• Journal of Industrial Technology
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• v.21 no.B
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• pp.241-248
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• 2001

Normally at a flood season the operation of the dam depends on a short range weather forecast that makes many difficulties of the management at a dry season. It is needed to study the pattern of the long period rainfall. The concept of PMP(Probable Maximum Precipitation) was used for designing dam. From the concept, this study is applied the concept of monthly probable maximum precipitation for operating dam. It can be possible to let us know the appropriateness of a limiting water level at a rainy season. For the operation of dam at a dry season this study can predict roughly the flood season's pattern of precipitation by month or period, therfore the prediction of precipitation can rise efficient operation of a dam.

• Geomechanics and Engineering
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• v.13 no.2
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• pp.217-235
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• 2017

The stability prediction of shallow buried tunnels is one of the most difficult tasks in civil engineering. The aim of this work is to predict the state of collapse in shallow tunnel in layered soils by employing non-associated flow rule and nonlinear failure criterion within the framework of upper bound theorem. Particular emphasis is first given to consider the effects of dilation on the collapse mechanism of shallow tunnel. Furthermore, the seepage forces and surface settlement are considered to analyze the influence of different dilation coefficients on the collapse shape. Two different curve functions which describe two different soil layers are obtained by virtual work equations under the variational principle. The distinct characteristics of falling blocks up and down the water level are discussed in the present work. According to the numerical results, the potential collapse range decreases with the increase of the dilation coefficient. In layered soils, both of the single layer's dilation coefficient and two layers' dilation coefficients increase, the range of the potential collapse block reduces.

• Structural Engineering and Mechanics
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• v.52 no.1
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• pp.97-113
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• 2014

In the present work appropriate concrete material models have been proposed to predict drying shrinkage and specific creep of High-performance concrete (HPC) using Artificial Neural Network (ANN). The ANN models are trained, tested and validated using 106 different experimental measured set of data collected from different literatures. The developed models consist of 12 input parameters which include quantities of ingredients namely ordinary Portland cement, fly ash, silica fume, ground granulated blast-furnace slag, water, and other aggregate to cement ratio, volume to surface area ratio, compressive strength at age of loading, relative humidity, age of drying commencement and age of concrete. The Feed-forward backpropagation networks with Levenberg-Marquardt training function are chosen for proposed ANN models and same implemented on MATLAB platform. The results shows that the proposed ANN models are more rational as well as computationally more efficient to predict time-dependent properties of drying shrinkage and specific creep of HPC with high level accuracy.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.138-142
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• 2001

A comparison between theoretical and measured transfer function, which relates structure-borne noise source level to underwater radiated noise, of a naval ship is presented in this study. Transfer functions are obtained by dividing far field underwater noise by the value of structure borne noise source levels below machinery mounts. In prediction, statistical energy analysis of the whole ship structure is used to get vibration levels of wetted hull plates below water line. Then, far field radiated noise is calculated by summing up contributions from each plates using vibration levels and radiation efficiencies. And 1/3-octave band underwater sound pressure at the distance of 1 m away from the hull were measured to get experimental transfer functions. The two transfer functions are compared to show resonable agreements in spite of the subtle physical differences between each other.

• Journal of the Korean Geophysical Society
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• v.7 no.2
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• pp.121-134
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• 2004

This study has tried to develop the modified DRASTIC Model by supplying the parameters, such as structural lineament density and land-use, into conventional DRASTIC model, and to predict the potential of groundwater contamination using GIS in Hwanam 2 District, Gyeonggi Province, Korea. Since the aquifers in Korea is generally through the joints of rock-mass in hydrogeological environment, lineament density affects to the behavior of groundwater and contaminated plumes directly, and land-use reflect the effect of point or non-point source of contamination indirectly. For the statistical analysis, lattice-layers of each parameter were generated, and then level of confidence was assessed by analyzing each correlation coefficient. Groundwater contamination potential map was achieved as a final result by comparing modified DRASTIC potential and the amount of pollutant load logically. The result suggest the predictability of contamination potential in a specified area in the respects of hydrogeological aspect and water quality.

• Nuclear Engineering and Technology
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• v.52 no.12
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• pp.2709-2716
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• 2020

Compositions of large nuclear cores (e.g. boiling water reactors) are highly heterogeneous in terms of fuel composition, control rod insertions and flow regimes. For this reason, they usually lack high order of symmetry (e.g. 1/4, 1/8) making it difficult to estimate their neutronic parameters for large spaces of possible loading patterns. A detailed hyperparameter optimization technique (a combination of manual and Gaussian process search) is used to train and optimize deep neural networks for the prediction of three neutronic parameters for the Ringhals-1 BWR unit: power peaking factors (PPF), control rod bank level, and cycle length. Simulation data is generated based on half-symmetry using PARCS core simulator by shuffling a total of 196 assemblies. The results demonstrate a promising performance by the deep networks as acceptable mean absolute error values are found for the global maximum PPF (~0.2) and for the radially and axially averaged PPF (~0.05). The mean difference between targets and predictions for the control rod level is about 5% insertion depth. Lastly, cycle length labels are predicted with 82% accuracy. The results also demonstrate that 10,000 samples are adequate to capture about 80% of the high-dimensional space, with minor improvements found for larger number of samples. The promising findings of this work prove the ability of deep neural networks to resolve high dimensionality issues of large cores in the nuclear area.

• Journal of Korea Water Resources Association
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• v.51 no.8
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• pp.687-701
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• 2018

A multi-function weir is representative control structure in the stream flow. Estimation of accurate flood discharge according to gate operations and prediction of floodwave travel times at the downstream are very important in terms of water use and river management. This study analyzed the limitation and improvement through the current gate operation data on the Young-san river. in addition, flood discharge was calculated considering lower and upper water level condition and gate operating using the modified slope-area method in the Seoung-chon weir. As a result, the current state was required improvement because exceed the theoretical range and rapidly fluctuation of discharge coefficient, can not be considered difference between the upper and lower water level and the estimation by the regression equation. As a result of applying the proposed method in this study, the above mentioned limitations can be compensated, compared with the current discharge data. Also it was analyzed as more physically valid because using the evaluated hydraulic equation and estimate the slope and friction loss of natural stream by iteration and to reduce the error. In conclusion, the process carried out serves as a representative flow control point of the water system through reliable discharge estimation, it is expected that it will be possible to properly river management.

• Korean System Dynamics Review
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• v.9 no.2
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• pp.105-128
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• 2008

City of Gyeongju's referendum finally offered the long-waited low-level radioactive waste disposal site in November 2005. Gyeongju's positive decision was due to the various economic rewards and incentives the national government promised to the city. 300 billion won for an accepting bonus, the location of the headquarter building of the Korean Hydro and Nuclear Power Co., and the accelerator research center and 3.25 trillion won for supporting regional development program implementation. All of the above will affect the city's infrastructure and the citizens' economic and social lives. Population, land use, economic structure, SOC and quality of life will be affected. Some will be very positive, and some will be negative. This research project will see the future of the city and forecast the demographic, economic, physical and environmental changes of the city via computer simulation's system dynamics technique. This kind of simulation will help City of Gyeongju's what to prepare for the future. The population forecasting of the year 2046 will be 662,424 with the waste disposal site, and 327,274 without the waste disposal site in Gyeongju. The waste disposal site and regional supporting program will increase 184,246 Jobs more with 1,605 agriculture and fishery, 5,369 manufacturing shops and 27,577 shops. The population increase will bring 96,726 more houses constructed in the city. Land use will also be affected. More land will be developed. And road, water plant and waste water plant will be expanded as much. The city's financial structure will be expanded, due to the increased revenues from the waste disposal site, and property tax revenues from the middle-class employees of the company, and the high-powered scientists and technologists from the accelerator research center. All in all, the future of the city will be brighter after operating the nuclear waste disposal site inside the city.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.217-224
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• 2004

Open-coast storm surge computations are of value in planning and constructing engineering works, especially in coastal regions. Prediction of typhoon surge elevations is based primarily on the use of a numerical model in this study, since it is difficult to study these events in real time or with use of physical models. A simple quasi-two dimensional numerical model for storm surge is considered. In order to understand the model's underlying assumptions, range of validity, and application, we discussed several aspects of typhoons and the physical factors governing storm generation processes. We also followed the basic governing equation, together with the assumption generally taken in their development, to see the principle characteristics of the model from a physical as well as a mathematical point of view. The equations consistent with the model described here are reduced forms of the basic equations and their effects on the resulting numerical scheme are discussed. Finally we applied the model discussed above to a storm surge problem at Masan Bay, the south coast of Korea Effects of astronomical tide, initial water level, and atmospheric pressure setup are considered. We then analyzed the flood at the coastal city and proposed a reasonable way of flood control.

• Spatial Information Research
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• v.21 no.5
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• pp.63-72
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• 2013

This paper analyzed the flood propagation characteristics of each flood elevation due to failure of embankment in Muju Namdae Stream using recursive call algorithm. A flood propagation order by the flood elevation was estimated by setting destruction point at Beonggu and Chasan small dam through recursive call algorithm and then, the number of grids of each flood propagation order and accumulated inundation area were calculated. Based on the flood propagation order and the grid size of DEM, flood propagation time could be predicted each flood elevation. As a result, the study could identify the process of flood propagation through distribution characteristic of the flood propagation order obtained from recursive call algorithm, and could provide basic data for protection from flood disaster by selecting the flood vulnerable area through the gradient pattern of the graph for accumulated inundation area each flood propagation order. In addition, the prediction of the flood propagation time for each flood water level using this algorithm helped provide valuable information to calculate the evacuation path and time during the flood season by predicting the flood propagation time of each flood water level.