Seoul National University · 環境科学
Professor Il Won Seo's research lab specializes in environmental fluid mechanics and water quality modeling, with a focus on longitudinal and transverse dispersion in natural streams, pollutant transport, and mixing processes in rivers. The lab develops advanced theoretical and numerical models—such as the storage zone model, beta distribution-based velocity profiles, and finite element simulations—to improve the prediction of dispersion coefficients and water quality parameters. Innovative computational techniques, including artificial neural networks and ensemble modeling, are applied to enhance the accuracy of water quality forecasting in complex river systems.
Figures are computed from collected data and may differ slightly.
In this study, previous empirical equations used to compute the dispersion coefficient are analyzed in order to evaluate their behavior in predicting dispersion characteristics in natural streams. A comparative analysis of previous theoretical and empirical equations is reported. A new simplified method for predicting dispersion coefficients using hydraulic and geometric data that are easily obtained in natural streams is also developed. The one-step Huber method, which is one of the nonlinear m
In this study, a theoretical method for predicting the longitudinal dispersion coefficient is developed based on the transverse velocity distribution in natural streams. Equations of the transverse velocity profile for irregular cross sections of the natural streams are analyzed. Among the velocity profile equations tested in this study, the beta distribution equation, which is a probability density function, is considered to be the most appropriate model for explaining the complex behavior of t
SUMMARY The no‐slip condition is an assumption that cannot be derived from first principles and a growing number of literatures replace the no‐slip condition with partial‐slip condition, or Navier‐slip condition. In this study, the influence of partial‐slip boundary conditions on the laminar flow properties past a circular cylinder was examined. Shallow‐water equations are solved by using the finite element method accommodating SU/PG scheme. Four Reynolds numbers (20, 40, 80, and 100) and six sl
Theoretical methods have been developed to calculate values of parameters of the storage zone model for river mixing. Analytical solutions of the Laplace-transformed equations of the storage zone model are related to the observed concentration distribution in order to determine model parameters in both the moment matching method and the maximum likelihood method, which were developed in this study. The results obtained by comparison with experimental data show that the parameters calculated by t
In this study, the water quality parameters (Temperature, DO, pH, Electric Conductivity, TN, TP, Turbidity and Chlorophyll-a) at the downstream of Cheongpyeong dam are predicted using artificial neural network. The artificial neural network(ANN) is a powerful computational technique for modeling complex relationship between input and output data. Typically, Time series generally consists of a linear combination of trend, periodicity and stochastic component. In this study, to reduce the influenc
To investigate the effects of the stream geometry on the transverse mixing of the pollutant, tracer tests were conducted at seven different sites in tributaries of the Han River in Korea. The routing procedure combined with the stream-tube concept was developed to analyze the dispersion data collected in a natural stream with irregular geometry under slug tests. The routing procedure was used to calculate the transverse dispersion coefficient from the observed concentration data, and the result
To investigate the two-dimensional dispersion characteristics of the dissolved contaminant in natural rivers, tracer experiments were performed based on the instantaneous injection of Rhodamine WT solution into small- to medium-sized rivers in Korea. The relations between the dispersion coefficients and hydraulic and geometric variables of the river were analyzed in depth. The experimental results show that transverse dispersion coefficient tends to increase as the friction term, U/U*, and the c
Two types of dispersion coefficient tensor for meandering channels were examined. The first type was estimated using measured vertical velocity profile in an S-curved channel, and the second type was based on the depth-averaged velocity field. A Petrov-Galerkin type finite element scheme was used in the numerical modeling, and the simulation results were compared with the experimental results from tracer tests in an S-curved channel. Comparison of the results show that the dispersion coefficient
The feasibility of using the velocity-based method for calculating the transverse mixing coefficient of the two-dimensional contaminant transport model was studied to substitute the concentration-based method in which the mixing coefficient is calculated from the concentration curves obtained via the costly tracer experiment. To calculate the transverse mixing coefficients, the hydraulic data and concentration data of the electric conductivity (EC) were collected at the confluence of tributary r
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