• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.734-743
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• 1999

In this paper, a real-time communication method using a PICNET-NP(Plant instrumentation and Control Network for Nuclear Power plant) is proposed with an analysis of the control network requirements of DCS(Distributed Control System) in nuclear power plants. The method satisfies deadline in case of worst data traffics by considering aperiodic and periodic real-time data and others. In addition, the method was used to analyze the data characteristics of the DCS in existing nuclear power plant. The result shows that use of this method meets the response time requirement(100ms).

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.4
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• pp.69-78
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• 2001

In this study optimal analysis of pipe network was performed using linear and non linear analysis method for complex real pipe network system of Mungyeong water purification field system which consists of 70 nodes and 86 elements. From the examination result of total flow which is distributed to each pipe, it is found that KYPIPE2 Model supplies less amount than NLAM. It is known that dynamic water level and pressure head of KYPIPE2 Model and NLAM are nearly in accordance with each other from each method of the pipe network analyses, and appeared that both methods of analysis shows high reliable result since the distribution of dynamic water level for every node is the short range of EL. 205.0m~EL. 210.0m besides the pressed dynamic water level. The analysis results of pressure in the methods of pipe network analysis for KYPIPE2 Model and NLAM are similar and it is satisfactory result that the pressure distributions of the tab water design criterion of 5.0kgf/cm$^2$ besides the small part of highland.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.4
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• pp.227-236
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• 1986

In this paper, an integrated voice/data packet network with window flow control is modeled by a colsed multichain queueing system, and its performance is analyzed by the mean value analysis method. Particularly, for the analysis of a packet network having various kinds of messages with different priority classes, we introduce an approach based on the mean value analysis and the concept of effective capacity. By the mathematical analysis and computer simulation, we obtain the following network statistics in the steady state: Mean buffer occupancy at each node, utilization of link throughput of a virtual channel, and mean delay time of each message. Our iterative analysis method can predict the link data status in most cases within about 10 percent of accurady, and the statistics of voice messages and external data within 5 percent as compared to simulation results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.620-636
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• 2015

Survivability is a necessary property of network system in disturbed environment. Recovery ability is a key actor of survivability. This paper concludes network survivability into a novel composite metric, i.e. Network Recovery Degree (NRD). In order to measure this metric in quantity, a concept of Source-Destination Pair (SD Pair), is created to abstract end-to-end activity based on end nodes in network, and the quality of SD Pair is also used to describe network performance, such as connectivity, quality of service, link degree, and so on. After that, a Survivability Test method in large scale Network based on SD pairs, called STNSD, is provided. How to select SD Pairs effectively in large scale network is also provided. We set up simulation environment to validate the test method in a severe destroy scenario and evaluate the method scalability in different large scale network scenarios. Experiment and analysis shows that the metric NRD correctly reflects the effort of different survivability strategy, and the proposed test method STNSD has good scalability and can be used to test and evaluate quantitative survivability in large scale network.

• 한국전산유체공학회:학술대회논문집
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• 2000.10a
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• pp.101-108
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• 2000

Pipe network analysis is analyze all of it about pressure and volume flow rate through that are pipeline, junction, regulator and valve etc. In this study is compare TVD with MOC method for analysis of unsteady compressible flow in pipelines. Then, we calculated unsteady compressible flow for pipe network that periodic volume flow rate conditions.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1032-1038
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• 2008

KTX train system is composed of TORNAD* network for transmitting information of train's internal equipments and OBCS which proceed information within train. OBCS of one trainset consisted of 28 equipments takes intelligent and dynamic composition according to equipment handling, train command and control flow. Each OBCS which is installed within trainset handle and supervise mutually action information about equipments, transmit it to driver to transmit information about train operation and preventive management. This mutual supervision and information transmission use KTX TORNAD* network system. TORNAD* network system is the one which is uniquely developped by GEC ALSTHOM, the KTX trainset manafacturing provider and this field is excluded from technical know-how transfer item. Through the research on analysis method of KTX TORNAD* system data structure which is operating on Seoul-Pusan Line, I hope that this thesis can contribute to train network system's standardization after applying it to improvement of train network system maintenance, enhancing quality of train service and applying it to future Korean rolling stock network system development.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.3
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• pp.492-507
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• 2008

Many classical network analysis methods approach networks in aspatial perspectives. Measuring network reliability and finding critical nodes in particular, the analyses consider only network connection topology ignoring spatial components in the network such as node attributes and edge distances. Using local network autocorrelation measure, this study handles the problem. By quantifying similarity or clustering of individual objects' attributes in space, local autocorrelation measures can indicate significance of individual nodes in a network. As an application, this study analyzed internet backbone networks in the United States using both classical disjoint product method and Getis-Ord local G statistics. In the process, two variables (population size and reliability) were applied as node attributes. The results showed that local network autocorrelation measures could provide local clusters of critical nodes enabling more empirical and realistic analysis particularly when research interests were local network ranges or impacts.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.100-110
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• 2008

It is not easy to monitor and identify all engine faults and conditions using conventional fault detection approaches like the GPA (Gas Path Analysis) method due to the nature and complexity of the faults. This study therefore focuses on a model based diagnostic method using Neural Network algorithms proposed for fault detection on a turbo shaft engine (PW 206C) selected as the power plant for a tilt rotor type unmanned aerial vehicle (Smart UAV). The model based diagnosis should be performed by a precise performance model. However component maps for the performance model were not provided by the engine manufacturer. Therefore they were generated by a new component map generation method, namely hybrid method using system identification and genetic algorithms that identifies inversely component characteristics from limited performance deck data provided by the engine manufacturer. Performance simulations at different operating conditions were performed on the PW206C turbo shaft engine using SIMULINK. In order to train the proposed BPNN (Back Propagation Neural Network), performance data sets obtained from performance analysis results using various implanted component degradations were used. The trained NN system could reasonably detect the faulted components including the fault pattern and quantity of the study engine at various operating conditions.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.59-66
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• 2019

Since Jeju is the absolute weight of agriculture and tourism, the analysis of precipitation is more important than other regions. Currently, some numerical models are used for analysis of precipitation of Jeju Island using observation data from meteorological satellites. However, since precipitation changes are more diverse than other regions, it is difficult to obtain satisfactory results using the existing numerical models. In this paper, we propose a Jeju precipitation pattern analysis method using the texture analysis method based on Convolution Neural Network (CNN). The proposed method converts the water vapor image and the temperature information of the area of ​​Jeju Island from the weather satellite into texture images. Then converted images are fed into the CNN to analyse the precipitation patterns of Jeju Island. We implement the proposed method and show the effectiveness of the proposed method through experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.232-241
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• 2010

This paper describes the development of robust contingency analysis program for Korean Energy Management System. The important function of contingency analysis is to determine the bus/branch model for contingency, and to calculate the state of the power network based on the network model and topology output. In the proposed method, the bus/branch models for contingencies are determined exactly using a fast linked-list method based on the application common model database. To calculate the state of the power system included contingency, the full-decoupled powerflow approach, the partial powerflow method for contingencies and the proposed contingency screening algorithm are also used to contingency analysis. To verify the performance of the developed processor, we performed a file-based test using several structured input data and online test using the database which resides on memory. The results of these comprehensive tests showed that the developed processors can accurately calculate the power system contingency state from online data and can be applied to Korea Power Exchange system.