 제53권7호
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• pp.2174-2183
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• 2021

Helium cooled solid breeder blanket as an important blanket candidate of the Tokamak fusion reactor uses ceramic pebble bed for tritium breeding. Considering the poor effective thermal conductivity of the ceramic breeder pebble bed, thin structure of tritium breeder pebble bed is usually adopted in the blanket design. The container wall has a great influence on the thin pebble bed packing structure, especially for the assembly of mono-sized particles, and thin pebble bed will appear anisotropic effective thermal conductivity phenomenon. In this paper, thin ceramic pebble beds composed of 1 mm diameter Li₄SiO₄ particles are generated by the EDEM 2.7. The effective thermal conductivity of different thickness pebble beds in the three-dimensional directions are analyzed by three-dimensional thermal network method. It is observed that thin Li₄SiO₄ pebble bed showing anisotropic effective thermal conductivity under the practical design size. Normally, the effective thermal conductivity along the bed vertical direction is higher than the horizontal direction due to the gravity effect. As the thickness increases from 10 mm to 40 mm, the effective thermal conductivity of the pebble bed gradually increases.

• Journal of Electrical Engineering and Technology
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• 제8권5호
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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.

• 한국주거학회논문집
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• 제22권3호
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• pp.113-122
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• 2011

This study aimed to develop AI- (Artificial Intelligence) based thermal control logics and test their performance for identifying the optimal thermal control method in buildings. For this objective, a conventional Two-Position On/Off logic and two AI-based variable logics, which applied ANN (Artificial Neural Network) and ANFIS (Adaptive Neuro-Fuzzy Inference System), have developed. Performance of each logic was tested in a typical two-story residential building in U.S.A. using the computer simulation incorporating MATLAB and IBPT (International Building Physics Toolbox). In the analysis of the test results, AI-based control logic presented the advanced thermal comfort with stability compared to the conventional logic while they did not show significant energy saving effects. In conclusion, the predictive and adaptive AI-based control logics have a potential to maintain interior air temperature more comfortably, and the findings in this study could be a solid foundation for identifying the optimal thermal control method in buildings.

• Geomechanics and Engineering
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• 제28권5호
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• pp.477-491
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• 2022

In the present study, the effects of thermal loading on the buckling and resonance frequency of graphene platelets (GPL) reinforced nano-composites are examined. Functionally graded (FG) material properties are considered in thickness direction for the thermal responses of the composite. The equivalent material properties are obtained using Halphin-Tsai nano-mechanical model for composite layers. Moreover, the effects of nano-scale sizes are taken into account, employing functionally modified couple stress (FMCS) parameter. In this regard, for the first time, it is demonstrated that at certain values of GPL weight fraction, thermal buckling occurs. In obtaining results of vibrational behavior, both analytical solution and deep neural network (DNN) methods are used. The DNN method needs low computational costs to predict the resonance behavior. A comprehensive parametric study is conducted to indicate the effects of several geometrical, material, and loading conditions on the vibrational and buckling behavior of cylindrical shell structures made of GPL-nanocomposites. It is shown that the effect of temperature change on the occurrence of buckling is vital while it has a negligible impact on the resonance frequency of the structure. Moreover, the size-dependency of the results is demonstrated, and it cannot be neglected in nano-scales.

• 한국지반공학회논문집
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• 제27권9호
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• pp.77-86
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• 2011

지반 물질의 열전도도는 경험식이 제안하는 단위 중량, 간극률 등의 영향 인자 이외에도 하중조건에 따라 크게 좌우된다. 본 논문에서는 개별요소법에 의해 생성된 입자상 지반재료의 열 전달 특성을 열 네트워크 모델로 해석하여 하중이 열전도도에 미치는 영향을 평가하였다. 하중의 변화에 의한 개별 입자들간의 접촉수 및 간극률, 간극수의 전도도에 따른 열전도도를 산출하여 영향 요소들간의 관계를 분석하였다. 전도도의 변화 양상은 전단강성도 분석과 유사하게 열전달 방향 및 하중 크기에 따른 멱함수 형태로 회귀분석이 가능하였다. 해석 결과 하중에 따른 입자간 접촉 면적의 증가 및 간극수의 전도도가 전체 입자상 물질의 열 흐름에 큰 영향을 미침을 알 수 있었다. 열전도도의 이방성은 하중 방향에 의해 좌우되며 입자 스케일에서의 매커니즘이 열 흐름을 좌우하는 중요한 인자임을 보였다.

• Geomechanics and Engineering
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• 제6권4호
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• pp.359-376
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• 2014

Thermal conductivity of ground has a great influence on the performance of Ground Heat Exchangers (GHEs). In general, the ground thermal conductivity significantly depends on the density (or porosity) and the moisture content since they are decisive factors that determine the interface area between soil particles which is available for heat transfer. In this study, a large number of thermal conductivity experiments were conducted for soils of varying porosity and moisture content, and a database of thermal properties for the weathered granite soils was set up. Based on the database, a 3D Curved Surface Model and an Artificial Neural Network Model (ANNM) were proposed for estimating the thermal conductivity. The new models were validated by comparing predictions by the models with new thermal conductivity data, which had not been used in developing the models. As for the 3D CSM, the normalized average values of training and test data were 1.079 and 1.061 with variations of 0.158 and 0.148, respectively. The predictions became somewhat unreliable in a low range of thermal conductivity values in considering the distribution pattern. As for the ANNM, the 'Logsig-Tansig' transfer function combination with nine neurons gave the most accurate estimates. The normalized average values of training data and test data were 1.006 and 0.954 with variations of 0.026 and 0.098, respectively. It can be concluded that the ANNM gives much better results than the 3D CSM.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2009년 춘계학술대회논문집
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• pp.135-141
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• 2009

A preliminary thermal analysis is performed for the optical payload system of a geostationary satellite. The optical payload considered in this paper is GOCI(Geostationary Ocean Color Imager) of COMS of Korea. The radiative and conductive thermal models are employed in order to predict thermal responses of the GOCI on the geostationary orbit. According to the results of this analysis are as follows: 1) the GOCI instrument thermal control is satisfactory to provide the temperatures for the GOCI performances, 2) the thermal control is defined and interfaces are validated, and 3) the entrance baffle temperature is found slightly out its specification, therefore further detailed analyses should be continued on this element.