• Atmosphere
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• v.29 no.2
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• pp.219-226
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• 2019

Generally, the weather forecast system has been run using prescribed ocean condition. As it is widely known that coupling between atmosphere and ocean process produces consistent initial condition at all-time scales to improve forecast skill, there are many trials on the application of data assimilation of coupled model. In this study, we implemented a weakly coupled data assimilation (short for WCDA) system in global NWP model with low horizontal resolution for coupled forecast with uncoupled initialization, following WCDA system at the Met Office. The experiment is carried out for a typhoon evolution forecast in 2017. Air-sea exchange process provides SST cooling and gives a substantial impact on tendency of central pressure changes in the decaying phase of the typhoon, except the underestimated central pressure. Coupled data assimilation is a challenging new area, requiring further work, but it would offer the potential for improving air-sea feedback process on NWP timescales and finally contributing forecast accuracy.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.145-152
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• 2021

Environmental change due to construction of large offshore wind farm has been a debate for a long time in Korea. There are various data acquired on hydrodynamics around this area before and during construction of offshore wind farm but no data during operation could be made due to delayed schedule. In this study, environmental change such as bathymetry change and scouring was forecasted using MIKE, numerical hydrodynamics model, and its results were validated using the observation data before and during construction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.395-400
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• 1999

At present, some evolutional system has been used to promote the efficiency of the DNC(Direct Numerical Control) Controller. However, these are many inconvenience to this operator because it lacks harmony in interaction between the computer and the NC(Numerical Control). Also, there are some controversial poults when data error occurs at the Data Input/output. According1y, this thesis explores a new Data Remote Control System. In this study, the NC Controller of the DNC network has to Bet full data by removing data error in this system. In this system, the main merits are easy manufacturing and the convenience of Data Input/output. That is, remote control of the NC machine tool is possible without mutual interaction between the computer and itself.

• Journal of ILASS-Korea
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• v.3 no.4
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• pp.65-76
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• 1998

An experimental and numerical study of a spray flow is performed to investigate the spray characteristics using an air-assisted atomizer. A Partical Dynamic Analyzer(PDA) is used to measure SMD, dmp velocity, and drop number density whose the initial conditions have considerable effect on the numerical results. The measured experimental data have been used to asses the accuracy of model predictions. Numerical investigation is made with the Eulerian - Lagrangian formulism. Turbulent dispersion effects using a Monte-Carlo method, turbulent modulation effect and entrainment of air are also numerically simulated. Results show that the numerical predictions of SSF(Stochastic Separated Flow) analysis yielded reasonable agreement with the experimental data. However, the model calculations for small drops produced the inconsistent numerical results due to the effect of surrounding air entrainment.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.1
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• pp.27-33
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• 1997

A neural network approach has been developed to determine the depth of a surface breaking crack in a steel plate from ultrasonic backscattering data. The network is trained by the use of feedforward three-layered network together with a back-scattering algorithm for error correction. The signal used for crack insonification is a mode converted 70$^{\circ}$transverse wave. A numerical analysis of back scattered field is carried out based on elastic wave theory, by the use of the boundary element method. The numerical data are calibrated by comparison with experimental data. The numerical analysis provides synthetic data for the training of the network. The training data have been calculated for cracks with specified increments of the crack depth. The performance of the network has been tested on other synthetic data and experimental data which are different from the training data.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.167-174
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• 2006

In this paper, the applicability of strain data to a strain-energy-based damage evaluation methodology in detecting damage in a beam-like structure is demonstrated. For the purpose of this study, one of the premier damage evaluation methodology based on modal amplitudes, the damage index method, is expanded to accomodate strain data, and the numerical and experimental verifications are conducted using numerical and experimental data. To compare the relative performance of damage detection, the damage evaluation using acceleration data is also performed for the same damage scenarios. The experimental strain and acceleration data are extracted from laboratory static and dynamic tests. The numerical and experimental studies show that the strain data as well as acceleration data can be utilized in detecting damage.

• Research in Mathematical Education
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• v.10 no.4 s.28
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• pp.259-288
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• 2006

This study considers the performance of students in Grades 5 to 10 on four tasks assessing students' ability to evaluate data presented in numerical form, for example, in a list or table, or in graphical form, for example, in a frequency graph or scatter graph. The ability to tell a story from data or a graph is an important aspect of statistical literacy. The samples provide the opportunity to consider the association of two pairs of items, one from each type of interpretation, numerical and graphical. Educational implications for the outcomes and the classroom use of the items are considered.

• Atmosphere
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• v.28 no.2
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• pp.163-174
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• 2018

In order to assimilate MHS satellite data into the convective scale model at KMA, ATOVS data are reprocessed to utilize the original high-resolution data. And then to improve the preprocessing experiments for cloud detection were performed and optimized to convective-scale model. The experiment which is land scattering index technique added to Observational Processing System to remove contaminated data showed the best result. The analysis fields with assimilation of MHS are verified against with ECMWF analysis fields and fit to other observations including Sonde, which shows improved results on relative humidity fields at sensitive level (850-300 hPa). As the relative humidity of upper troposphere increases, the bias and RMSE of geopotential height are decreased. This improved initial field has a very positive effect on the forecast performance of the model. According to improvement of model field, the Equitable Threat Score (ETS) of precipitation prediction of $1{\sim}20mm\;hr^{-1}$ was increased and this impact was maintained for 27 hours during experiment periods.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.300-302
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• 2008

For the evaluation of wind resources, numerical simulation was carried out as a tool for establishing wind map around the korean peninsula. Initial and boundary condition are given by 3 hourly RDAPS(Regional Data Assimilation and Prediction System) data of KMA(Korea Meteorology Administration) and high resolution terrain elevation land cover(30 seconds) data from USGS(United States Geological Survey). Furthermore, Data assimilation was adopted to improve initial meteorological data with buoy and QuikSCAT seawinds data. The simulation was performed from 2003 to 2006 year. To understand wind data correctly in complex terrain as the korean peninsula, at this research, Wind map was classified 4 categories by distance from coastline and elevation.

• Geomechanics and Engineering
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• v.31 no.3
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• pp.319-328
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• 2022

Ensuring the integrity of a country's infrastructure is necessary to protect surrounding communities in case of disaster. Embankment dam systems across the US are an essential component of infrastructure, referred to as lifeline structures. Embankment dams are crucial to the survival of life and if these structures were to fail, it is imperative that states be prepared. Southern California is particularly concerned with the stability of embankment dams due to the frequent seismic activity that occurs in the state. The purpose of this study was to create a numerical model of an existing embankment dam simulated under seismic loads using previously recorded data. The embankment dam that was studied in Los Angeles, California was outfitted with accelerometers provided by the California Strong Motion Instrumentation Program that have recorded strong motion data for decades and was processed by the Center for Engineering Strong Motion Data to be used in future engineering applications. The accelerometer data was then used to verify the numerical model that was created using finite element modeling software RS2. The results from this study showed Puddingstone Dam's simulated response was consistent with that experienced during previous earthquakes and therefore validated the predicted behavior from the numerical model. The study also identified areas of weakness and instability on the dam that posed the greatest risk for its failure. Following this study, the numerical model can now be used to predict the dam's response to future earthquakes, develop plans for its remediation, and for emergency response in case of disaster.