• Journal of the Korean housing association
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• v.15 no.4
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• pp.99-105
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• 2004

Korea gets most of its housing energy from fossil fuel which can be mined only for 30 years. So the development of an alternative energy is very important. Solar and underground thermal energy are two of these alternatives but little study has been conducted on these. For use of underground energy, we need accurate data regarding underground temperature, but there are only 30 measuring points for underground temperature in the entire country. We need to have a method of predicting underground temperature precisely. In this study the underground temperature is measured at under 3m in Gumi, and these data are compared with predicted data for checking the accuracy of the predicting method.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.4
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• pp.87-94
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• 2004

Recently, technical trend in machine tools is focused on enhancing of speed, accuracy and reliability. The high speed usually results in thermal displacement and structural deformation. To minimize the thermal effect, precision machine tools adopt a high precision cooling system. This study proposes a temperature control for an oil cooler system using Pill control with fuzzy logic. In the cooler system, refrigerant flow rate is controlled by rotational speed of a compressor, and outlet oil temperature is selected as the control variable. The fuzzy control rules iteratively correct PID parameters to minimize the error and difference between the outlet temperature and the reference temperature. Here, ambient temperature is used as the reference one. To show the effectiveness of the proposed method, a series of experiments are conducted for an oil cooler system of machine tools, and the results are compared with the ones of a conventional Pill control. The experimental results show that the proposed method has advantages of faster response and smaller overshoot.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.9
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• pp.1124-1132
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• 2004

The inverse problem of determining unknown inlet temperature in thermally developing, hydrodynamically developed two phase laminar flow in a parallel plate duct is considered. The inlet temperature profile is determined by measuring temperature in the flow field. No prior information is needed for the functional form of the inlet temperature profile. The inverse convection problem is solved by minimizing the objective function with regularization method. The conjugate gradient method as iterative method and the Tikhonov regularization method are employed. The effects of the functional form of inlet temperature, the number of measurement points and the measurement errors are investigated. The accuracy and efficiency of these two methods are compared and discussed.

• Journal of the Korean Solar Energy Society
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• v.29 no.5
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• pp.81-87
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• 2009

Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design.. Building designers often now predict the performance of buildings simulation programmes that require hourly weather data. However, not all weather stations provide hourly data. Climate prediction models such as HadCM3 also provide the daily average dry bulb temperature as well as the maximum and minimum. Hourly temperature values are available for building thermal simulations that accounts for future changes to climate. In order to make full use of these predicted future weather data in building simulation programmes, algorithms for downscaling daily values to hourly values are required. This paper describes a more accurate method for generating hourly temperature values in the South Korea that uses all three temperature parameters from climate model. All methods were evaluated for accuracy and stability in terms of coefficient of determination and cumulative error. They were compared with hourly data collected in Seoul and Ulsan, South Korea.

• Progress in Superconductivity and Cryogenics
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• v.13 no.2
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• pp.29-32
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• 2011

The thermal properties of insulation material are essential to develop a high-temperature superconducting (HTS) power cable to be operated at around liquid nitrogen temperature. Unlike metallic materials, nonmetallic materials have a high thermal resistance; therefore special attention needs to be paid to estimate heat flow correctly. Thus, we have developed a precise instrument for measuring the thermal conductivity of insulating materials over a temperature range from 40 K to near room temperature using a cryocooler. Firstly, the measurement of thermal conductivity for Teflon is carried out for accuracy confirmation. For a supplied heat flux, the temperature difference between warm and cold side is measured in steady state, from which the thermal conductivity of Teflon is calculated and compared with published result of NIST. In addition, the apparent thermal conductivity of Polypropylene laminated paper (PPLP) is presented and its temperature dependency is discussed.

• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.451-454
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• 2006

Fiber optic distributed temperature sensing and thermal line sensor are applied in an observation borehole and a loom deep borehole heat exchanger. For the case of permanently installed system fiber optic DTS is very useful. By comparing with TLS, fiber optic DTS shows good accuracy and reliability. Ground water flow can give influences at heat exchange rate of the heat pump system. According to the hydraulic characteristics and temperature-depth profile, we consider that temperature-depth profile do not seem to be dependent on ground water flow. A permanent installation of fiber optic cable is expected as a reliable temperature measurement technique in a borehole heat exchanger system.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.104-109
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• 2021

In the aftermath of the global pandemic that started in 2019, there have been many changes in the import/export and supply/demand process of agricultural products in each country. Amid these changes, the necessity and importance of each country's food self-sufficiency rate is increasing. There are several conditions that must accompany efficient agricultural activities, but among them, temperature is by far one of the most important conditions. For this reason, the need for high-accuracy climate data for stable agricultural activities is increasing, and various studies on climate prediction are being conducted in Korea, but data that can visually confirm climate prediction data for farmers are insufficient. Therefore, in this paper, we propose an artificial intelligence-based temperature prediction algorithm that can predict future temperature information by collecting and analyzing temperature data of farms in Gyeonggi-do in Korea for the last 10 years. If this algorithm is used, it is expected that it can be used as an auxiliary data for agricultural activities.

• Geosystem Engineering
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• v.21 no.6
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• pp.309-317
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• 2018

We employ a three-dimensional indirect boundary element method (BEM) to simulate temperature change around an underground liquefied natural gas storage cavern. The indirect BEM (IBEM) uses fictitious heat source strength on boundary elements as basic variables which are solved from equations of boundary conditions and then used to compute the temperature change at other points in the considered problem domain. The IBEM requires evaluation of singular integration for temperature change due to heat conduction from a constant heat source on a planar (triangular) region. The singularity can be eliminated by a semi-analytical integration scheme. However, it is found that the semi-analytical integration scheme yields sharp temperature gradient for points close to vertices of triangle. This affects the accuracy of heat flux, if they are evaluated by finite difference method at these points. This difficulty can be overcome by a combination of using a direct numerical integration for these points and the semi-analytical scheme for other points distance away from the vertices. The IBEM and the hybrid integration scheme have been verified with an analytic solution and then used to the application of the underground storage.

• Journal of Biomedical Engineering Research
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• v.4 no.1
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• pp.3-8
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• 1983

Characteristics of the lung inflation and deflation reflexes were measured at various temperatures on the cervical vagi in five anesthetized mongrel dogs. Nerve temperature was maintained at the body temperature, and 2-14˚C with 2˚C apart using a specially designed automated vagal cooling apparatus with an accuracy to within $\pm$ 0.1˚c at each temperature. The inflation reflex was blocked abruptly at 8-10˚C. The deflation reflex started weakened at 14˚C, thereafter showed a gradual blockade with the temperature decreased with a substantial variance among the animals.It was approximately 75% blocked at 2-5˚C. These differences in temperature characteristics made it hard to differentiate the deflation reflex from the inflation reflex. In one animal, however, the inflation reflex was completely blocked with the deflation reflex almost alive at 6-8˚C. This suggests that differential cold blockade of the vagal reflexes can be done only in selected subjects. Furthermore, the fact that these two reflexes were blocked at different temperatures may be due to the differences in the nerve fiber size and the changes in the conduction velocity with temperature.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.26-26
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• 2023

General circulation models (GCMs) are widely used in hydrological prediction, however their coarse grids make them unsuitable for regional analysis, therefore a downscaling method is required to utilize them in hydrological assessment. As one of the downscaling methods, convolutional neural network (CNN)-based downscaling has been proposed in recent years. The aim of this study is to generate the process of dynamic downscaling using CNNs by applying GCM output as input and RCM output as label data output. Prediction accuracy is compared between different input datasets, and model structures. Several input datasets with key atmospheric variables such as precipitation, temperature, and humidity were tested with two different formats; one is two-dimensional data and the other one is three-dimensional data. And in the model structure, the hyperparameters were tested to check the effect on model accuracy. The results of the experiments on the input dataset showed that the accuracy was higher for the input dataset without precipitation than with precipitation. The results of the experiments on the model structure showed that substantially increasing the number of convolutions resulted in higher accuracy, however increasing the size of the receptive field did not necessarily lead to higher accuracy. Though further investigation is required for the application, this paper can contribute to the development of efficient downscaling method with CNNs.