• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.483-488
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• 2010

An online monitoring based upon sensor system is essential to assure both efficient operation and safety in the power plant. Of great importance is modeling for auto-association (AA) in online monitoring technique. The objective of auto-associative models lies in predicting true values of plant operation parameters from sensor signals transmitted. This paper presents two AA models using Support Vector Regression (SVR) and Partial Least Square Regression (PLSR). The presented models are useful, in particular, when there are many parameters to monitor in the power plant. Illustrative examples are given by using a real-world plant dataset. AA performances of SVR and PLSR are finally summarized in terms of accuracy and sensitivity. According to our results, SVR shows much higher accuracy and, however, its sensitivity is relatively degraded.

• Journal of Soil and Groundwater Environment
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• v.22 no.3
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• pp.1-9
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• 2017

The numerical analysis of groundwater flow is indispensable for predicting problems associated with water resource development, civil works, environmental hazards, and nuclear power plant construction. Korea lacks public regulatory procedures and guidelines for groundwater flow modeling, especially in nuclear facility sites, which makes adequate evaluation difficult. Feasible step-by-step guidelines are also unavailable. Consequently, reports on groundwater flow modeling have low-grade quality and often present controversial opinions. Additionally, without public guidelines, maintaining consistency in reviewing reports and enforcing laws is more challenging. In this study, the guidelines for groundwater flow modeling were reviewed for three countries - the United States (Documenting Groundwater Modeling at Sites Contaminated with Radioactive Substances), Canada (Guidelines for Groundwater Modelling to Assess Impacts of Proposed Natural Resource Development Activities), and Australia (Australian Groundwater Modelling Guidelines), with the aim of developing groundwater flow modeling regulatory guidelines that can be applied to nuclear facilities in Korea, in accordance with the Groundwater Act, Environmental Impact Assessment Act, and the Nuclear Safety Act.

• Journal of the Earthquake Engineering Society of Korea
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• v.21 no.2
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• pp.95-103
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• 2017

In order to modeling seismic isolation system such as lead-rubber bearing (LRB), bilinear model is widely used by many researchers. In general, an actual force-displacement relationship for LRB has a smooth hysteretic shape. So, Bouc-Wen model with smooth hysteretic shape represents more accurately actual hysteretic shape than bilinear model. In this study, seismic responses for seismically isolated nuclear power plant (NPP) with LRB modelled by Bouc-Wen and bilinear models are compared with those of NPP without seismic isolation system. To evaluate effect of earthquake characteristics for seismic responses of NPP isolated by LRB, 5 different site class earthquakes distinguished by Geomatrix 3rd Letter Site Classification and artificially generated earthquakes corresponding to standard design spectrum by Reg. Guide 1.60 are used as input earthquakes. From the seismic response results of seismically isolated NPP, it can be observed that maximum displacements of seismic isolation modelled by Bouc-Wen model are larger than those by bilinear model. Seismic responses of NPP with LRB is significantly reduced than those without LRB. This reduction effect for seismic responses of NPP subjected to Site A (rock) earthquakes is larger than that to Site E (soft soil) earthquakes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.2 s.173
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• pp.355-361
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• 2000

In this study, active control magnetic actuator for reducing vibration of rotor system is performed. Identification, modeling, simulation, control system design, and evaluation of active magnetic damper system have been researched. Power amplifier modeling, connected magnetic actuator and augmented by system identification, is included to establish a magnetic damper simulation which provides close performance correspondence to the physical plant. A magnetic actuator, digital controller using DSP(Digital Signal Processor), and bipolar operational power supply/amplifiers are developed to show the effectiveness of reducing rotor vibration. Also the curve fitting procedure to obtain the transfer function of frequency dependent components is developed. Two kinds of test are executed as sliding and oil bearing. Results presented in this paper will provide a well-defined technical parameters in designing magnetic damper system for the proposed rotor.

• KIEE International Transactions on Power Engineering
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• v.5A no.4
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• pp.385-389
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• 2005

Power transformers would appear to be simple. However, due to their nonlinear and frequency-dependent behaviors, they can be one of the most complex system components to model. It is imperative that the applied models be appropriate for the range of frequencies and excitation levels that the system experiences. Transformer modeling is not a mature field and newer improved models must be made available in ATP packages. Further, there is a lack of published guidance on recommended modeling approaches. And there is typically not enough detailed design or test information available to determine the parameters for a given model. The purpose of this paper is to develop improved transformer core models for ATP and parameter estimation methods that can efficiently utilize the limited available information such as factory test reports.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.175-180
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• 2005

Incorrections between model and plant are parameter, system order uncertainties and modeling error due to disturbance like friction. Therefore to achieve a good tracking performance, adaptive discrete time sliding mode tracking controller is used under time-varying desired position. Based on the diophantine equation, a new discrete time sliding function is defined and utilized for the control law. Robustness is increased by using both a recursive least-square method and a sliding function-based nonlinear feedback. The effectiveness of the proposed control algorithm is proved by the results of simulation and experiment.

• Journal of Power System Engineering
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• v.3 no.1
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• pp.50-54
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• 1999

In order to reject the steady-state tracking error, it is common to introduce integral compensators in servosystems for constant reference signals. However, if the mathematical model of the plant is exact and no disturbance input exists, the integral compensation is not necessary. From this point of view, a two-degree-of-freedom(2DOF) servosystem has been proposed, in which integral compensation is effective only when there is modeling error for disturbance input. The present paper considers the design problem of 2DOF servosystem incorporating an observer. It is shown that if a state feedback gain and a observer gain satisfy a condition, the integral effect does not appear when modeling error or disturbance input exists. This result means that the servosystem does not behave as a 2DOF servosystem.

• Nuclear Engineering and Technology
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• v.29 no.6
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• pp.433-443
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• 1997

In this work, an analytic approach to the dependability of software in the operational phase is suggested with special attention to the hardware fault effects on the software behavior : The hardware faults considered are memory faults and the dependability measure in question is the reliability. The model is based on the simple reliability theory and the graph theory which represents the software with graph composed of nodes and arcs. Through proper transformation, the graph can be reduced to a simple two-node graph and the software reliability is derived from this graph. Using this model, we predict the reliability of an application software in the digital system (ILS) in the nuclear power plant and show the sensitivity of the software reliability to the major physical parameters which affect the software failure in the normal operation phase. We also found that the effects of the hardware faults on the software failure should be considered for predicting the software dependability accurately in operation phase, especially for the software which is executed frequently. This modeling method is particularly attractive for the medium size programs such as the microprocessor-based nuclear safety logic program.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.943-945
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• 1998

This paper presents a method of modeling of DSTATCON (Distribution-line Static Condenser) for installation in a specific plant and analyze the effectiveness of the DSTATCON from the viewpoints of voltage regulation and harmonic mitigation in a distribution line. For the reliable modeling, detailed information on distribution system and loads is performed by field measurements. The DSTATCON has been modeled according to the control algorithm of real controller. The effectiveness of the DSTATCON installation is verified by simulation using EMTDC.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.171-178
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• 2018

Recently, the continuing operation of nuclear power plants has become a major controversial issue in Korea. Whether to continue to operate nuclear power plants is a matter to be determined considering many factors including social and political factors as well as economic factors. But in this paper we concentrate only on the economic factors to make an optimum decision on operating nuclear power plants. Decisions should be based on forecasts of plant accident risks and large and small accident data from power plants. We outline the structure of a decision model that incorporate accident risks. We formulate to decide whether to shutdown permanently, shutdown temporarily for maintenance, or to operate one period of time and then periodically repeat the analysis and decision process with additional information about new costs and risks. The forecasting model to predict nuclear power plant accidents is incorporated for an improved decision making. First, we build a one-period decision model and extend this theory to a multi-period model. In this paper we utilize influence diagrams as well as decision trees for modeling. And bayesian statistical approach is utilized. Many of the parameter values in this model may be set fairly subjective by decision makers. Once the parameter values have been determined, the model will be able to present the optimal decision according to that value.