• Journal of Ocean Engineering and Technology
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• v.29 no.6
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• pp.488-498
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• 2015

This paper presents the dynamic model of an AUV called HW200 for underwater surveillance. The mathematical model of HW200 is briefly introduced, considering its shape. The maneuvering coefficients were initially estimated using empirical formulas and a database of vehicles with similar shapes. A motion simulator, based on Simulink of Mathworks, was developed to evaluate the mathematical model of the vehicle and to tune the maneuvering coefficients. The parameters were finely tuned by comparing the experimental results and simulated responses generated with the simulator by applying the same control inputs as the experiment. The velocity of HW200 in the tuning process was fixed at a constant forward speed of 1.83 m/s. Simulations with variable speed commands were conducted, and the results showed good consistency in the motion response, attitude, and velocity of the vehicle, which were similar to those of the experiment even under the speed variation. This paper also discusses the feasibility of its application to a model-based integrated navigation system (INS) using the auxiliary information on the velocities generated by the model.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.904-907
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• 2007

We reported a simplified circuit model to investigate the interface states and the quality of a-Si film based on a MIS structure using admittance spectroscopy. The model can be employed easily to monitor the fabrication process of thin-film transistor and to obtain the important parameters.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.1
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• pp.21-29
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• 2022

Power generated from renewable energy has continuously increased recently. As the distributed generation begins to interconnect in the distribution system, an accurate generation forecasting has become important in efficient distribution planning. This paper explained method and current state of distributed power generation forecasting models. This paper presented selecting input and output variables for the forecasting model. In addition, this paper analyzed input variables and forecasting models that can use as mid-to long-term distributed power generation forecasting.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.3
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• pp.313-320
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• 2013

The fractional slot windings are widely used in rotating machine in order to increase the flexibility of design and improve the voltage waveform. However, the MMF wave of fractional-slot windings are found to contain unique harmonic component, which are designated as even order space flux harmonics, fractional number flux harmonics, or both. They may cause stray loss and stator core vibration. This paper proposes new winding methods "novel interspersed windings" and "expanded group windings" to reduce these harmonics. The advantages of two proposed windings are verified by using numerical analysis and measurement test of winding model.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.165-171
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• 2019

The steam turbine used in nuclear power plant is modeled for the purpose of verification of control system rather than the operator education. The valves, reheater and generator are modeled also and integrated into the simulator. After that, the operation data and the designed data such as heat balance diagram are utilized to identify the model parameters. It was evident that model outputs of developed simulator are very close to the measured operating ones. The simulator within dynamic model was used to verify and validate the whole control system together with field instruments. And the target plant has been operating long time.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.951-957
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• 2015

This Paper considers the heading and depth control problem for an underactuated AUV (Autonomous Underwater Vehicle) HW200. The HW200 is a torpedo-type AUV that is developed from Hanwha corporation R&D Center for military operation such as MCM (Mine Counter Measures). The HW200 controls horizontal and vertical motion with two stern plane and two rudder plane. It is well known that fine control of an AUV motion is not easy because of model uncertainties, highly nonlinear and coupled motions. To overcome those kind of uncertainties, a number of control methods have been presented. In this paper, the motion controllers of the HW200 are designed using PD controller design method based on the linear and perturbed model of the typical 6-DOF equations of an AUV, and confirmed the effectiveness of the controller through simulations and field test.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.2
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• pp.249-254
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• 2021

As the spreading speed of electric vehicles increases rapidly, those are expected to be able to use them as flexible resources in the power system beyond the concern for the supply of its charging power. Especially when the Renewable Energy sources (RES) which have no intrinsic control capability have replaced the synchronous generators more and more, the power system needs to secure the additional frequency control resources to ensure its stability. However, the feasibility of using electric vehicles as the frequency control resources should be analyzed from the perspective of the power system operation and it requires the existing simulation frameworks for the power system. Therefore, this paper proposes the grid connected modeling of the primary frequency control provided by electric vehicles which can be integrated into the existing power system model. In addition, the proposed model is implemented considering technical performances constrained by the characteristics of the Vehicle-Grid Integration (VGI) system so that the simulation results can be accepted by the power utilities operating the power system conservatively.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.413-418
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• 2020

It is necessary to manage the prediction accuracy of the machine learning model to prevent the decrease in the performance of the grid network condition prediction model due to overfitting of the initial training data and to continuously utilize the prediction model in the field by maintaining the prediction accuracy. In this paper, we propose an automation technique for maintaining the performance of the model, which increases the accuracy and reliability of the prediction model by considering the characteristics of the power grid state data that constantly changes due to various factors, and enables quality maintenance at a level applicable to the field. The proposed technique modeled a series of tasks for maintaining the performance of the power grid condition prediction model through the application of the workflow management technology in the form of a workflow, and then automated it to make the work more efficient. In addition, the reliability of the performance result is secured by evaluating the performance of the prediction model taking into account both the degree of change in the statistical characteristics of the data and the level of generalization of the prediction, which has not been attempted in the existing technology. Through this, the accuracy of the prediction model is maintained at a certain level, and further new development of predictive models with excellent performance is possible. As a result, the proposed technique not only solves the problem of performance degradation of the predictive model, but also improves the field utilization of the condition prediction model in a complex power grid system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.4
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• pp.283-289
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• 2018

Launch Acceptability Region(LAR) means an area for successfully hitting the target. And LAR should be calculated in real time on aircraft so that LAR can be seen by pilot. LAR can be changed by the launch condition of the bomb, the impact condition of the target, and the atmospheric condition at the time of flight of the bomb. In this paper, we propose the calculation method of LAR using Artificial Neural Network(ANN). The learning data was generated by changing each condition from existing LAR model, and LAR model was derived through ANN learning. We confirmed the accuracy of the new LAR model by comparing the difference between the result data of existing LAR model and the new LAR model. And we confirmed the possibility of real time calculation of the LAR model on the aircraft by comparing the calculation time.

• Journal of Ginseng Research
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• v.40 no.1
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• pp.90-96
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• 2016

Background: Knowledge on microclimate conditions under artificial shades in a ginseng field would facilitate climate-aware management of ginseng production. Methods: Weather data were measured under the shade and outside the shade at two fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012 seasons to assess temperature and humidity conditions under the shade. An empirical approach was developed and validated for the estimation of leaf wetness duration (LWD) using weather measurements outside the shade as inputs to the model. Results: Air temperature and relative humidity were similar between under the shade and outside the shade. For example, temperature conditions favorable for ginseng growth, e.g., between $8^{\circ}C$ and $27^{\circ}C$, occurred slightly less frequently in hours during night times under the shade (91%) than outside (92%). Humidity conditions favorable for development of a foliar disease, e.g., relative humidity > 70%, occurred slightly more frequently under the shade (84%) than outside (82%). Effectiveness of correction schemes to an empirical LWD model differed by rainfall conditions for the estimation of LWD under the shade using weather measurements outside the shade as inputs to the model. During dew eligible days, a correction scheme to an empirical LWD model was slightly effective (10%) in reducing estimation errors under the shade. However, another correction approach during rainfall eligible days reduced errors of LWD estimation by 17%. Conclusion: Weather measurements outside the shade and LWD estimates derived from these measurements would be useful as inputs for decision support systems to predict ginseng growth and disease development.