• Journal of Korean Society of Water and Wastewater
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• v.9 no.4
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• pp.73-86
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• 1995

The propriety of the numerical model application was examined on Paldang resevoir and its inflow tributaries located in the center of the Korean peninsula and the long term water quality forecast of the oxygen profile was carried out in this syduy. The input data of the model was the capacity of the reservoir, catchment area, percolation, diffusion rate, vertical mixing rate, dissolution rate from the bottom of the reservoir, outflow of the resevoir, water quality measurement and meteorology data of the drainage basin, and the output result was the annual estimation value of the dissolved oxygen concentration and the biochemical oxygen demand. The modeling method is based on the measured or calculated boundary condition dividing the water area into several blocks from the macorscopic aspect and considering the mass balance in these blocks. As the result of the water quality forecast, it was expected that the water quality in Northern Han River and Paldang reservoir would maintain the recent level, but that the water quality in the Southern Han River and its inflow tributary would worsen below the grade 4 of the life environmental standard from around 2000 owing to the decrease of DO concentration and the increase of BOD concentration.

• Nuclear Engineering and Technology
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• v.41 no.8
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• pp.1045-1052
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• 2009

A calculation model is developed to predict the transient free surface flow on the containment floor following a loss-of-coolant accident (LOCA) of pressurized water reactors (PWR) for the use of debris transport evaluation. The model solves the two-dimensional Shallow Water Equation (SWE) using a finite volume method (FVM) with unstructured triangular meshes. The numerical scheme is based on a fully explicit predictor-corrector method to achieve a fast-running capability and numerical accuracy. The Harten-Lax-van Leer (HLL) scheme is used to reserve a shock-capturing capability in determining the convective flux term at the cell interface where the dry-to-wet changing proceeds. An experiment simulating a sudden break of a water reservoir with L-shape open channel is calculated for validation of the present model. It is shown that the present model agrees well with the experiment data, thus it can be justified for the free surface flow with accuracy. From the calculation of flow field over the simplified containment floor of APR1400, the important phenomena of free surface flow including propagations and interactions of waves generated by local water level distribution and reflection with a solid wall are found and the transient flow rates entering the Holdup Volume Tank (HVT) are obtained within a practical computational resource.

• Water for future
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• v.26 no.2
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• pp.99-105
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• 1993

A practical flood forecasting model(FFM) is suggested. The output of the model is the results which the initial condition of meteorological parameters and soil moisture are projected on the future. The physically based station model for rainfall forecasting(RF) and the storage function model for runoff prediction(RP) are adopted respectively. Input variables for FFM are air temperature, pressure, and dew-point temperature at the ground level and the flow at the rising limb(FRL). The constant parameters for FFM are average of optimum values which the past storm events have. Also loss rate of rainfall can predicted by FRL.

• Journal of Korean Society of Water and Wastewater
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• v.14 no.1
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• pp.108-116
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• 2000

Chlorine is widely used as a disinfectant in drinking-water systems throughout the world. Chlorine residual was used as an indicator for prediction of water quality in water distribution systems. The variation of chlorine residual in drinking water distribution systems of Suwon city was simulated using EPANET. EPANET is a computerized simulation model which predicts the dynamic hydraulic and water quality behavior within a water distribution system operating over an extended time period. Sampling and analysis were performed to calibrated the computer model in 1999 (Aug. Summer). Water quality variables used in simulations are temperature, roughness coefficient, pipe diameter, pipe length, water demand, velocity and so on. Extended water residence time affected water quality due to the extended reaction time in some areas. All area showed the higher concentration of chlorine residual than 0.2mg/l(standard). So it can be concluded that any area in Suwon city is not in biological regrowth problem. Rechlorination turned out to be an useful method for uniform concentration of free chlorine residual in distribution system. The cost of disinfectant could be saved remarkably by cutting down the initial chlorine concentration to the level which guarantees minimum concentration (0.2mg/l) throughout the distribution system.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.1
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• pp.93-100
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• 2011

A coupled tide-surge model, which has been evaluated the utility in the previous study, is applied for simulating the inundation phenomena. The coupled model system adopts the hydrodynamic module of MIKE21 software, and the study area is identical to the previous study. The only difference is additional detailed areas for simulating inundation. An artificial scenario of a virtual typhoon striking Mokpo coastal zone at spring high tide is simulated. Then the calculated water level corresponds to the extreme high water level(556 cm) for 100 year return period. The result also shows the inundation depth is 50~100 cm not only near the Mokpo Inner Port but also near the Mokpo North Port. Finally, the coastal inundation prediction map is drawn on the basis of inundation simulation results.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.891-897
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• 2021

There is a need for a technology that can quickly and accurately analyze soil carbon contents. Existing soil carbon analysis methods are cumbersome in terms of professional manpower requirements, time, and cost. It is against this background that the present study leverages the soil physical properties of color and water content levels to develop a model capable of predicting the carbon content of soil sample. To predict the total carbon content of soil, the RGB values, water content of the soil, and lux levels were analyzed and used as statistical data. However, when R, G, and B with high correlations were all included in a multiple regression analysis as independent variables, a high level of multicollinearity was noted and G was thus excluded from the model. The estimates showed that the estimation coefficients for all independent variables were statistically significant at a significance level of 1%. The elastic values of R and B for the soil carbon content, which are of major interest in this study, were -2.90 and 1.47, respectively, showing that a 1% increase in the R value was correlated with a 2.90% decrease in the carbon content, whereas a 1% increase in the B value tallied with a 1.47% increase in the carbon content. Coefficient of determination (R²), root mean square error (RMSE), and mean absolute percentage error (MAPE) methods were used for regression verification, and calibration samples showed higher accuracy than the validation samples in terms of R² and MAPE.

• Journal of Korea Water Resources Association
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• v.47 no.8
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• pp.729-742
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• 2014

This study predicted long-term sediment distribution for 76 years by using RMA-2 which is two-dimensional numerical model and SED2D which is the sediment transport model to quantitatively analyze sediment distribution in the reservoir based on sediment intrusion and efficiently manage the reservoir. For water level-discharge-sediment data required in boundary conditions of the model, real-time data measured by the Korea Water Resources Corporation were used. The sediment input data was calculated using K-DRUM model. Sedimentation depth was compared with results of model by collecting cross-section core in the reservoir during the dry season. As the result of validation, the sediment depth in the reservoir was similar to actually measured value. For prediction of long-term sediment distribution, terrain data measured in 2012 was used as starting crosssection and simulations for 76 years until 2088 were made. As the results of simulations, sediment distributions of 1.63~1.26 m and 1.45~0.007 m were shown in upstream and downstream of Hapcheon Dam, respectively.

• Journal of Soil and Groundwater Environment
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• v.19 no.3
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• pp.123-133
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• 2014

It is important to predict the groundwater level fluctuation for effective management of groundwater monitoring system and groundwater resources. In the present study, three different time series models for the prediction of groundwater level in response to rainfall were built, those are transfer function noise model (TFNM), artificial neural network (ANN), and adaptive neuro fuzzy interference system (ANFIS). The models were applied to time series data of Boen, Cheolsan, and Hongcheon stations in National Groundwater Monitoring Network. The result shows that the model performance of ANN and ANFIS was higher than that of TFNM for the present case study. As lead time increased, prediction accuracy decreased with underestimation of peak values. The performance of the three models at Boen station was worst especially for TFNM, where the correlation between rainfall and groundwater data was lowest and the groundwater extraction is expected on account of agricultural activities. The sensitivity analysis for the input structure showed that ANFIS was most sensitive to input data combinations. It is expected that the time series model approach and results of the present study are meaningful and useful for the effective management of monitoring stations and groundwater resources.

• Computers and Concrete
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• v.31 no.2
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• pp.111-121
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• 2023

The influence of material composition such as aggregate types, addition of supplementary cementitious materials as well as exposed temperature levels have significant impacts on concrete residual mechanical strength properties when exposed to elevated temperature. This study is based on data obtained from literature for fly ash blended concrete produced with natural and recycled concrete aggregates to efficiently develop prediction models for estimating its residual compressive strength after exposure to high temperatures. To achieve this, an extensive database that contains different mix proportions of fly ash blended concrete was gathered from published articles. The specific design variables considered were percentage replacement level of Recycled Concrete Aggregate (RCA) in the mix, fly ash content (FA), Water to Binder Ratio (W/B), and exposed Temperature level. Thereafter, a simplified mathematical equation for the prediction of concrete's residual compressive strength using Gene Expression Programming (GEP) was developed. The relative importance of each variable on the model outputs was also determined through global sensitivity analysis. The GEP model performance was validated using different statistical fitness formulas including R², MSE, RMSE, RAE, and MAE in which high R² values above 0.9 are obtained in both the training and validation phase. The low measured errors (e.g., mean square error and mean absolute error are in the range of 0.0160 - 0.0327 and 0.0912 - 0.1281 MPa, respectively) in the developed model also indicate high efficiency and accuracy of the model in predicting the residual compressive strength of fly ash blended concrete exposed to elevated temperatures.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1095-1105
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• 2021

The advancement of dam operation is further required due to the upcoming rainy season, typhoons, or torrential rains. Besides, physical models based on specific rules may sometimes have limitations in controlling the release discharge of dam due to inherent uncertainty and complex factors. This study aims to forecast the water level of the nearest station to the dam multi-timestep-ahead and evaluate the availability when it makes a decision for a release discharge of dam based on LSTM (Long Short-Term Memory) of deep learning. The LSTM model was trained and tested on eight data sets with a 1-hour temporal resolution, including primary data used in the dam operation and downstream water level station data about 13 years (2009~2021). The trained model forecasted the water level time series divided by the six lead times: 1, 3, 6, 9, 12, 18-hours, and compared and analyzed with the observed data. As a result, the prediction results of the 1-hour ahead exhibited the best performance for all cases with an average accuracy of MAE of 0.01m, RMSE of 0.015 m, and NSE of 0.99, respectively. In addition, as the lead time increases, the predictive performance of the model tends to decrease slightly. The model may similarly estimate and reliably predicts the temporal pattern of the observed water level. Thus, it is judged that the LSTM model could produce predictive data by extracting the characteristics of complex hydrological non-linear data and can be used to determine the amount of release discharge from the dam when simulating the operation of the dam.