• Nuclear Engineering and Technology
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• v.40 no.5
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• pp.327-348
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• 2008

A risk-informed regulatory approach implies that risk insights be used as supplement of deterministic information for safety decision-making purposes. In this view, the use of risk assessment techniques is expected to lead to improved safety and a more rational allocation of the limited resources available. On the other hand, it is recognized that uncertainties affect both the deterministic safety analyses and the risk assessments. In order for the risk-informed decision making process to be effective, the adequate representation and treatment of such uncertainties is mandatory. In this paper, the risk-informed regulatory framework is considered under the focus of the uncertainty issue. Traditionally, probability theory has provided the language and mathematics for the representation and treatment of uncertainty. More recently, other mathematical structures have been introduced. In particular, the Dempster-Shafer theory of evidence is here illustrated as a generalized framework encompassing probability theory and possibility theory. The special case of probability theory is only addressed as term of comparison, given that it is a well known subject. On the other hand, the special case of possibility theory is amply illustrated. An example of the combination of probability and possibility for treating the uncertainty in the parameters of an event tree is illustrated.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.25-30
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• 2002

The problem of qualitative reliability system is very important issue in the digitalized nuclear power plant, because the failure of its system brings about extravagant economic loss, extensive environment destruction, and fatal damage of human. Therefore this study is to develop the reliability evaluation model through the normalized scoring model by the quantitative and qualitative factors considering the advanced safety factors In the Advanced Pressurized water Reactor 1400MWe(APR 1400) under uncertainty Especially, the qualitative factors considering the information and human factors for the systematic and rational justification have been closely analyzed. The reliability evaluation model can be simply applied in real fields in order to minimize the industrial accident and human error in the digitalized nuclear power plant.

• The KSFM Journal of Fluid Machinery
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• v.6 no.1 s.18
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• pp.57-65
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• 2003

The measurement uncertainties of an ultrasonic flowmeter were analyzed to evaluate its applicability to the measurement of the steam generator feedwater flow-rate in a nuclear power plant. The analyses of measurement uncertainties of a reactor power were also performed with the analyses of feedwater flow measurement uncertainties. Two ultrasonic flowmeters based on a cross-correlation technique and a transit time method were used in this study. The ultrasonic flowmeters were installed on a feedwater pipe line of a typical 1000 MWe Korea-standardized nuclear power plant to take the necessary data. The results have shown that the measurement uncertainties of the ultrasonic flowmeters are adequately smaller than those or a venturi meter. The research has also indicated that the measurement uncertainties of the reactor power based on the ultrasonic flowmeter uncertainties are sufficiently bounded by the uncertainty range usually assumed in nuclear safety analyses.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1029-1031
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• 1999

This paper presents an $H_{\infty}$ based robust STATCOM supplementary controller design to suppress the SSR in series-compensated line. This controller is designed to have the robust stability against the plant model uncertainty. Time domain simulations using a nonlinear system model show that the proposed STATCOM supplementary controller can suppress the SSR efficiently against the plant model uncertainty

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.6
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• pp.23-35
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• 2002

The problem of system reliability is very important issue in the digitalized nuclear power plant, because the failure of its system brings about extravagant economic loss, environment destruction, and fatal damage of human. Therefore the purpose of this study has developed the reliability evaluation model through the scoring model by the quantitative and qualitative factors in order to justify the evaluation considering the advanced safety factors in the Advanced Pressurized water Reactor 1400MWe(APR 1400MWe) under uncertainty. Especially, the qualitative factors considering the human, information control, and quality factors for the systematic and rational justification have been closely analyzed. The proposed model can be simply applied in real fields in order to minimize the industrial accidents in the digitalized nuclear power plant.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.884-886
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• 1998

This paper presents an LQG based robust TCSC supplementary controller design to suppress the SSR in the FACTS. This controller is designed to have the robust stability against the plant model uncertainty. The robust stability is guaranteed using the $\mu$ analysis. Time domain simulations using a nonlinear system model show that the proposed TCSC supplementary controller can suppress the SSR efficiently against the plant model uncertainty.

• Nuclear Engineering and Technology
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• v.43 no.2
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• pp.175-186
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• 2011

Previous evaluations of the safety of the Ulchin Nuclear Power Plant in the event of a tsunami have the shortcoming of uncertainty of the tsunami sources. To address this uncertainty, maximum and minimum wave heights at the intake of Ulchin NPP have been estimated through a parametric study, and then assessment of the safety margin for the intake has been carried out. From the simulation results for the Ulchin NPP site, it can be seen that the coefficient of eddy viscosity considerably affects wave height at the inside of the breakwater. In addition, assessment of the safety margin shows that almost all of the intake water pumps have a safety margin over 2 m, and Ulchin NPP site seems to be safe in the event of a tsunami according to this parametric study, although parts of the CWPs rarely have a margin for the minimum wave height.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.9
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• pp.670-677
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• 1987

The robustness and stability properties for a model reference adaptive control system with plant uncertainty are considered in this paper, using input-output stability theory. An error model for a typical adaptive control structure is extended to unmodelled dynamics in the plant model and then, the strictly positive real condition for global stability is examined. In general, since this condition can be easily violated due to unmodelled dynamics, a modified compensator which can be guaranteed Hev e SPR is introduced in the plant model and the effectiveness for the given structure is also given.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.486-490
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• 1993

This paper presents an improved algorithm which enables to find a suboptimal $H^{\infty}$ controller. In the $H^{\infty}$ control problem with output multiplicative uncertainty, the Glover-Doyle algorithm has sorne constraints for the standard plant. The proposed algorithm removes them by reformulating the standard plant. We show the validity of this algorithm by investigating the variation of norm-bound.d.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.233-238
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• 2016

In this paper, we propose the algorithms of processing the uncertainty data using data fusion for the next generation intrusion detection. In the next generation intrusion detection, a lot of data are collected by many of network sensors to discover knowledge from generating information in cyber space. It is necessary the data fusion process to extract knowledge from collected sensors data. In this paper, we have proposed method to represent the uncertainty data, by classifying where is a confidence interval in interval of uncertainty data through feature analysis of different data using inference method with Dempster-Shafer Evidence Theory. In this paper, we have implemented a detection experiment that is classified by the confidence interval using IRIS plant Data Set for anomaly detection of uncertainty data. As a result, we found that it is possible to classify data by confidence interval.