• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.6
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• pp.494-502
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• 2014

This paper presents a control method of the modular multilevel converter - high-voltage direct current (MMC-HVDC) system to regulate grid voltage on the basis of the Jeju Island power system. In this case, the MMC-HVDC system is controlled as a static synchronous compensator (Statcom) to exchange the reactive power with the power grid. The operation of the MMC-HVDC system is verified by using the PSCAD/EMTDC simulation program. The Jeju Island power system is first established on the basis of the parameters and measured data from the real Jeju Island power system. This power system consists of two line-commutated converter - high-voltage direct current (LCC-HVDC) systems, two Statcom systems, wind farms, thermal power plants, transformers, and transmission and distribution lines. The proposed control method is then applied by replacing one LCC-HVDC system with a MMC-HVDC system. Simulation results with and without using the MMC-HVDC system are compared to evaluate the effectiveness of the control method.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.469-474
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• 1997

To provide tile information ell severe accident progression is very important for advanced or new type of nuclear power plant (NPP) design. A parametric study, therefore was performed to investigate the effect of thermal hydraulic design parameters ell severe accident progression of pressurized water reactors (PWRs), Nine parameters, which are considered important in NPP design or severe accident progression, were selected among the various thermal hydraulic design parameters. The backpropagation neural network (BPN) was used to determine parameters, which might more strongly affect the severe accident progression, among mile parameters. For training. different input patterns were generated by the latin hypercube sampling (LHS) technique and then different target patterns that contain core uncovery time and vessel failure time were obtained for Young Gwang Nuclear (YGN) Units 3&4 using modular accident analysis program (MAAP) 3.0B code. Three different severe accident scenarios, such as two loss of coolant accidents (LOCAs) and station blackout(SBO), were considered in this analysis. Results indicated that design parameters related to refueling water storage tank (RWST), accumulator and steam generator (S/G) have more dominant effects on the progression of severe accidents investigated, compared to tile other six parameters.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.2
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• pp.103-115
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• 2018

This paper performs a numerical computation of ship maneuvering performance in waves. For this purpose, modular-type model (MMG (Mathematical Modeling Group) model) is adopted for maneuvering simulation and wave drift force is included in the equation of maneuvering motion. In order to compute wave drift force, two different seakeeping programs are used: AdFLOW based on Wave Green function method and SWAN based on Rankine panel method. When wave drift force is calculated using SWAN program, not only ship forward speed but also ship lateral speed are considered. By doing this, effects of lateral speed on wave drift force and maneuvering performance in waves are confirmed. The developed method is validated by comparing turning test results in regular waves with existing experimental data. Sensitivities of wave drift force on maneuvering performance are, also, checked.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.1
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• pp.59-71
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• 2008

In this paper, a software framework that integrates computational and experimental simulation has been developed to simulate and test a large-scale structural system under earthquake loading. The proposed software framework does not need development of the computer codes for both dynamic and static simulations. Any general-purpose software can be utilized with a main control module and interface APIs. This opens up a new opportunity to facilitate use of sophisticated finite elements into hybrid simulation regime to enhance accuracy and efficiency of simulations. The software framework described in the paper is modular and uses object oriented programming concepts. A series of illustrative examples demonstrate that the system is fully-functional and is capable of running any number of experimental and/or analytical components.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.6
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• pp.516-527
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• 2011

This paper considers a numerical analysis of ship maneuvering performance in the high amplitude incident waves by adopting linear and nonlinear ship motion analysis. A time-domain ship motion program is developed to solve the wave-body interaction problem with the ship slip speed and rotation, and it is coupled with a modular type 4-DOF maneuvering problem. Nonlinear Froude-Krylov and restoring forces are included to consider weakly nonlinear ship motion. The developed method is applied to observe the nonlinear ship motion and planar trajectories in maneuvering test in the presence of incident waves. The comparisons are made for S-175 containership with existing experimental data. The nonlinear computation results show a fair agreement of overall tendency in maneuvering performance. In addition, maneuvering performances with respect to wave slope is predicted and reasonable results are observed.

• The KIPS Transactions:PartC
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• v.9C no.2
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• pp.163-172
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• 2002

Java Card API porvide benifit for development program based on smart card using limmited resource. This APIs does not support arithmetic operations such as modular arithmetic, greatest common divisor calculation, and generation and certification of prime number, which is necessary arithmetic in PKI algorithm implementation. In this paper, we implement class BigInteger acted in the Java Card platform because that Java Card APIs does not support class BigInteger necessary in implementation of PKI algorithm.

• Journal of Power Electronics
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• v.18 no.1
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• pp.204-211
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• 2018

At present, one of two LCC-HVDC systems is responsible for controlling the grid frequency of the Jeju Island Power System (JIPS). The grid voltage is regulated by using STATCOMs. However, these two objectives can be achieved in one device that is called by a modular multilevel converter-high voltage direct current (MMC-HVDC) system. Therefore, this paper proposes frequency and voltage control strategies for the JIPS based on a MMC-HVDC system. In this case, the ancillary frequency and voltage controllers are implemented into the MMC-HVDC system. The modelling of the JIPS is done based on the parameters and measured data from the real JIPS. The simulation results obtained from the PSCAD/EMTDC simulation program are confirmed by comparing them to measured data from the real JIPS. Then, the effect of the MMC-HVDC system on the JIPS will be tested in many cases of operation when the JIPS operates with and without STATCOMs. The objective is to demonstrate the effectiveness of the proposed control strategy.

• Nuclear Engineering and Technology
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• v.45 no.4
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• pp.439-458
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• 2013

REX-10 is a fully-passive small modular reactor in which the coolant flow is driven by natural circulation, the RCS is pressurized by a steam-gas pressurizer, and the decay heat is removed by the PRHRS. To confirm design decisions and analyze the transient responses of an integral PWR such as REX-10, a thermal-hydraulic system code named TAPINS (Thermal-hydraulic Analysis Program for INtegral reactor System) is developed in this study. Based on a one-dimensional four-equation drift-flux model, TAPINS incorporates mathematical models for the core, the helical-coil steam generator, and the steam-gas pressurizer. The system of difference equations derived from the semi-implicit finite-difference scheme is numerically solved by the Newton Block Gauss Seidel (NBGS) method. TAPINS is characterized by applicability to transients with non-equilibrium effects, better prediction of the transient behavior of a pressurizer containing non-condensable gas, and code assessment by using the experimental data from the autonomous integral effect tests in the RTF (REX-10 Test Facility). Details on the hydrodynamic models as well as a part of validation results that reveal the features of TAPINS are presented in this paper.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2547-2555
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• 2021

The frequency of reactor coolant leakage is expected to increase over the lifetime of a nuclear power plant owing to degradation mechanisms, such as flow-acceleration corrosion and stress corrosion cracking. When loss of coolant accidents (LOCAs) occur, several parameters change rapidly depending on the size and location of the cracks. In this study, leak flow during LOCAs is predicted using a deep fuzzy neural network (DFNN) model. The DFNN model is based on fuzzy neural network (FNN) modules and has a structure where the FNN modules are sequentially connected. Because the DFNN model is based on the FNN modules, the performance factors are the number of FNN modules and the parameters of the FNN module. These parameters are determined by a least-squares method combined with a genetic algorithm; the number of FNN modules is determined automatically by cross checking a fitness function using the verification dataset output to prevent an overfitting problem. To acquire the data of LOCAs, an optimized power reactor-1000 was simulated using a modular accident analysis program code. The predicted results of the DFNN model are found to be superior to those predicted in previous works. The leak flow prediction results obtained in this study will be useful to check the core integrity in nuclear power plant during LOCAs. This information is also expected to reduce the workload of the operators.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.723-730
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• 2019

Acquiring instrumentation signals generated from nuclear power plants (NPPs) is essential to maintain nuclear reactor integrity or to mitigate an abnormal state under normal operating conditions or severe accident circumstances. However, various safety-critical instrumentation signals from NPPs cannot be accurately measured on account of instrument degradation or failure under severe accident circumstances. Reactor vessel (RV) water level, which is an accident monitoring variable directly related to reactor cooling and prevention of core exposure, was predicted by applying a few signals to deep neural networks (DNNs) during severe accidents in NPPs. Signal data were obtained by simulating the postulated loss-of-coolant accidents at hot- and cold-legs, and steam generator tube rupture using modular accident analysis program code as actual NPP accidents rarely happen. To optimize the DNN model for RV water level prediction, a genetic algorithm was used to select the numbers of hidden layers and nodes. The proposed DNN model had a small root mean square error for RV water level prediction, and performed better than the cascaded fuzzy neural network model of the previous study. Consequently, the DNN model is considered to perform well enough to provide supporting information on the RV water level to operators.