• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.27-38
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• 2006

The storage function model (SFM) has been used for the flood forecasting in Korea. The SFM has a simple calculation process and it is known that the model is more reasonable than linear model because it considers non-linearity of flood runoff. However, the determination of parameters is very difficult. In general, the trial and error method which is an manual calibration by the decision of a model manager. This study calibrated the parameters by the trial and error method and optimization technique. The calibrated parameters were compared with the representative parameters which are used in the Flood Control Centers in Korea. Also, the evaluation indexes on objective functions and calibration methods for the comparative analysis of simulation efficiency. As a result, the Genetic Algorithm showed the smallest variation in objective functions and, in this study, it is known that the objective function of SSR (Sum of Squared of Residual) is the best one for the flood forecasting.

• Transactions on Electrical and Electronic Materials
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• v.18 no.2
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• pp.111-118
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• 2017

The increased diversity of different types of energy sources requires moving towards smart distribution networks. This paper proposes a probabilistic DG (distributed generation) units planning model to determine technology type, capacity and location of DG units while simultaneously allocating ESS (energy storage systems) based on pre-determined capacities. This problem is studied in a wind integrated power system considering loads, prices and wind power generation uncertainties. A suitable method for DG unit planning will reduce costs and improve reliability concerns. Objective function is a cost function that minimizes DG investment and operational cost, purchased energy costs from upstream networks, the defined cost to reliability index, energy losses and the investment and degradation costs of ESS. Electrical load is a time variable and the model simulates a typical radial network successfully. The proposed model was solved using the DICOPT solver under GAMS optimization software.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.39-50
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• 2006

The flood control offices of main rivers have used a storage function model to forecast flood stage in Korea and studies of flood forecasting actively have been done even now. On this account, the storage function model, which is used in flood control office, regression models and artificial neural network model are applied into flood forecasting of study watershed in this paper. The result obtained by each method are analyzed for the comparative study. In case of storage function model, this paper uses the representative parameters of the flood control offices and the optimized parameters. Regression coefficients are obtained by regression analysis and neural network is trained by backpropagation algorithm after selecting four events between 1995 to 2001. As a result of this study, it is shown that the optimized parameters are superior to the representative parameters for flood forecasting. The results obtained by multiple, robust, stepwise regression analysis, one of the regression methods, show very good forecasts. Although the artificial neural network model shows less exact results than the regression model, it can be efficient way to produce a good forecasts.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.3
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• pp.15-25
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• 2005

Ninety tow percent of over 1,800 gate controlled dams in Korea are classified as small dams. The primary purpose of these small dams is to supply irrigation water. Therefore, while large dams can store as much as 80 percent of precipitation and thus are efficient to control flood, small dams are often lack of flood control function resulting in increased susceptibility drought and flood events. The purpose of this study is to develope a storage management model for irrigation dams occupying the largest portion of small dams. The proposed Storage Management Model (STMM) can be applied to the Seongju dam for efficient management. Besides, the operation standard is capable of analyzing additional available water, considering water demand and supply conditions of watershed realistically. And the model can improve the flood control capacity and water utilization efficiency by the flexible operation of storage space. Consequently, if the small dams are managed by the proposed Storage management model, it is possible to maximize water resources securance and minimize drought and flood damages.

• Water Engineering Research
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• v.1 no.3
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• pp.171-185
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• 2000

A mathematical model to adequately predict complex mixing characteristics of sorptive polluants in natural streams with pools-and-riffes has been developed. In this model, sorption of pollutants onto the bed sediment as well as mass storage and exchange in the storage zones were incorporated into one-dimensional mass balance equatins. The geometric and hydraulic characteristics of the pool-riffle sequences were properly conceptualized. Simulations with parameters of pool-and-riffle streams better fit the measured data in overall shape and peak concentration than simulations with parameters for uniform channels. The analyses on the characteristics of the storage zone model parameters reveal that a linear relationship between the logrithm of the storage zone volume ratio and a function of the friction factor exists. A linear relatiohship might also be tenatively assumed between the logarithm of the dimensionless mass exchange coefficient and the logarithm of the aspect ratio of the storage zone if some of the high values of the dimensionless mass exchange coefficient collected on the successive bed forms are excluded.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.2
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• pp.60-66
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• 2014

A control oriented model of the Lean $NO_x$ trap (LNT) was developed to determine the timing of $NO_x$ regeneration. The LNT model consists of $NO_x$ storage and reduction model. Once $NO_x$ is stored ($NO_x$ storage model), at the right timing $NO_x$ should be released and then reduced ($NO_x$ reduction model) with reductants on the catalyst active sites, called regeneration. The $NO_x$ storage model simulates the degree of stored $NO_x$ in the LNT. It is structured by an instantaneous $NO_x$ storage efficiency and the $NO_x$ storage capacity model. The $NO_x$ storge capacity model was modeled to have a Gaussian distribution with a function of exhaust gas temperature. $NO_x$ release and reduction reactions for the $NO_x$ reduction model were modeled as Arrhenius equations. The parameter identification was optimally performed by the data of the bench flow reactor test results at space velocity 50,000/hr, 80,000/hr, and temperature of $250-500^{\circ}C$. The LNT model state, storage fraction indicates the degree of stored $NO_x$ in the LNT and thus, the timing of the regeneration can be determined based on it. For practical purpose, this model will be verified more completely by engine test data which simulate the NEDC transient mode.

• Journal of The Korea Institute of Healthcare Architecture
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• v.14 no.2
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• pp.53-64
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• 2008

This study is the architectural planning of 5 distribution supporting facilities for traditional herbal medicine cultivated in the rural areas. The main function of the facility consists of storage, pre-treatment/processing, loading/unloading and the assistant function consists of inspection, office, exhibition/sale, technical equipment etc. The planning shows the modular plan and the section plan of the storage space reflecting the shape and size of storage container, the action radius of carrier and the possibilities of space lease. The total floor area of the storage is 3,192$m^2$ consisting of 27 space. The total floor area of the pre-treatment/processing is 1,488$m^2$ consisting of 7 space. The total floor area of the loading/unloading is 329$m^2$ consisting of 4 space. The total floor area of each facility storage is 8,284$m^2$ including of public space 2,170$m^2$. Also this planning shows the preliminary design, "fundamental model design" for 5 rural government BTL project. Therefore, this result of planning will be the guidelines of the RFP(Request For Proposal) for the private sector company interested in this BTL project.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.531-534
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• 2003

A model using a nonlinear programming technique was applied for allocating the optimal water depending on storage level changes of the Sumjin dam. The objective function of optimization model was set up to maintain the storage at target level, to satisfy the water demand, and to maximize the hydropower production. In this way, the water allocation as to target level and instream flow was optimized and compared with historical operational data.

• Journal of Korea Water Resources Association
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• v.33 no.3
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• pp.341-350
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• 2000

The objectives of this study are to develop a state-space form of stochastic dynamic storage function routing model and to test the model performance for real-time flow forecast. The selected study area is the main Han River starting from Paldang Dam site to Indogyo station and the 13 flood events occurred from 1987 to 1998 are selected for computing model parameters and testing the model performance. It was shown that the optimal model parameters are quite different depending on Hood events, but the values used on field work also give reasonable results in this study area. It is also obvious that the model performance from the stochastic-dynamic model developed in this study gives more accurate and reliable results than that from the existing deterministic model. Analysis for allowable forecast lead time leads that under the current time step the reasonable predicted downstream flows in 5 hours time advance are obtained from the stochastic dynamic model on relatively less lateral inflow event in the study area.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1219-1223
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• 2005

This study was accomplished to confirm the possibility of supplying stream minimum flow from detention storage which was determined to reduce peak flows of flood within developing planned district. The results analyzed was summarized as follows; Firstly, Sin-gil district situated in Ansan city was selected, of which watershed area has $0.56km^2$. And detention storage was determined to $5,370m^3$ from analyzing flood volume by the SCS unit hydrograph method. Secondly, using Visual Basic ver 6.0, a detention storage water balance model was developed, in which simulation was based on conditioning storage inflow and outflow according to streamflow volume or rate state. And streamflow was simulated using the DAWAST model. Thirdly, detention operation scenarios were consisted of the combinations with inflow referencing streamflow of 5mm/day, 10mm/day and outflow referencing streamflow of 1mm/day, 2mm/day. The developed detention storage water balance model was operated to simulate daily water storages of detention sized on flood by scenarios. Stream minimum flows were able to be supplied during 209 days to 237 days per a year, total volume of stream minimum flows supplied for this period was analyzed to reach 27 to $55\% of yearly streamflow volume. If inflow criteria of streamflows to detention was considered to be established on a theoretical condition, it is expected to supply stream minimum flows of 20 to $30\% of yearly streamflow from stream to detention. Also to maximize function of supplying urban stream minimum flow from detention storages, sewage waters within developing planned district have to be treated and entered to detention inflow together with streamflows to enrich function of detention planned to reduce flood volumes.