• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.4
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• pp.295-300
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• 2014

The frequency is an important operating parameter of a power system. There is an increasing importance of constant monitoring of frequency to achieve stable power supply by WAMS(wide area monitoring system) and FNET(Frequency Monitoring Network). This paper is part of development of a network-based frequency monitoring and failure prediction system for wide-area intelligent protection relaying. In this paper, analysis of propagation speed of power frequency by generation drop using the PSS/E was carried out. For dynamic analysis, the 11 metropolitan areas offices of KEPCO divided into five groups of Seoul, Gangwon, Chungcheong, Honam, and Yeongnam group, study was performed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.9
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• pp.567-569
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• 2005

NARX(Nonlinear AutoRegressive with eXogenous input) neural network was used for prediction of nuclear reactor behavior which was influenced by control rods in short-term period and also by the concentration of xenon and boron in long-term period in load following operations. The developed model was designed to predict reactor power, xenon worth and axial offset with different burnup states when control rods and boron were adjusted in load following operations. Data of the Korea Next Generation PWR were collected by ONED94 code. The test results presented exhibit the capability of the NARX neural network model to capture the long term and short term dynamics of the reactor core and the developed model seems to be utilized as a handy tool for the use of a plant simulation.

• Journal of Integrative Natural Science
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• v.12 no.1
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• pp.20-23
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• 2019

Demand response is usually operated through using the power rates and incentives. Demand management based on power charges is the most rational and efficient demand management method, and such methods include rolling base charges with peak time, sliding scaling charges depending on time, sliding scaling charges depending on seasons, and nighttime power charges. Search for other methods to stimulate resources on demand by actively deriving the demand reaction of loads to increase the energy efficiency of loads. In this paper, ESS algorithm for saving energy based on predicting the amount of solar power generation that can be used for buildings with small loads not under electrical grid.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.82.3-82.3
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• 2019

In this study, we generate future full disk magnetograms in 12, 24, 36 and 48 hours advance from SDO/HMI images using deep learning. To perform this generation, we apply the convolutional generative adversarial network (cGAN) algorithm to a series of SDO/HMI magnetograms. We use SDO/HMI data from 2011 to 2016 for training four models. The models make AI-generated images for 2017 HMI data and compare them with the actual HMI magnetograms for evaluation. The AI-generated images by each model are very similar to the actual images. The average correlation coefficient between the two images for about 600 data sets are about 0.85 for four models. We are examining hundreds of active regions for more detail comparison. In the future we will use pix2pix HD and video2video translation networks for image prediction.

• Aerospace Engineering and Technology
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• v.13 no.1
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• pp.44-54
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• 2014

This paper suggests two kinds of reaction control system command generation methods for upper stage attitude control of launch vehicles. The reaction control system is assumed to consist of two sets of three nozzles. One operation technology is based on mixed attitude error functions, and the other is based on command mixing functions. Both are compared via simulations. The simulation results show that the latter is comparatively preferable in terms of interference among control axes, independency of controller design and analysis among axes, and prediction of flight performance of each control axis.

• The KSFM Journal of Fluid Machinery
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• v.1 no.1 s.1
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• pp.7-16
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• 1998

An interactive mode of grid generation system has been developed for a Navier-Stokes design procedure of axial flow compressors. The present grid generator adopts the multiblock H-grid structure, which simplifies the creation of computational grids about complex turbomachinery geometries and facilitate the manipulation of multiple grid blocks for multirow flow fields. The numerical algorithm adopts the combination of the algebraic and elliptic method to create the internal grids efficiently and quickly. The system consists of four separated modules, which are linked together with a common graphical user interface. The system input is made of the results of the preliminary design. The final grids generated from each module of the system are used as the preprocessor for the performance prediction of the two-or three-dimensional flow simulation inside the blade passage. Application to the blade design of the LP compressor was demonstrated to be very reliable and practical in support of design activities. This customized system are coupled strongly with the design procedure of the turbomachinery cascades using the Navier-Stokes technique.

• The KSFM Journal of Fluid Machinery
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• v.16 no.1
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• pp.11-16
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• 2013

A numerical study was conducted to improve the performance of an impeller of centrifugal compressor. Nine design variables were chosen with constraints. Only meridional contours and blade profile were adjusted. ANN (Artificial Neural Net) was adopted as a main optimization algorithm with PSO (Particle Swarm Optimization) in order to reduce the optimization time. At first, ANN was learned and trained with the design variable sets which were obtained using DOE (Design of Experiment). This ANN was continuously improved its accuracy for each generation of which population was one hundred. New design variable set in each generation was selected using a non-gradient based method of PSO in order to obtain the global optimized result. After $7^{th}$ generation, the prediction difference of efficiency and pressure ratio between ANN and CFD was less than 0.6%. From more than 1,200 design variable sets, a pareto of efficiency versus pressure ratio was obtained and an optimized result was selected based on the multi-objective function. On this optimized impeller, the efficiency and pressure ratio were improved by 1% and 9.3%, respectively.

• Journal of the Korean Ceramic Society
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• v.42 no.12 s.283
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• pp.846-853
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• 2005

For the performance prediction of a planar-type solid oxide fuel cell, the computational analysis of transport phenomena with a simplified treatment of heat generation by the electrochemical reaction is conducted. From the result of the computational analysis, it is shown that the electrochemical reaction is closely related to the transport phenomena inside a solid oxide fuel cell. Transport phenomena including heat and mass transfer influences on the distribution of local current density and, as a result, on the performance characteristics of the fuel cell. Computational analysis is also extended to the parametric study to investigate the performance behavior of the fuel cell with different amount of supplied fuel flow rates. It is also demonstrated that the mathematical formulation and computational procedures proposed in this study can be applied to prove the importance of the specific TPB area in the manufacturing process of electrodes in solid oxide fuel cells.

• Wind and Structures
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• v.5 no.1
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• pp.25-48
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• 2002

Wind flow and pressure on the roof of the Texas Tech Experimental Building are studied along with the incident wind in an effort to understand the wind-structure interaction and the mechanisms of roof pressure generation. Two distinct flow phenomena, cornering vortices and separation bubble, are investigated. It is found for the cornering vortices that the incident wind angle that favors formation of strong vortices is bounded in a range of approximately 50 degrees symmetrical about the roof-corner bisector. Peak pressures on the roof corner are produced by wind gusts approaching at wind angles conducive to strong vortex formation. A simple analytical model is established to predict fluctuating pressure coefficients on the leading roof corner from the knowledge of the mean pressure coefficients and the incident wind. For the separation bubble situation, the mean structure of the separation bubble is established. The role of incident wind turbulence in pressure-generation mechanisms for the two flow phenomena is better understood.

• Clinical and Experimental Pediatrics
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• v.63 no.6
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• pp.195-202
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• 2020

Developments in next-generation sequencing (NGS) techogies have assisted in clarifying the diagnosis and treatment of developmental delay/intellectual disability (DD/ID) via molecular genetic testing. Advances in DNA sequencing technology have not only allowed the evolution of targeted panels but also, and more currently enabled genome-wide analyses to progress from research era to clinical practice. Broad acceptance of accuracy-guided targeted gene panel, whole-exome sequencing (WES), and whole-genome sequencing (WGS) for DD/ID need prospective analyses of the increasing cost-effectiveness versus conventional genetic testing. Choosing the appropriate sequencing method requires individual planning. Data are required to guide best-practice recommendations for genomic testing, regarding various clinical phenotypes in an etiologic approach. Targeted panel testing may be recommended as a firsttier testing approach for children with DD/ID. Family-based trio testing by WES/WGS can be used as a second test for DD/ID in undiagnosed children who previously tested negative on a targeted panel. The role of NGS in molecular diagnostics, treatment, prediction of prognosis will continue to increase further in the coming years. Given the rapid pace of changes in the past 10 years, all medical providers should be aware of the changes in the transformative genetics field.