• Journal of Korea Water Resources Association
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• v.33 no.6
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• pp.689-699
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• 2000

This paper presents the integrated storage function model (ISFM) to improve the accuracy of the storage function model (SFM) which is widely employed for flood runoff analysis and its forecasting in Korea. In order to achieve this objective, the optimization method is applied for estimation of parameters of the model which dominate the accuracy of the analysis, which is usually taken by empirical formulae, and they are treated as time dependent variables. The fuzzy control technique is used to detennine the time variant parameters. In addition, the ISFM can be applied to the combined routing of the watershed and the channel with a residual watershed.ershed.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.6
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• pp.119-130
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• 2010

The universal model for the parameter estimation of the Storage Function Model(SFM) was developed through the applications of the distributed model for various hypothetical watersheds and runoff conditions. The existing parameter estimation equations are based on observations and these equations which are derived from the restricted conditions are not sensitive to the variation of physical characteristics of a watershed. This study developed the universal model for the parameter estimation through the runoff simulations of 35,000 times. As the simulation results, we have known that the lag time is related to the longest stream channel characteristics and the storage coefficient is related to the watershed characteristics.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.2
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• pp.149-158
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• 2008

The parameters of each basin, required for the accurate analysis of flood runoff using Storage Function Model, are estimated. Prior to the estimation, sensitivity analysis and extraction of new regional topographic factors for Han River basin are conducted. Based on the result, the outflow constant of basin model is calculated through regression analysis in relation with pre-flood runoff depth. The storage constant of basin model is derived by the optimum storage constant equation, according to the flood event of each basin. The model using the mentioned parameters was compared with K-Water model of Korea Water Resources Corporation and the model of Han River Flood Control Office, and proved to correspond to the observed hydrograph more.

• Journal of Korean Society for Quality Management
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• v.41 no.1
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• pp.135-148
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• 2013

Purpose: This paper presents a method to evaluate the stockpile reliability of propelling charge for performance and storage safety with storage time. Methods: We consider a performance failure level is the amount of muzzle velocity drop which is the maximum allowed standard deviation multiplied by 6. The lifetime for performance is estimated by non-linear regression analysis. The state failure level is assumed that the content of stabilizer is below 0.2%. Because the degradation of stabilizer with storage time has both distribution of state and distribution of lifetime, it must be evaluated by stochastic process method such as gamma process. Results: It is estimated that the lifetime for performance is 59 years. The state distribution at each storage time can be shown from probability density function of degradation. It is estimated that the average lifetime as $B_{50}$ life is 33 years from cumulative failure distribution function curve. Conclusion: The lifetime for storage safety is shorter than for performance and we must consider both the lifetime for storage safety and the lifetime performance because of variation of degradation rate.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.6
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• pp.81-87
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• 2010

In order to calculate the accurate runoff from a basin, nonlinearity in the relationship between rainfall and runoff has to be considered. Many runoff calculation models assume the linearity in the relationship or are too complicated to be analyzed. Therefore, the storage function method has been used in the prediction of flood because of the simplicity of the model. The storage function method has five parameters with related to the basin and rainfall characteristics which can be estimated by the empirical trial and error method. To optimize these parameters, regression method or optimization techniques such as genetic algorithm have been used, however, it is not easy to optimize them because of the complexity of the method. In this study, the metamodel is proposed to estimate those model parameters. The metamodel is the combination of artificial neural network and genetic algorithm. The model is consisted of two stages. In the first stage, an artificial neural network is constructed using the given rainfall-runoff relationship. In the second stage, the parameters of the storage function method are estimated using genetic algorithm and the trained artificial neural network. The proposed metamodel is applied in the Peong Chang River basin and the results are presented.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.449-453
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• 2007

Has been being operated since 1974, recently, the flood forecasting and warning system is applied in almost all the rivers in Korea, and the Storage Function Method(SFM) is used for flood routing. The SFM which was presented by Toshimitsu Kimura(1961) routes floods in channels and basins with the storage function as the basic equation. A watershed is devided into two zone, runoff and percolation area and Runoff is occured when cumulated rainfall is not exceed saturation rainfall, but exceed, runoff is occured from percolation area, too. Runoff area is given and not changed, runoff ratio is constant. In routing process, runoff from runoff and percolation area is routed seperately with nonlinear cenceptual reservior having same characteristics and it is unreasonable assumption. Modified SFM is proposed with storage function and continuity Equation which has no assumption for routing process and effective rainfall is calculated by SCS Method. For Wi Stream, comparision of Kimura and Modified SFM is conducted and It could be seen that Modified SFM is more improvemental and easily applicable method.

• Journal of Korea Water Resources Association
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• v.40 no.7
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• pp.523-532
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• 2007

It has been operated since 1974, recently, the flood forecasting and warning system is applied in almost all the rivers in Korea, and the Storage Function Method (SFM) is used for flood routing. The SFM which was presented by Toshimitsu Kimura (1961) routes floods in channels and basins with the storage function as the basic equation. A watershed is divided into two zone, runoff and percolation area and runoff from runoff area is occurred when cumulated rainfall is not exceed saturation point, but exceed runoff is occurred from percolation area, too. Runoff area is given and not changed, runoff ratio is constant. In routing Process, runoff from runoff and percolation area is routed seperately with nonlinear conceptual reservoir having the same characteristics and it is unreasonable assumption. A modified SFM is proposed with storage function and continuity equation which has no assumption for routing process and effective rainfall is calculated by SCS Method. For Wi-stream, comparison of Kimura and the modified SFM is conducted, and it could be seen that the modified SFM is more improvable and applicable method easily by reducing the parameters.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.125-130
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• 2009

Storage function method which considers the non-linearity of the relationship between rainfall and runoff has been frequently used to predict runoff in a basin and a flood pattern. However, it is time-consuming to estimate appropriate parameters of every basin and rainfall event, which requires the empirical parameter equation applicable in Korea. In this study, multiple regression analysis is used to develop empirical equations to estimate parameters of Storage Function method using basin characteristics. The basin area, maximum stream length, and stream slope are considered as the basin characteristics as the result of the regression analysis. Collinearity is removed and trial-and-error method is used to choose the most descriptive parameters to the dependent variables in Han River basin which is divided into 30 subbasins. The developed equations are validated using the rainfall events in MunMak gauging station and named as 'Han River equation'. The equation could provide the useful information about Storage Function method parameter to calculate runoff from a basin and predict river stage.

• Journal of Industrial Technology
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• v.18
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• pp.51-59
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• 1998

To flood forecastion, until now, Storage function method, Streamflow Synthesis and Reservoir Regulation, and HEC-1 model have been analysed generally in various definite simulation. Generally, Streamflow Synthesis and Reservoir Regulation and HEC-1 model are more delicacy and more excellent model than Storage function method in physically. But the resource huge for test of models. On the contrary, Storage function method has not only a few model various and data for decision but also has poor theory background in model excessively simpled water circulation about a basin. In this reason, this study is purpose to develop a statistical flood forecasting model that can forecast with accuracy variety of water height to Nak-Dong river vibration spots in flood with accumulated water resource.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.9-14
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• 1995

A cost minimization model for designing AS/RS (Automated Storage/Retrieval Systtems) has been developed under the S/R (Storage/Retrieval) machine throughput rate and total storage capacity requirements. The objective function includes S/R machine cost storage rack cost, and interface conveyor cost. Since the model is a nonlinear integer programming problem which is very hard to solve with large problem size, the model is simplified using previous research results to be solved exactly and a simultion procedure is combined to verify that throughput rate requirements are satisfied.