• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1599-1606
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• 2008

Recently, new dispersed generation systems such as photovoltaic, wind power, fuel cell etc. are energetically interconnected and operated in the distribution systems, as one of the national projects for alternative energy with the provision against oil crisis. The technical guidelines on the interconnection of dispersed generation systems have been established and conducted positively. However, protection devices (Re-closer) in primary feeder of distribution system interconnected with photovoltaic generation may cause problems with mis-operation, and then many customers could have problems like an interruption. So, this paper presents the optimal method to minimize the impact of interruption, using both the symmetric method and MATLAB/SIMULINK. And, also this paper shows the effectiveness of proposed method by simulating at the real distribution systems.

• Korean Chemical Engineering Research
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• v.43 no.5
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• pp.571-578
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• 2005

We propose a new optimization framework for the reactive scheduling. The proposed rescheduling scheme is specially focused on how to generate rescheduling results when equipment failure occurs. The approach is based on a continuous-time problem representation that takes into account the schedule in progress, the updated information on the batches still to be processed, the present plant state, the deviations in plant parameters and the time data. To update the predictive scheduling, we used right shift rescheduling and total regeneration when equipment failure occurs. And, a practical solution to the rescheduling problem requires satisfaction of two often confliction measures: the efficiency measure that evaluates the satisfaction of a desired objective function value and the stability measure that evaluates the amount of change between the schedules before and after the disruption. In this paper, the efficiency is measured by the makespan of all jobs in the system. And, the stability is measured by the percentage change in makespan and the modified sequence deviation in the predictive scheduling and rescheduling.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.2
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• pp.120-126
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• 2019

Recently, there is an increasing need for highly precise processing with the rapid development of precision machinery, electrical and electronics, and semiconductor industries. Cutting machine control relies on the operator's sense and experience in tradition, but it has been greatly enhanced by the adoption of CNC(Computerized Numeric Controller). In addition, cutting dynamics technology has been paid attention to reflect the operating state of machine in real time. This paper presents a method to detect and stabilize tool vibration by attaching an acoustic sensor to a CNC machine. The sensed acoustic data is synchronized with the tool position and the abnormal vibration frequency is separated from the collected acoustic frequency, then analyzed to detect the tool vibration. Also the reliability the tool vibration detection and stabilization is improved by applying the cutting dynamic method. The proposed method is analyzed and evaluated in terms of the surface roughness.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.101-105
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• 2018

In this paper, the kernel regression model is applied for the case study of gas turbine abnormal state analysis. In addition to vibration analysis at the remote site, the kernel regression model technique can is useful for analyzing abnormal state of rotor vibration signals of gas turbine in power plant. In monitoring based on data-driven techniques correlated measurements, the fault free training data of shaft vibration obtained during normal operations of gas turbine are used to develop a empirical model based on auto-associative kernel regression. This data-driven model can be used to predict virtual measurements, which are compared with real-time data, generating residuals. Any faults in the system may cause statistically abnormal changes in these residuals and could be detected. As the result, the kernel regression model provides information that can distinguish anomalies such as sensor failure in a shaft vibration signal.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.841-852
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• 2023

Gas turbines, which are used as generators for frequency regulation of the domestic power system, are increasing in use due to the carbon-neutral policy, quick startup and shutdown, and high thermal efficiency. Since the gas turbine rotates the turbine using high-temperature flame, the turbine inlet temperature is acting as a key factor determining the performance and lifespan of the device. However, since the inlet temperature cannot be directly measured, the temperature calculated by the manufacturer is used or the temperature predicted based on field experience is applied, which makes it difficult to operate and maintain the gas turbine in a stable manner. In this study, we present a model that can predict the inlet temperature of a reheat gas turbine based on Deep Neural Network (DNN), which is widely used in artificial neural networks, and verify the performance of the proposed DNN based on actual data.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.06a
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• pp.110-120
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• 2005

For utilizing vitrification to treat low and intermediate level waste, industrial pilot plant was designed and constructed in October 1999 at Daejon, Korea through the joint research program among NETEC, MOBIS and SGN. More than 70 tests were performed on simulated IER, DAW etc. including key nuclide surrogate(Cs, Co); this plant has been shown to vitrify the target waste effectively and safely, however, some dust are generated from the HTF(High Temperature Filter) as a secondary waste. In case of long term operation, it is also concerned that pipe plugging can be occurred due to deposited dust in cooling pipe namely, connecting pipe between CCM(Cold Crucible Melter) and HTF. In this regard, we have developed the special complementary system of the off-gas treatment system to recycle the dust from HTF to CCM and to remove the interior dust of cooling pipe. Main concept of the dust recycling is to feed the dust to the CCM as a slurry state; this system is regarded as of an important position in the viewpoint of volume reduction, waste disposal cost and glass melt control in CCM. The role of DRS(Dust Recycling System) is to recycle the major glass components and key nuclides; this system is served to lower glass viscosity and increase waste solubility by recycling B, Na, Li components into glass melt and also to re-entrain and incorporate into glass melt like Cs, Co. Therefore dust recycling is helpful to control the molten glass; it is unnecessary to consider a separate dust treatment system like a cementation equipment. The effects of Dust Cleaner are to prevent the pipe plugging due to dust and to treat the deposited dust by raking the dust into CCM. During the pilot vitrification test, overall performance assessment was successfully performed; DRS and Dust Cleaner are found to be useful and effective for recycling the dust from HTF and also removing the dust in cooling pipe. The obtained operational data and operational experiences will be used as a basis of the commercial facility.

• Journal of agricultural medicine and community health
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• v.27 no.2
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• pp.107-126
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• 2002

Health sub-centers(HSCs) have played an important role in primary health care in rural area in Korea. The unification of neighboring HSCs was a strategy to improve the role of HSCs. This study was conducted to reveal the efficacy of the unified HSC established in Yangbuk-myeon, Gyeongju-si in1997. The utilization patterns of HSC and its related factors, and satisfaction of consumer on HSC were compared before and after unification of two HSCs in Gampo-eup, Yangnam-myeon using questionnaire survey, and also the statistics of medical care services and public health services were compared. Four hundred forty nine subjects were questioned in survey, 156 from Gampo-eup, 147 from Yangbuk-myeon, and 146 from Yangnam-myeon. Following unification, the utilization rates and the frequency of visits in Gampo-eup declined. In all three areas, chronic illness was the common factor influencing the utilization and change in frequency of visits to the unified HSC. Following unification, aspects of consumer satisfaction, for example; accessibility and affordability decreased in Gampo-eup, but increased in both Yangbuk-myeon and Yangnam-myeon. The statistics relating to medical care, X-ray examination, home visiting service, vaccination, and health education showed an increase for the unified HSC when compared to the sum of the statistics for the previous two. The execution rates for other public health services were the same, or a little decreased. Clinical laboratory examinations and the issuing of civil affair documents were new services offered by the unified HSC. It is concluded, the overall consumer satisfaction with the unified HSC was improved. In Gampo-eup, where after unification there was no HSC, it seemed to be a barrier to accessing the unified HSC. The effect of the unified HSC, in the respect of medical care and public health services, was not as significant as expected at the time of being established. Therefore, the strategies to reenforce the unified HSC should be developed to provide all residents with comprehensive primary health care services.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.4
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• pp.341-348
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• 2010

The basic principle of fry drying process of sludge lies in the rapid pressure change of sludge material caused by the change of temperature between oil and moisture due to the difference of specific heat. Therefore, the rapid increase of pressure in drying sludge induces the efficient moisture escape through sludge pores toward heating oil media. The object of this study is to carry out a systematic investigation of the influence of various parameters associated with the sludge fry drying processes on the drying efficiency. To this end, a series of parametric experimental investigation has been made together with the numerical calculation in order to obtain typical drying curves as function of important parameters such as drying temperature, sludge diameter, oil type and sludge type. In the aspect of frying temperature, especially it is found that the operation higher than $140^{\circ}C$ was favorable in drying efficiency regardless of type of waste oil employed in this study. The same result was also noted consistently in the investigation of numerical calculation, that is, in that the sludge particle drying was efficiently made over $140^{\circ}C$ irrespective of the change of particle diameter. As expected, in general, the decrease of diameter in sludge was found efficient both experiment and numerical calculation in drying due to the increased surface area per unit volume. In the investigation of oil type and property, the effect of the viscosity of waste oil was found to be more influential in drying performance. In particular, when the oil with high viscosity, a visible time delay was noticed in moisture evaporation especially in the early stage of drying. However, the effect of high viscosity decreased significantly over the temperature of $140^{\circ}C$. There was no visible difference observed in the study of sludge type but the sewage sludge with a slightly better efficiency. The numerical study is considered to be a quite useful tool to assist in experiment with more detailed empirical modeling as further work.

• Korean Chemical Engineering Research
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• v.50 no.4
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• pp.595-603
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• 2012

International Thermonuclear Experimental Reactor (ITER) will be constructed in 2019 according to the JIA (Joint Implementation Agreement) of 7 countries. The ITER fusion fuel cycle consists of fusion vacuum vessel, tritium plant and fuelling system. The tritium plant provides the functions of storage, delivery, separation, removal and recovery of the deuterium and tritium used as fusion fuels for the ITER. The tritium plant systems supply deuterium and tritium from external sources and treat all tritiated fluids from ITER operation through Storage and Delivery System (SDS), Tokamak Exhaust Processing (TEP), Isotope Separation System (ISS), Water Detritiation System & Atmosphere Detritiation System (WDS & ADS) and Analysis System (ANS). In this paper, the functions and design requirements of the major systems in the tritium plant and the status of R&D are described. Korean party is developing the SDS for ITER tritium plant and partially attaining the WDS technology through the construction and operation experience of the Wolsong Tritium Removal Facility (WTRF). Now it is expected that researchers in other fields such as chemical engineering take part in the development of upcoming technologies for ISS and TEP.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.1 s.4
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• pp.31-44
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• 2004

The study of Estimation model for the short-term travel time prediction. There is a different solution which has predicted the link travel time to solve this problem. By using this solution, the link travel time is predicted based on link conditions from time to time. The predicated link travel time is used to search the shortest path. Before providing a dynamic shortest path finding, the prediction model should be verified. To verify the prediction model, three models such as Kalman filtering, Stochastic Process, ARIMA. The ARIMA model should adjust optimal parameters according to the traffic conditions. It requires a frequent adjustment process of finding optimal parameters. As a result of these characteristics, It is difficult to use the ARIMA model as a prediction. Kalman Filtering model has a distinguished prediction capability. It is due to the modification of travel time predictive errors in the gaining matrix. As a result of these characteristics, the Kalman Filtering model is likely to have a non-accumulative errors in prediction. Stochastic Process model uses the historical patterns of travel time conditions on links. It if favorably comparable with the other models in the sense of the recurrent travel time condition prediction. As a result, for the travel time estimation, Kalman filtering model is the better estimation model for the short-term estimation, stochastic process is the better for the long-term estimation.