• KIEAE Journal
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• v.15 no.4
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• pp.105-110
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• 2015

Purpose: This study aimed at finding the optimal input variables of the artificial neural network-based predictive model for the optimal controls of the indoor temperature environment. By applying the optimal input variables to the predictive model, the required time for restoring the current indoor temperature during the setback period to the normal setpoint temperature can be more precisely calculated for the cooling season. The precise prediction results will support the advanced operation of the cooling system to condition the indoor temperature comfortably in a more energy-efficient manner. Method: Two major steps employing the numerical computer simulation method were conducted for developing an ANN model and finding the optimal input variables. In the first process, the initial ANN model was intuitively determined to have input neurons that seemed to have a relationship with the output neuron. The second process was conducted for finding the statistical relationship between the initial input variables and output variable. Result: Based on the statistical analysis, the optimal input variables were determined.

• International Journal of Advanced Culture Technology
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• v.4 no.2
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• pp.47-56
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• 2016

In transformer cooling systems, oil temperature is controlled through the use of a blower and oil pump. For this paper, set-point algorithms, a reset algorithm and control algorithms of the cooling system were developed by neural networks and fuzzy logics. The oil inlet temperature was set by a $2{\times}2{\times}1$ neural network, and the oil temperature difference was set by a $2{\times}3{\times}1$ neural network. Inputs used for these neural networks were the transformer operating ratio and the air inlet temperature. The inlet set temperature was reset by a fuzzy logic based on the transformer operating ratio and the oil outlet temperature. A blower was used to control the inlet oil temperature while the oil pump was used to control the oil temperature difference by fuzzy logics. In order to analysis the performance of these algorithms, the initial start-up test and the step change test were performed by using the dynamic model of a transformer cooling system. Test results showed that algorithms developed for this study were effective in controlling the oil temperature of a transformer cooling system.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.45-48
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• 1999

Model predictive control algorithm requires a relevant model of the system to be controlled. Unfortunately, the first principle model describing a polymerization reaction system has a large number of parameters to be estimated. Thus there is a need for the identification and control of a polymerization reactor system by using available input-output data. In this work, the polynomial auto-regressive moving average (ARMA) models are employed as the input-output model and combined into the nonlinear model predictive control algorithm based on the successive linearization method. Simulations are conducted to identify the continuous styrene polymerization reactor system. The input variables are the jacket inlet temperature and the feed flow rate whereas the output variables are the monomer conversion and the weight-average molecular weight. The polynomial ARMA models obtained by the system identification are used to control the monomer conversion and the weight-average molecular weight in a continuous styrene polymerization reactor It is demonstrated that the nonlinear model predictive controller based on the polynomial ARMA model tracks the step changes in the setpoint satisfactorily. In conclusion, the polynomial ARMA model is proven effective in controlling the continuous styrene polymerization reactor.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.3
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• pp.205-212
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• 2008

This paper describes the application of an inverse building model to a calibrated forward building model using EnergyPlus program. Typically, inverse models are trained using measured data. However, in this study, an inverse building model was trained using data generated by an EnergyPlus model for an actual office building. The EnergyPlus model was calibrated using field data for the building. A training data set for a month of July was generated from the EnergyPlus model to train the inverse model. Cooling load prediction of the trained inverse model was tested using another data set from the EnergyPlus model for a month of August. Predicted cooling loads showed good agreement with cooling loads from the EnergyPlus model with root-mean square errors of 4.11%. In addition, different control strategies with dynamic cooling setpoint variation were simulated using the inverse model. Peak cooling loads and daily cooling loads were compared for the dynamic simulation.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.622-627
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• 1996

Detailed analysis of Feedwater Line Break (FLB) event for the fuel failure point of view are lack because the event was characterized as the increase in reactor coolant system (RCS) pressure. Up to now, the potential of the rapid system heatup case has been emphasized and comprehensively studied. The cooldown effects of FLB event is considered to be bounded by the Steam Line Break (SLB) event since the cooldown effect of SLB event is larger than that of the FLB event. This analysis provides a new possible path which can cause the fuel failure. The new path means that the fuel failure can occur under the heatup scenario because the Pressurizer Safety Valves (PSVs) open before the reactor trips. The 1000 MWe typical C-E plant FLB event assuming Loss of Offsite Power (LOOP) at the turbine trip has been analyzed as an example and the results show less than 1% of the fuel failure. The result is well within the acceptance criteria. In addition to that, a study was accomplished to prevent the fuel failure for the heatup scenario case as an example. It is found that giving the proper pressure gap between High Pressurizer Pressure Trip (HPPT) analysis setpoint and the minimum PSV opening pressure could prevent the fuel failure.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.9
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• pp.997-1005
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• 1990

Integral Error and State Feedback (IESF) controller which incorporates state feedback as a modern control scheme and integral action as a classical control scheme has better performance than that of conventional PID controller in linear time invariant system. But the structure of the IESF controller requires all the state variables of the system and is applicable only to pole assignable linear time invariant systems without time delay. Many industrial processes have large time delay and it is impossible to directly apply IESF control scheme to those processes. In this paper, a new controller structure, Modified Integral Error and State Feedback (MIESF) has been suggested in order to effectively control processes having time delay and its performance has been analyzed and its effectiveness has also been confirmed. As the proposed controller uses output feedback scheme based on integral error and state feedback (IESF) method, it can be simply designed by pole assignment algorithm irrespective of the order of the process. The MIESF controller can follow setpoint changes without overshoot. It is robuster than conventional Smith-Predictor plus PI(D) controller in case of occurring time delay mismatch and extra parameter mismatches between the process and the model. It can enhance control performance by intentional time delay mismatch.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.1
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• pp.47-58
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• 2018

A solar array simulator (SAS) consists of an engine that generates a setpoint according to panel characteristics, a power stage that provides the actual output, and a controller. Particularly, if the control method is not suitable due to the nonlinearity of the solar panel output curve depending on the irradiation amount and the temperature, and the variation of the curve factor depending on the various panel materials, then the panel simulation function cannot be performed properly. Current and voltage mode controls are usually used for the conventional control method. However, these control methods deteriorate the control performance near the maximum power point; thus, a hybrid control method using two or more controllers has been investigated. In this study, we analyze the hybrid control method using three controllers divided into different areas. The design equation of the controller is derived based on the small signal modeling of each controller, and the simulation performance of the solar array simulator verifies its stability and response speed.

• Nuclear Engineering and Technology
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• v.48 no.4
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• pp.1047-1057
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• 2016

Design engineering process for field programmable gate array (FPGA)-based reactor trip functions are developed in this work. The process discussed in this work is based on the systems engineering approach. The overall design process is effectively implemented by combining with design and implementation processes. It transforms its overall development process from traditional V-model to Y-model. This approach gives the benefit of concurrent engineering of design work with software implementation. As a result, it reduces development time and effort. The design engineering process consisted of five activities, which are performed and discussed: needs/systems analysis; requirement analysis; functional analysis; design synthesis; and design verification and validation. Those activities are used to develop FPGA-based reactor bistable trip functions that trigger reactor trip when the process input value exceeds the setpoint. To implement design synthesis effectively, a model-based design technique is implied. The finite-state machine with data path structural modeling technique together with very high speed integrated circuit hardware description language and the Aldec Active-HDL tool are used to design, model, and verify the reactor bistable trip functions for nuclear power plants.

• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.355-362
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• 2012

The aim of this study was to develop a bundle position-wise linear model (BPLM) to predict Pressure Tube (PT) diametral creep employing the previously measured PT diameters and operating conditions. There are twelve bundles in a fuel channel, and for each bundle a linear model was developed by using the dependent variables, such as the fast neutron fluences and the bundle coolant temperatures. The training data set was selected using the subtractive clustering method. The data of 39 channels that consist of 80 percent of a total of 49 measured channels from Units 2, 3, and 4 of the Wolsung nuclear plant in Korea were used to develop the BPLM. The data from the remaining 10 channels were used to test the developed BPLM. The BPLM was optimized by the maximum likelihood estimation method. The developed BPLM to predict PT diametral creep was verified using the operating data gathered from Units 2, 3, and 4. Two error components for the BPLM, which are the epistemic error and the aleatory error, were generated. The diametral creep prediction and two error components will be used for the generation of the regional overpower trip setpoint at the corresponding effective full power days. The root mean square (RMS) errors were also generated and compared to those from the current prediction method. The RMS errors were found to be less than the previous errors.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.404-410
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• 1998

In Yonggwang nuclear units 3 and 4 currently under commercial operation, the cold leg temperature was very close to the technical specification limit of 298$^{\circ}C$ during initial startup testing, which was caused by the higher-than-expected reactor coolant system flow. Accordingly, the reference temperature (Tref) program needed to be revised to allow more flexibility for plant operations. In this study, the method of a specific test performed at Yonggwang nuclear unit 4 to revise the Tref program was described and the test results were discussed. In addition, the modified Tref program was evaluated on its potential impacts on system performance and safety. The methods of changing the Tref program and the associated pressurizer level setpoint program were also explained. Finally, for Ulchin nuclear unit 3 and 4 currently under initial startup testing, the effects of reactor coolant system flow rate on the coolant temperature were evaluated from the thermal hydraulic standpoint and an optimum Tref program was recommended.