• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.6
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• pp.295-300
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• 2003

Voltage instability has been studied for some decade now. But, There is not generally accepted definition of voltage instability because of the complex phenomenon and the variety of ways in which it can manifest itself. Both IEEE and CIGRE have the respective definitions. The areas of voltage instability research are the analysis, simulation and countermeasure of voltage instability. It needs to model the components of the power system to simulate the voltage instability and voltage collapse. At the beginning, the static simulation was used. This method provides the voltage stability indices and it requires less CPU resource and gives much insight into the voltage and power problem. However, it is less accurate than the dynamic simulation peformed in the time domain simulation. So, when it appears difficult to secure the voltage stability margin in a static stability, it is necessary to perform the dynamic simulation. To perform time-domain simulation, we have to model the dynamic component of the power system like a generator and a load. The dynamic simulation provides the accurate result of the voltage instability. But, it is not able to provide the sensitivity information or the degree of stability and it is time consuming and it needs much CPU resource. In this Paper, we perform a dynamic simulation of voltage instability and voltage collapse using EMTP MODELS. The exponential load model is designed with MODEIS and this load model is connected with test power system. The result shows the process of voltage change in time domain when the voltage instability or voltage collapse occurs.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.2
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• pp.94-102
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• 2000

This paper presents a new FDI scheme based on dynamic fuzzy model(DFM) for the unknown nonlinear system, which can detect and isolate process faults continuously over all ranges of operating condition. The dynamic behavior of a nonlinear process is represented by a set of local linear models. The parameters of the DFM are identified by an on-line methods. The residual vector of the FDI system is consisted of the parameter deviations from nominal model and the set of grade of membership values indicating the operating condition of the nonlinear process. The detection and isolation of faults are performed via a neural network classifier that are learned the relationship between the residual vector and fault type. We apply the proposed FDI scheme to the FDI system design for a two-tank system and show the usefulness of the proposed scheme.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.8
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• pp.8-17
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• 2019

In this study, a model reduction technique was used to develop a precise noise and vibration prediction model for the individual components of a driveline system. The dynamic reduced-order model generated by the Craig-Bampton method was applied to perform dynamic analysis of an electric agricultural power cart. The natural frequency and acceleration response results were analyzed according to the different number of dominant sub-structural modes contained in the reduced-order models. Through the analysis results, it was confirmed that a sufficient number of dominant sub-structures to satisfy the operating conditions should be selected to construct an optimal reduced-order model.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.3
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• pp.93-114
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• 2002

This paper suggests a dynamic balanced scorecard (DBSC) model employing the concept of system dynamics (SD), which could overcome the limitations inherent in the conventional balanced scorecard (BSC) and facilitate strategic learning process in organizations. The BSC has been a successful framework for measuring an organization＇s performance in various Perspectives through translating an organization＇s vision and strategy into an interrelated set of key performance indicators and specific actions. The BSC, while having significant strengths over traditional performance measurement methods, however, has its own limitations, due to its static nature, such as overlooking two-way causation between performance Indicators and neglecting the impact of delayed feedback flowing from the adoption of new strategies or policy changes. To overcome these limitations, we employs SD, a methodology for understanding complex systems where dynamic feedback among the interrelated system components significantly impact on the system outcomes. The SD simulation model in the form of DBSC we suggest in this paper would serve as a useful strategic learning tool for facilitating an organization＇s communication process through various scenario analyses as well as predicting the dynamic behavior pattern of their key performance measures over a future time frame. For the demonstration purpose, we apply the DBSC model to Korea Coal Corporation (KoCoal ) BSC case.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1999.04a
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• pp.61-68
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• 1999

In the nonlinear dynamic structural analysis the given ground excitation as an input should be well defined. Because of the lack of recorded accelerograms in Korea it is required to generate an artificial earthquake by a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms. It is well known that earthquake motions are generally non-stationary with time-varying intensity and frequency content. Many researchers have proposed non-stationary random process models. Yeh and Wen (1990) proposed a non-stationary modulation function and a power spectral density function to describe such non-stationary characteristics. Satio and Wen(1994) proposed a non-stationary stochastic process model to generate earthquake ground motions which are compatible with design reponse spectrum at sites in Japan. this paper shows the process to modify power spectrum compatible with target design response spectrum for generating of nonstationary artificial earthquake ground motions. Target reponse spectrum is chosen by ATC14 to calibrate the response spectrum according to a give recurrence period.

• Elastomers and Composites
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• v.34 no.4
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• pp.321-331
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• 1999

The curing process is the final step in tire manufacturing whereby a green tire built from layers of rubber compounds is formed to the desired shape and the compounds are converted to a strong, elastic materials to meet tire performance needs under elevated pressure and temperature in a press. A numerical optimization procedure was developed to improve product quality in a tire curing process. First, a dynamic constrained optimization problem was formulated to determine the optimal condition of the supplied cure media during a curing process. The objective function is subject to an equality constraint representing the process model that describes the heat transfer and cures kinetic phenomena in a cure press and is subject to inequality constraints representing temperature limits imposed on cure media. Then, the optimization problem was solved to determine optimal condition of the supplied cure media for a tire using the complex algorithm along with a finite element model solver.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.289-294
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• 1988

This paper describes tbe design and implementation of the adaptive controller to maintain the glood weld quality in gas metal arc welding process. The weld torch travel speed and the surface temperature are taken, respectively, as an input and an output of the welding control system. Because of the very complex phenomena of the process, the input-output dynamic model was experimentally identified by AIC (Akiake Information Criterion). Based on the model structure, the explicit model reference adaptive controller is simulated in order to regulate the output tempernture to the desired level.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.106.2-106.2
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• 2010

IGCC (Integrated Gasification Combined Cycle) plants are among the most advanced and effective systems for electric energy generation. From a control perspective, IGCC plants represent a significant challenge: complex reactions, highly integrated control to simultaneously satisfy production, controllability, operability and environmental objectives. While all these requirements seem clearly to demand a multivatiable, model predictive approach, not many applications can be easily found in the literature. This paper describes the IGCC dynamic simulation that is capable of simulating plant startup, shutdown, normal, and abnormal operation and engineering studies. This high fidelity dynamic models contain the detailed process design data to produce realistic responses to process operation and upset. And the simulation is used by engineers to evaluate the transient performance and produce graphical information indicating the response of the process under study conditions.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.35 no.3
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• pp.1-12
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• 2003

The complexity of the papermaking system accelerates interactions between a large number of variables involved. The process operation, therefore, is subject to frequent perturbations by disturbance. Dynamic modelling is a useful tool for characterizing the transient behavior and selecting the best control strategies to reject disturbances. In this study we developed a dynamic simulation model of a fine paper production process, which consists of stock preparation, wire sections, white water circulations, and broke system. It focused on dynamic simulation in its role for developing control strategies and studying control loop dynamics related to filler loading for ash control. The results emphasized the importance of filler-loading position and length of control loop for rapid ash control and process stabilization.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2757-2772
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• 2023

The fluid retention effect of the Volume Control Tank (VCT) leads to a long time delay in Reactor Coolant System (RCS) concentration during the boration process. A coupled model combining a lumped-parameter sub-model and a computational fluid dynamics sub-model is currently used to investigate the concentration dynamic characteristic of RCS during the boration process. This model is validated by comparison with experimental data, and the predicted results show excellent agreement with experimental data. We provide detailed fields in VCT and concentration variations of RCS to study the interaction between mixing in VCT and the transient responses of RCS. Moreover, the impacts of the inlet flow rate, inlet nozzle diameter, original concentration, and replenishing temperature of VCT on the RCS concentration characteristic are studied. The inlet flow rate and nozzle diameter of VCT remarkably affect the RCS concentration characteristic. Too-large or too-small inlet flow rates and nozzle diameters will lead to unacceptable long delays. In this work, the optimal inlet flow rate and nozzle diameter of VCT are 5 m³/h and 58.8 mm, respectively. Besides, the impacts of the original concentration and replenishing temperature of VCT are negligible under normal operating conditions.