• Journal of Korean Society on Water Environment
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• v.25 no.1
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• pp.125-135
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• 2009

Reliable long-term flows by SWAT-K model were applied to the relationship between stream flow and pollutant load derived from 8-day measured data of Ministry of Environment (MOE) in order to obtain continuous loadograph and evaluate accuracy in water quality modeling for the Chungju dam watershed. The measured flow were compared with flow duration curve from the model, and it showed that measured values corresponded to the almost full range of stream flow conditions except at Odae A. And there was significant relationship ($R^2=0.60{\sim}0.97$) between measured flow and water quality load at all unit-watersheds. Applying this relationship to simulated flows, continuous loadograph was obtained and compared with modeled pollutant loads. Although there were some differences during some dry and flood seasons, those were not significant and overall trend showed a good agreement. From the results, we would be able to derive a continuous loadograph based on measured data at total maximum daily loads (TMDLs) unit-watersheds on a national scale, in which stream flow and water quality have been measured at 8-day intervals since 2004, and this could be helpful to utilize distributed water quality models with difficulty in calibrating and validating parameters from lack of measured data at present.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.449-453
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• 2008

This research focused on analyzing and comparing between the results of hydraulic physical modeling and the results of numerical modeling of Grass Concrete which is newly developed in-situ block system. The physical model was built as a scale of 1:50 by Froude similitude measuring the water levels and the water velocities for before and after vegetation and the effects were analyzed after reviewing the results. In consequence, the water velocities were observed to decrease meanly 19.1%, and the water depth were determined to increase meanly 27.8% in case of the of design flood, $Q=200m^3/sec$. Moreover, the velocities were produced reduction effects of 27.2%, and the water levels were derived from addition effects of the highest 31.3% in case of the probability maximum flood(PMF), $Q=600m^3/sec$. To verifying the hydraulic physical modeling, the numerical modeling was conducted for a close examination of before and after vegetation. HEC-RAS model was for 1 dimensional numerical analysis and RMA-2 was for 2 dimensional numerical analysis. The results of the numerical simulation, under the condition of roughness coefficient calibration, shows similar results of the physical modeling. These satisfactory results show that the accomplished results of hydraulic modeling and the predicted results of numerical modeling corresponded reasonably each others.

• Journal of Korean Society of Water and Wastewater
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• v.28 no.5
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• pp.561-571
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• 2014

The paper is to estimate willingness-to-pay (WTP) for tap water quality improvement in Busan, using parametric approach in contingent valuation method(CVM). For parametric approach linear logit model and log logit model are employed in double-bounded dichotomous choice format of CVM. For the reliability and the validity of contingent valuation method a survey was conducted for 665 respondents, who were sampled by stratified random sampling method, by personal interview method. The result of mean WTP for the tap water quality improvement in Busan was estimated to be 3,687 won and 3,660 won per month per household, while median WTP being 1,884 won and 1,892 won per month per household, respectively by linear logit model and log logit model. Provided that our sample is broadly representative of the Busan's population, an estimate of the annual aggregated benefit of residential water improvement for all Busan households is approximately 29.7 billion won to 29.8 billion won based on median WTP.

• Journal of Korean Society on Water Environment
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• v.29 no.5
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• pp.625-629
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• 2013

The objective of this study is to develop and evaluate simple and multiple regression models for Total Organic Carbon (TOC) concentration estimation in stream flow. For development (using water quality data in 2012) and evaluation (using water quality data in 2011) of regression models, we used water quality data from downstream of Yeongsan river basin during 2011 and 2012, and correlation analysis between TOC and water quality parameters was conducted. The concentrations of TOC were positively correlated with Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), TN (Total Nitrogen), Water Temperature (WT) and Electric Conductivity (EC). From these results, simple and multiple regression models for TOC estimation were developed as follows : $TOC=0.5809{\times}BOD+3.1557$, $TOC=0.4365{\times}COD+1.3731$. As a result of the application evaluation of the developed regression models, the multiple regression model was found to estimate TOC better than simple regression models.

• Water for future
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• v.27 no.1
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• pp.111-121
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• 1994

The purpose of this paper is to construct a network model for the optimal allocation of limited water resources to the nodal system with given priorities. The solution technique for the model is based on the out-of-kilter algorithm(OKA). For the verification and application of the theoretical methodology and computer programs, the Geum river system is selected. Using release of Daecheong dam and water demand in Geum river basin, optimal allocation of water resources is accomplished for 4 cases(case 1 - case 4) which consider priority numbers in the demand nodes. The results of the application show that the model can reasonably represent the physical system, and water shortage at the demand nodes with high priority numbers is reduced. Its system solution was verified with that by the revised simplex algorithm.

• Journal of Korea Water Resources Association
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• v.47 no.1
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• pp.11-24
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• 2014

In this study, the characteristics of the propagation of dam-break wave through a porous structure in a water tank is numerically analyzed by using the three-dimensional numerical model (ANSYS CFX model). As results of comparison between the existing measured and simulated water depth distributions in and around a porous structure, the agreement is relatively well satisfied. Moreover, for the case of the presence in part of a porous structure in a water tank, the three-dimensional flow structure is numerically analyzed In general, compared with in the area with a porous structure, the abrupt variation of water depth occurs in the area without a porous structure. It is shown that the porous structure can play a role to decrease the abrupt variation of water depth.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.3
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• pp.273-283
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• 2019

The authors has predicted the maneuvering characteristics of a fishing vessel in deep water using Kijima's empirical formula in a previous study. Since the Kijima's empirical formula was developed by a regression analysis of merchant vessels which have dimensions ($C_b$, L/B, etc.) that are different from those of fishing vessels, it was possible to make a prediction approximately even with inaccurate estimation. In this study, the authors estimated the turning-motion characteristics of a model ship of fisheries training ship in shallow water based on the results of its previous study. The turning-motion characteristics of the model ship in shallow water was found out through quantitative analysis according to the water depth to ship draft ratio (H/d). In conclusion, the turning-motion characteristics of the model ship had significant changes immediately after an H/d 1.5, and this result will be helpful for sailing in shallow water.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4102-4111
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• 2023

In order to better perform thermal hydraulic calculation and analysis of supercritical water reactor, based on the experimental data of supercritical water, the model training and predictive analysis of the heat transfer coefficient of supercritical water were carried out by using the support vector machine (SVM) algorithm. The changes in the prediction accuracy of the supercritical water heat transfer coefficient are analyzed by the changes of the regularization penalty parameter C, the slack variable epsilon and the Gaussian kernel function parameter gamma. The predicted value of the SVM model obtained after parameter optimization and the actual experimental test data are analyzed for data verification. The research results show that: the normalization of the data has a great influence on the prediction results. The slack variable has a relatively small influence on the accuracy change range of the predicted heat transfer coefficient. The change of gamma has the greatest impact on the accuracy of the heat transfer coefficient. Compared with the calculation results of traditional empirical formula methods, the trained algorithm model using SVM has smaller average error and standard deviations. Using the SVM trained algorithm model, the heat transfer coefficient of supercritical water can be effectively predicted and analyzed.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.51-57
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• 2024

This study was conducted on how to simulate runoff, which was done using existing physical models, using an LSTM (Long Short-Term Memory) model based on deep learning. Tancheon, the first tributary of the Han River, was selected as the target area for the model application. To apply the model, one water level observatory and four rainfall observatories were selected, and hourly data from 2020 to 2023 were collected to apply the model. River water level of the outlet of the Tancheon basin was simulated by inputting precipitation data from four rainfall observation stations in the basin and average preceding 72-hour precipitation data for each hour. As a result of water level simulation using 2021 to 2023 data for learning and testing with 2020 data, it was confirmed that reliable simulation results were produced through appropriate learning steps, reaching a certain mean absolute error in a short period time. Despite the short data period, it was found that the mean absolute percentage error was 0.5544~0.6226%, showing an accuracy of over 99.4%. As a result of comparing the simulated and observed values of the rapidly changing river water level during a specific heavy rain period, the coefficient of determination was found to be 0.9754 and 0.9884. It was determined that the performance of LSTM, which aims to simulate river water levels, could be improved by including preceding precipitation in the input data and using precipitation data from various rainfall observation stations within the basin.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.10a
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• pp.134-141
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• 2002

A series of forced oscillation test on model mooring chain was carried out to investigate dynamic tension characteristics. The model test was conducted at two different water depth to gather basic data for 'truncated mooring test' and 'hybrid mooring test'. The truncated and hybrid mooring test are highly recommended to overcome the limitation of water depth in model test recently. The resultant tension RAO gives good possibility of approximation of dynamic tension by equivalent weight adjustment for the ratio of water depth in different water depth. Because the hybrid mooring test is the adequate combination of model test and simulation, accurate simulation model on mooring system is essential. The simulation results show good agreement with model test results.