• Nuclear Engineering and Technology
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• v.38 no.1
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• pp.81-92
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• 2006

In this study, the core dynamics of a PWR reactor is identified online by a recursive least-squares method. Based on the identified reactor model consisting of the control rod position and the core average coolant temperature, the future average coolant temperature is predicted. A model predictive control method is applied to designing an automatic controller for the thermal power control of PWR reactors. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, this procedure for solving the optimization problem is repeated. The objectives of the proposed model predictive controller are to minimize both the difference between the predicted core coolant temperature and the desired temperature, as well as minimizing the variation of the control rod positions. In addition, the objectives are subject to the maximum and minimum control rod positions as well as the maximum control rod speed. Therefore, a genetic algorithm that is appropriate for the accomplishment of multiple objectives is utilized in order to optimize the model predictive controller. A three-dimensional nuclear reactor analysis code, MASTER that was developed by the Korea Atomic Energy Research Institute (KAERI) , is used to verify the proposed controller for a nuclear reactor. From the results of a numerical simulation that was carried out in order to verify the performance of the proposed controller with a $5\%/min$ ramp increase or decrease of a desired load and a $10\%$ step increase or decrease (which were design requirements), it was found that the nuclear power level controlled by the proposed controller could track the desired power level very well.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.104-106
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• 2005

In this work, a PWR reactor core dynamics is identified online by a recursive least squares method. Based on this identified reactor model consisting of the control rod position and the core average coolant temperature, the future average coolant temperature is predicted. A model predictive control method is applied to design an automatic controller for thermal power control in PWRs. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, the procedure to solve the optimization problem is then repeated. The objectives of the proposed model predictive controller are to minimize both the difference between the predicted core coolant temperature and the desired one, and the variation of the control rod positions. Also, the objectives are subject to maximum and minimum control rod positions and maximum control rod speed. Therefore, the genetic algorithm that is appropriate to accomplish multiple objectives is used to optimize the model predictive controller. A 3-dimensional nuclear reactor analysis code, MASTER that was developed by Korea Atomic Energy Research Institute (KAERI), is used to verify the proposed controller for a nuclear reactor. From results of numerical simulation to check the performance of the proposed controller at the 5%/min ramp increase or decrease of a desired load and its 10% step increase or decrease which are design requirements, it was found that the nuclear power level controlled by the proposed controller could track the desired power level very well.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.478-484
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• 2018

This study predicts solar radiation, solar radiation, and solar power generation using hourly weather data such as temperature, precipitation, wind direction, wind speed, humidity, cloudiness, sunshine and solar radiation. I/O pattern in supervised learning is the most important factor in prediction, but it must be determined by repeated experiments because humans have to decide. This study proposed four input and output patterns for solar and sunrise prediction. In addition, we predicted solar power generation using the predicted solar and solar radiation data and power generation data of Youngam solar power plant in Jeollanamdo. As a experiment result, the model 4 showed the best prediction results in the sunshine and solar radiation prediction, and the RMSE of sunshine was 1.5 times and the sunshine RMSE was 3 times less than that of model 1. As a experiment result of solar power generation prediction, the best prediction result was obtained for model 4 as well as sunshine and solar radiation, and the RMSE was reduced by 2.7 times less than that of model 1.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.05a
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• pp.412-415
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• 2004

This study was performed to verify the behaviors of fiber Bragg grating (FBG) sensors attached to the containment structure in the nuclear power plant as a part of structural integrity test which demonstrates that the structural response of the non-prototype primary containment structure is within predicted limits plus tolerances when pressurized to $115\%$ of containment design pressure, and that the containment does not sustain any structural damage.

• Proceedings of the KSR Conference
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• 2000.11a
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• pp.142-149
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• 2000

It is required that the indoor-noise level of KHST (Korean high speed train) should be lower than 66 ㏈(A) at 350 km/h. In this study, the indoor-noise level of KHST has been predicted to determine the maximum allowable sound power levels of major noise sources. It is found that the indoor-noise requirement for KHST can be met by increasing the transmission losses of the floor and side-wall structures as well as by lowering the sound power levels of two major noise sources including the motor fans.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1995.05a
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• pp.113-116
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• 1995

Simplified approach has been adopted for the prediction of the thermal behavior of CANDU reactor core during power transients. Based on the assumption that the ratio of mass flow rate for each core channel does not vary during the transient, quasy-steady state analysis technique is applied with predicted core inlet boundary conditions(total mass flow rate and specific enthalpy). For restricted transient case, the presented method shows functionally reasonable estimation of core thermal behavior which could be implemented in the fast running reactor simulation program.

• Proceedings of the KSR Conference
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• 2002.05a
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• pp.29-34
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• 2002

In relation to the connection of South-North railway(Kyongui-Line), the operating speed of the train in Kyongui-Line was reviewed. Due to the insufficient maintenance to support on the track of north section of Kyongui-Line, it is very old. The plan that the train run in the north section faster than present time was studied. Finally, the electric power required in the north section was predicted.

• KEPCO Journal on Electric Power and Energy
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• v.3 no.1
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• pp.49-56
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• 2017

In order to examine the feasibility of Carbon Capture & Sequestration, a major technological strategy for the national goal of greenhouse gas reduction, this paper studies the various methods and corresponding costs for the transportation of $CO_2$ captured at the domestic thermal power plants, as well as performing comparative analysis with overseas CCS demonstration projects. It is predicted that the investment cost would be about 98 million USD when the using land-based pipelines to transport captured $CO_2$ from the thermal power plant located in the south coast. And using marine-based offshore pipelines, it will cost about twice the amount. When the captured $CO_2$ is transported from the power plant in the west coast instead, the cost is expected to increase substantially due to the transportation distance to the storage site being more than double to that of the south coast power plant case.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.2
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• pp.765-781
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• 2019

This study predicts the power consumption of an Electric Propulsion Ship (EPS) in marine environment. The EPS is driven by a propeller rotated by a propulsion motor, and the power consumption of the propeller changes by the marine environment. The propulsion motor consumes the highest percentage of the ships' total power. Therefore, it is necessary to predict the power consumption and determine the power generation capacity and the propeller capacity to design an efficient EPS. This study constructs a power estimation simulator for EPS by using a ship motion model including marine environment and an electric power consumption model. The usage factor that represents the relationship between power consumption and propulsion is applied to the simulator for power prediction. Four marine environment scenarios are set up and the power consumed by the propeller to maintain a constant ship speed according to the marine environment is predicted in each scenario.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.473-474
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• 2007

The Jeju power grid experienced several major power disturbances over the last decade. The postmortem studies of the incidents indicated that some of the generating units did not respond as predicted by system analysis & studies. Consequently, the Korean Power Exchange (KPX) mandated that all units (generators, excitation, governor and turbine systems) in the Korean network greater than or equal to 20MVA be tested to verify the generator reactive power limits as well as the dynamic model data being used for system studies. This paper presents field experiences of the authors in testing and modeling of steam turbines and their associated governors during the generator and model validation.