• Journal of Wetlands Research
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• 제18권1호
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• pp.76-83
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• 2016

In recent, the series of extreme storm events were occurred by those continuous typhoons and the severe flood damages due to the loss of life and the destruction of property were involved. In this study, we call Mega flood for the Extreme flood occurred by these successive storm events and so we can have a hypothetical Mega flood by assuming that a extreme event can be successively occurred with a certain time interval. Inter Event Time Definition (IETD) method was used to determine the time interval between continuous events in order to simulate Mega flood. Therefore, the continuous extreme rainfall events are determined with IETD then Mega flood is simulated by the consecutive events : (1) consecutive occurrence of two historical extreme events, (2) consecutive occurrence of two design events obtained by the frequency analysis based on the historical data. We have shown that Mega floods by continuous extreme rainfall events were increased by 6-17% when we compared to typical flood by a single event. We can expect that flood damage caused by Mega flood leads to much greater than damage driven by a single rainfall event. The second increase in the flood caused by heavy rain is not much compared to the first flood caused by heavy rain. But Continuous heavy rain brings the two times of flood damage. Therefore, flood damage caused by the virtual Mega flood of is judged to be very large. Here we used the hypothetical rainfall events which can occur Mega floods and this could be used for preparing for unexpected flood disaster by simulating Mega floods defined in this study.

• Journal of Korea Water Resources Association
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• 제48권9호
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• pp.729-741
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• 2015

This study examined the applicability of MBLRP (Modified Bartlett-Lewis Rectangular Pulse) rainfall generation model for an urban flood simulation which is a type of Poisson cluster rainfall generation model. This study constructed XP-SWMM model for Namgajwa area of Hongjecheon basin, which is a two-dimensional pipe network-surface flood simulation program and computed a flood discharge and a flooded area with input data of synthetic rainfall time series of 200 years that were generated by the MBLRP model. This study compared the data of flood with synthetic rainfall and flood with corresponding values which were based on design rainfall. The results showed that the flooded area computed with MBLRP model was somewhat smaller than the corresponding values on the basis of the design. A degree of underestimation was from 8% (5 year) to 34% (200 year) and the degree of underestimation increased as a return period increased. This study is meaningful in that it proposes methodology that enables quantifiability of uncertain variables which are related to a flooding through Monte Carlo analysis of urban flooding simulation and applicability and limitations thereof.

• Journal of Korean Society of Coastal and Ocean Engineers
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• 제32권2호
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• pp.106-121
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• 2020

In order to make harbor outskirt facilities robust using the reliability-based design, probabilistic models of wave heights at varying stage of shoaling process optimized for Korean sea waves are prerequisite. In this rationale, we numerically simulate the nonlinear shoaling process of random waves over the beach with a sandbar at its foreshore. In doing so, comprehensive numerical models made of spatially filtered Navier-Stokes Eq., LES [Large Eddy Simulation], dynamic Smagorinsky turbulence closure were used. Considering the characteristics of swells observed at the east coast of Korean Peninsula, random waves were simulated using JONSWAP wave spectrum of various peak enhancement coefficients and random phase method. The coefficients of probabilistic models proposed in this study are estimated from the results of frequency analysis of wave crests and its associated trough detected by Wave by Wave Analysis of the time series of numerically simulated free surface displacements based on the threshold crossing method. Numerical results show that Modified Glukhovskiy wave height distribution, the most referred probabilistic models at finite water depth in the literature, over-predicts the occurring probability of relatively large and small wave heights, and under predicts the occurrence rate of waves of moderate heights. On the other hand, probabilistic models developed in this study show vary encouraging agreements. In addition, the discrepancy of the Modified Glukhovskiy distribution from the measured one are most visible over the surf zone, and as a result, the Modified Glukhovskiy distribution should be applied with caution for the reliability-based design of harbor outskirt facilities deployed near the surf-zone.

• Korean Journal of Remote Sensing
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• 제15권2호
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• pp.131-146
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• 1999

The satellite visible data have been successfully applied to study the ocean color. Another ocean color sensor, the Ocean Scanning Multi-spectral Imager (OSMI) on the Korea Multi-Purpose Satellite (KOMPSAT) will be launched in 1999. In order to understand the characteristics of future OSMI images, we have first discussed the simulation models and procedures in detail, and produced typical patterns of radiances at visible bands by using radiative transfer models. The various simulated images of full satellite passes and Korean local areas for different seasons, water types, and the satellite crossing equator time (CET) are presented to illustrate the distribution of each component of radiance (i.e., aerosol scattering, Rayleigh scattering, sun glitter, water-leaving radiance, and total radiance). A method to evaluate the image quality and availability is then developed by using the characteristics of image defined as the Complex Signal Noise Ratio (CSNR). Meanwhile, a series of CSNR images are generated from the simulated radiance components for different cases, which can be used to evaluate the quality and availability of OSMI images before the KOMPSAT will be placed in orbit. Finally, the quality and availability of OSMI images are quantitatively analyzed by the simulated CSNR image. It is hoped that the results would be useful to all scientists who are in charge of OSMI mission and to those who plan to use the data from OSMI.

• Journal of Bio-Environment Control
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• 제31권3호
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• pp.152-162
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• 2022

This study developed simulation model for predicting the greenhouse interior environment using artificial intelligence machine learning techniques. Various methods have been studied to predict the internal environment of the greenhouse system. But the traditional simulation analysis method has a problem of low precision due to extraneous variables. In order to solve this problem, we developed a model for predicting the temperature inside the greenhouse using machine learning. Machine learning models are developed through data collection, characteristic analysis, and learning, and the accuracy of the model varies greatly depending on parameters and learning methods. Therefore, an optimal model derivation method according to data characteristics is required. As a result of the model development, the model accuracy increased as the parameters of the hidden unit increased. Optimal model was derived from the GRU algorithm and hidden unit 6 (r² = 0.9848 and RMSE = 0.5857℃). Through this study, it was confirmed that it is possible to develop a predictive model for the temperature inside the greenhouse using data outside the greenhouse. In addition, it was confirmed that application and comparative analysis were necessary for various greenhouse data. It is necessary that research for development environmental control system by improving the developed model to the forecasting stage.

• Journal of Information Technology Applications and Management
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• 제19권1호
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• pp.1-12
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• 2012

Data mining is the process of searching and analyzing large quantities of data for finding out meaningful patterns and rules. Artificial Neural Network (ANN) is one of the tools of data mining which is becoming very popular in forecasting the future values. Some of the areas where it is used are banking, medicine, retailing and fraud detection. In finance, artificial neural network is used in various disciplines including stock market forecasting. In the stock market time series, due to high volatility, it is very important to choose a model which reads volatility and forecasts the future values considering volatility as one of the major attributes for forecasting. In this paper, an attempt is made to develop two models - one using feed forward back propagation Artificial Neural Network and the other using Autoregressive Conditional Heteroskedasticity (ARCH) technique for forecasting stock market returns. Various parameters which are considered for the design of optimal ANN model development are input and output data normalization, transfer function and neuron/s at input, hidden and output layers, number of hidden layers, values with respect to momentum, learning rate and error tolerance. Simulations have been done using prices of daily close of Sensex. Stock market returns are chosen as input data and output is the forecasted return. Simulations of the Model have been done using MATLAB$^{(R)}$ 6.1.0.450 and EViews 4.1. Convergence and performance of models have been evaluated on the basis of the simulation results. Performance evaluation is done on the basis of the errors calculated between the actual and predicted values.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• 제32권10호
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• pp.67-76
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• 2004

This paper improves existing 'fly-the-wire' based autonomous station-keeping system, suitable for geostationary satellite and introduces results of computer simulations conducted to verify the algorithm. The on-board stationkeeping system receives pseudo-range signals from two ground equipments located with long baseline, determines the orbit error in realtime and generates orbit control commands. To reduce fuel consumption, this paper proposes an on-board orbit control logic using modified fly-the-wire method. The modified fly-the-wire method de-couples error components into two dynamic modes, harmonic and linear motion. The harmonic error components are removed by applying output commands produced by feedback controller, and the linear motions are controlled by the correction ${\Delta}V\;s$ added to reference maneuvers. The reference maneuvers are generated through the ground based computer simulation and embedded or uploaded into the on-board computer with time tags. Finally, the performance of the proposed algorithm is verified through a series of computer simulations.

• Journal of Environmental Science International
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• 제14권11호
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• pp.1015-1026
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• 2005

The southeastern coastal area of the Korean peninsula has a complex terrain including an irregular coastline and moderately high mountains. This implies that mesoscale circulations such as mountain-valley breeze and land-sea breeze can play an important role in wind field and ocean forcing. In this study, to improve the accuracy of complex coastal rind field(surface wind and sea surface wind), we carried out the sensitivity experiments based on PBL schemes in PSU/NCAR Mesoscale Model (MM5), which is being used in the operational system at Korea Meteorological Administration. Four widely used PBL parameterization schemes in sensitivity experiments were chosen: Medium-Range Forecast (MRF), High-resolution Blackadar, Eta, and Gayno-Seaman scheme. Thereafter, case(2004. 8. 26 - 8. 27) of weak-gradient flows was simulated, and the time series and the vertical profiles of the simulated wind speed and wind direction were compared with those of hourly surface observations (AWS, BUOY) and QuikSCAT data. In the simulated results, the strength of rind speed of all schemes was overestimated in complex coastal regions, while that of about four different schemes was underestimated in islands and over the sea. Sea surface wind using the Eta scheme showed the highest wind speed over the sea and its distribution was similar to the observational data. Horizontal distribution of the simulated wind direction was very similar to that of real observational data in case of all schemes. Simulated and observed vertical distribution of wind field was also similar under boundary layer(about 1 km), however the simulated wind speed was underestimated in upper layer.

• Journal of computational fluids engineering
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• 제21권2호
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• pp.112-119
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• 2016

NEXTSat-1 is the next-generation small-size artificial satellite system planed by the Satellite Technology Research Center(SatTReC) in Korea Advanced Institute of Science and Technology(KAIST). For the control of attitude and transition of the orbit, the system has adopted a RHM(Resisto-jet Head Module), which has a very simple geometry with a reasonable efficiency. An axisymmetric model is devised with two coil-resistance heaters using xenon(Xe) gas, and the minimum required specific impulse is 60 seconds under the thrust more than 30 milli-Newton. To design the module, seven basic parameters should be decided: the nozzle shape, the power distribution of heater, the pressure drop of filter, the diameter of nozzle throat, the slant length and the angle of nozzle, and the size of reservoir, etc. After quasi one-dimensional analysis, a theoretical value of specific impulse is calculated, and the optima of parameters are found out from the baseline with a series of multi-physical numerical simulations based on the compressible Navier-Stokes equations for gas and the heat conduction energy equation for solid. A commercial code, COMSOL Multiphysics is used for the computation with a FEM (finite element method) based numerical scheme. The final values of design parameters indicate 5.8% better performance than those of baseline design after the verification with all the tuned parameters. The present method should be effective to reduce the time cost of trial and error in the development of RHM, the thruster of NEXTSat-1.

• Journal of Korea Water Resources Association
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• 제45권5호
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• pp.455-464
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• 2012

In this study, a combined unsteady friction model has been developed to simulate the waterhammer phenomenon for the pipeline system. The method of characteristics has been employed as the modeling platform for the integration of the acceleration based model and the frequency dependant model for unsteady friction. Both Zielke's model and Ramos model were also compared with pressure measurements of a pilot plant pipeline system. In order to validate the modeling approach, a pipeline system equipped with the high frequency pressure data acquisition system was fabricated. The time series of pressure, introduced by a sudden valve closure, were obtained for two Reynolds numbers. A trial and error method was used to calibrate parameters for unsteady friction model. The comparison between different unsteady friction contributions in pressure variation provided the comprehensive understanding in the pressure damping mechanism of waterhammer. The proper evaluation of unsteady friction impact is a critical factor for accurate simulation of hydraulic transient.