• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.153-158
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• 1995

All of the nuclear power plants in Korea we operating with analog instrumentation and control (I&C) equipment which are increasingly faced with frequent troubles, obsolescence and high maintenance expenses. Electrical and computer technology has improved rapidly in recent years and has been applied to other industries. So it is strongly recommended we adopt modern digital and computer technology to improve plant safety and availability. The advanced I&C system, namely, Integrated Intelligent Instrumentation and Control System (I$^3$CS) will be developed for beyond the next generation nuclear power plant. I$^3$CS consists of three major parts, the advanced compact workstation, distributed digital control and protection system including Automatic Start-up/shutdown Intelligent Control System (ASICS) and the computer-based alarm processing and operator support system, namely, Diagnosis, Response, and operator Aid Management System (DREAMS).

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.340-345
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• 1996

Because of limited resources of time and information processing capability during abnormal situation, diagnosis is difficult tasks in nuclear power plant (NPP) operators. Moreover since minimizing of adverse consequences according to process abnormalities is vital for the safety of NPP, introducing of diagnosis support systems have particularly emphasized. However, considerable works to develop effective diagnostic support system are not sufficiently fulfilled because of the complexity of NPP is one of the major problems. To cope with this complexity, a lot of model-based diagnosis support systems have considered and implemented worldwide. In this paper, as a prior step to development of model-based diagnosis support systems, primary side of pressurized water reactor is functionally modeled by multilevel flow modeling (MFM) concept. MFM is suitable for complex system modeling and for diagnosis of abnormalities. Furthermore, knowledge-based diagnosis process, of NPP operator could be supported because this diagnosis strategy can represent operator's one.

• Proceedings of the Korean Nuclear Society Conference
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• 2003.05a
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• pp.77.2-77.2
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• 2003

• Proceedings of the Korean Nuclear Society Conference
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• 1998.10a
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• pp.191-191
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• 1998

• Proceedings of the Korean Nuclear Society Conference
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• 2005.10a
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• pp.1065-1066
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• 2005

• Proceedings of the Korean Nuclear Society Conference
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• 1999.10a
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• pp.117.1-117
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• 1999

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1384-1386
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• 2005

This paper focuses on development of load test simulator of a steam turbine-generator in a nuclear power plant. When load is taken off from electrical power network, it is very difficult to effectively control the steam flow to turbine of the nuclear turbine-generator, because of disturbances, such as electrical load and network unbalance on electrical network. Up to the present time, the conventional control system has been used for the load control on nuclear steam generator, owing to the easy control algorithms and the advantage which have been proven on the nuclear power plant. However, since there are problems with stability control during low power and start-up, only a highly experienced operator can operate during those procedures. Also, a great deal of time and an expensive simulator is needed for the training of an operator. The KEPRI is developed simulator for 600MW nuclear power plant to take a test of generator load rejection, throttle valve, and turbine load control. Total load test is implemented before start up.

• Nuclear Engineering and Technology
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• v.52 no.1
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• pp.78-86
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• 2020

The operation and monitoring (OM) interface is the digital medium between nuclear power system and operators. The cognitive load of OM interface has an important effect on the operation errors made by operator during OM task between operator and computer. The cognitive load model of OM interface is constructed for analysing the composition and influencing factors of OM interface cognitive load. And to study the coping strategies and methods for cognitive load of nuclear power system. An experiment method based on eye movement is proposed to measure the cognitive load of OM interface. Experiment case is carried out with 20 subjects and typical OM interface of a nuclear power system simulator. The OM interface is optimized based on the experiment results. And the results comparison between the original OM interface and the optimized OM interface shows that the cognitive load model and proposed method is valuable contributions in reducing the cognitive load and improving the interaction efficiency of OM tasks.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1261-1270
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• 2022

This study was conducted to investigate the possibility of using gaze entropy to evaluate an operator's situation awareness in an emergency accident situation of a nuclear power plant. Gaze entropy can be an effective measure for evaluating an operator's situation awareness at a nuclear power plant because it can express gaze movement as a single comprehensive number. In order to determine the relationship between situation awareness and gaze entropy for an emergency accident situation of a nuclear power plant, an experiment was conducted to measure situation awareness and gaze entropy using simulators created for emergency accident situations LOCA, SGTR, SLB, and LOV. The experiment was to judge the accident situation of nuclear power plants presented in the simulator. The results showed that situation awareness and Shannon, dwell time, and Markov entropy had a significant negative correlation, while visual attention entropy (VAE) did not show any significant correlation with situation awareness. The results determined that Shannon entropy, dwell time entropy, and Markov entropy could be used as measures to evaluate situation awareness.

• Nuclear Engineering and Technology
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• v.48 no.5
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• pp.1184-1191
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• 2016

This paper introduces the development of a transient monitoring system to detect the early stage of a transient, to identify the type of the transient scenario, and to inform an operator with the remaining time to turbine trip when there is no operator's relevant control. This study focused on the transients originating from a secondary system in nuclear power plants (NPPs), because the secondary system was recognized to be a more dominant factor to make unplanned turbine-generator trips which can ultimately result in reactor trips. In order to make the proposed methodology practical forward, all the transient scenarios registered in a simulator of a 1,000 MWe pressurized water reactor were archived in the transient pattern database. The transient patterns show plant behavior until turbine-generator trip when there is no operator's intervention. Meanwhile, the operating data periodically captured from a plant computer is compared with an individual transient pattern in the database and a highly matched section among the transient patterns enables isolation of the type of transient and prediction of the expected remaining time to trip. The transient pattern database consists of hundreds of variables, so it is difficult to speedily compare patterns and to draw a conclusion in a timely manner. The transient pattern database and the operating data are, therefore, converted into a smaller dimension using the principal component analysis (PCA). This paper describes the process of constructing the transient pattern database, dealing with principal components, and optimizing similarity measures.