• Journal of Korea Water Resources Association
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• v.48 no.4
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• pp.299-308
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• 2015

The aim of this study is that a theoretical formula for estimating the one-dimensional longitudinal dispersion coefficient is derived based on a transverse distribution equation for the depth averaged stream-wise velocity in open channel. In "Part I. Theoretical equation for stream-wise velocity" which is the former volume of this article, the velocity distribution equation is derived analytically based on the Shiono-Knight Method (SKM). And then incorporating the velocity distribution equation into a triple integral formula which was proposed by Fischer (1968), the one-dimensional longitudinal dispersion coefficient can be derived theoretically in "Part II. Longitudinal dispersion coefficient" which is the latter volume of this article. The proposed equations for the velocity distribution and the longitudinal dispersion coefficient are verified by using observed data set. As a result, the non-dimensional longitudinal dispersion coefficient is inversely proportional to square of the Manning's roughness coefficient and the non-dimensional transverse dispersion coefficient, and is directly proportional to square of the aspect ratio (channel width to depth).

• Journal of Korea Water Resources Association
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• v.36 no.4
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• pp.575-586
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• 2003

In case of continuous input of a pollutant, dispersion characteristics do not change much with changing dispersion coefficient, but that of an instantaneous input is very sensitive to the changes of dispersion coefficient. The characteristics of behavior of instantaneous input of a pollutant at the downstream of Han river were analyzed in this paper Field measurement of hydraulic and water quality factors at the downstream of Han river were conducted at low flow condition. The hydraulic factors were used to estimate the longitudinal dispersion coefficient, and the reasonable empirical equations for longitudinal dispersion coefficient at the downstream of Han river were suggested. The measured concentrations of BOD were closely matched with the calculated ones from RMA-4 model. In case of instantaneous input, range of dispersion, transport pathway and the traveltimes of the first and maximum concentration with variation of the longitudinal dispersion coefficients and water levels of downstream boundary were evaluated in this paper.

• Water for future
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• v.28 no.4
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• pp.195-204
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• 1995

New dispersion coefficient equation which can be used to estimate dispersion coefficient by using only hydraulic data easily obtained in natural streams has been developed. Dimensional analysis was performed to select physically meaningful parameters, One-Step Huber method, which is one of the nonlinear multi-regression method, was applied to derive a regression equation of dispersion coefficient. 59 measured hydraulic data which were collected in 26 streams in the United States and were analyzed in the Part I of this study, were used in developing new dispersion coefficient equation. Among 59 measured data sets, 35 data sets were used in deriving regression equation, and 24 data sets are used for verification. The new dispersion coefficient equation, which has been developed in this study was proven to be superior in explaining dispersion characteristics of natural streams more precisely compared to existing dispersion coefficient equations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.335-344
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• 2006

In this study, sequential mixing model (SMM) was proposed based on the Taylor's theory which can be summarized as the fact that longitudinal advection and transverse diffusion occur independently and then the balance between the longitudinal shear and transverse mixing maintains. The numerical simulation of the model were performed for cases of different mixing time and transverse velocity distribution, and the results were compared with the solutions of 1-D longitudinal dispersion model (1-D LDM) and 2-D advection-dispersion model (2-D ADM). As a result it was confirmed that SMM embodies the Taylor's theory well. By the comparison between SMM and 2-D ADM, the relationship between the mixing time and the transverse diffusion coefficient was evaluated, and thus SMM can integrate 2-D ADM model as well as 1-D LDM model and be an explanatory model which can represents the shear flow dispersion in a visible way. In this study, the predicting equation of the longitudinal dispersion coefficient was developed by fitting the simulation results of SMM to the solution of 1-D LDM. The verification of the proposed equation was performed by the application to the 38 sets of field data. The proposed equation can predict the longitudinal dispersion coefficient within reliable accuracy, especially for the river with small width-to-depth ratio.

• Journal of Korea Water Resources Association
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• v.33 no.4
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• pp.407-417
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• 2000

To estimate the longitudinal dispersion coefficient at the downstream of Jungrang-River, the undistorted 1/20 scale hydraulic model was used in this study. Experiments were conducted for dry season discharge, and Rhodamine B was used as a tracer. The relationship curve between concentration and conductivity of Rhodamine B was otained by laboratory test, and the conductivity which was measured in hydraulic model was converted to concentration using this curve. The longitudinal dispersion coefficient was calculated using the relationship between the peak concentration and the time to peak concentration. The results of this study were compared with the calculated values by the empirical equations for the longitudinal dispersion coefficient and with the field data. The results of comparison show that Parker's equation underestimates, and Liu'g equation and Iwasa and Aya's one overestimate, and McQuivey and Keefer's equations, Fischer's one, Magazine's one, and Seo and Cheong's one predict relatively well. The measured data sets were relatively close to the observed ones in natural river. The longitudinal dispersion coefficient at the downstream of Jungrang-River was estimated $10\textrm{m}^2/s$.

• Journal of Korea Water Resources Association
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• v.48 no.4
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• pp.291-298
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• 2015

The aim of this study is that a theoretical formula for estimating the one-dimensional longitudinal dispersion coefficient is derived based on a transverse distribution equation for the depth averaged stream-wise velocity in open channel. In "Part I. Theoretical equation for stream-wise velocity" which is the former volume of this article, the velocity distribution equation is derived analytically based on the Shiono-Knight Model (SKM). And then incorporating the velocity distribution equation into a triple integral formula which was proposed by Fischer (1968), the one-dimensional longitudinal dispersion coefficient can be derived theoretically in "Part II. Longitudinal dispersion coefficient" which is the latter volume of this article. SKM has presented an analytical solution to the Navier-Stokes equation to describe the transverse variations, and originally been applied to straight and nearly straight compound channel. In order to use SKM in modeling non-prismatic and meandering channels, the shape of cross-section is regarded as a triangle in this study. The analytical solution for the velocity distribution is verified using Manning's equation and applied to velocity data measured at natural streams. Although the velocity equation developed in this study do not agree well with measured data case by case, the equation has a merit that the velocity distribution can be calculated only using geometric data including Manning's roughness coefficient without any measured velocity data.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.863-873
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• 2021

The mechanical dispersion which dominates solute transport in porous media is caused by the difference in flow velocity within pores. Longitudinal dispersion coefficient and longitudinal dispersivity that are hydro-dispersive parameters of advection-dispersion equation can only be obtained by experiment. Hydraulic mean radius that represents the amount and intensity of flowing water within pores can be obtained by the formula using the factors for physical properties. A slug injection test was conducted and a power type empirical formula for obtaining a longitudinal dispersivity using a hydraulic mean radius in rockfill porous media was derived. It is possible to obtain the longitudinal dispersivity depending on transport distance because it contains a formula for a scale constant, and expected to be applicable to waterways filled with homogeneous gravel and small flow rate.

• Journal of applied mathematics & informatics
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• v.35 no.3_4
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• pp.241-260
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• 2017

An analysis is made to study the solute transport in a Casson fluid flow through an annulus in presence of oscillatory flow field and determine how this flow influence the solute dispersion along the annular region. Axial dispersion coefficient and the mean concentration expressions are calculated using the generalized dispersion model. Dispersion coefficient in oscillatory flow is found to be a function of frequency parameter, Schmidt number, and the pressure fluctuation component besides its dependency on yield stress of the fluid, annular gap and time in the case of steady flow. Due to the oscillatory nature of the flow, the dispersion coefficient changes cyclically and the amplitude and magnitude of the dispersion increases initially with time and reaches a non - transient state after a certain critical time. This critical value varies with frequency parameter and independent of the other parameters. It is found that the presence of inner cylinder and increase in the size of the inner cylinder inhibits the dispersion process. This model may be used in understanding the dispersion phenomenon in cardiovascular flows and in particular in catheterized arteries.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.607-616
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• 1999

A fractional step finite difference model for the longitudinal dispersion of nonconservative contaminants is developed. It is based on splitting the longitudinal dispersion equation into a set of three equations each to be solved over a one-third time step. The fourth-order Holly-Preissmann scheme, an analytic solution, and the Crank-Nicholson scheme are used to solve the equations for the pure advection, the first-order decay, and the diffusion, respectively. To test the model, it is applied to simulate the longitudinal dispersion of continuous source released into a nonuniform flow field as well as the dispersion of an instantaneous source in a uniform flow field. The results are compared with the exact solution and those computed by an existing model. Compared to the existing model which uses Euler method for the first-order decay equation, the present model yield more accurate results as the decay coefficient increases.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.495-506
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• 2013

This study developed the Time-split Mixing Model (TMM) which can represent the pollutant mixing process on a three-dimensional open channel through constructing the conceptual model based on Taylor's assumption (1954) that the shear flow dispersion is the result of combination of shear advection and diffusion by turbulence. The developed model splits the 2-D mixing process into longitudinal mixing and transverse mixing, and it represents the 2-D advection-dispersion by the repetitive calculation of concentration separation by the vertical non-uniformity of flow velocity and then vertical mixing by turbulent diffusion sequentially. The simulation results indicated that the proposed model explains the effect of concentration overlapping by boundary walls, and the simulated concentration was in good agreement with the analytical solution of the 2-D advection-dispersion equation in Taylor period (Chatwin, 1970). The proposed model could explain the correlation between hydraulic factors and the dispersion coefficient to provide the physical insight about the dispersion behavior. The longitudinal dispersion coefficient calculated by the TMM varied with the mixing time unlike the constant value suggested by Elder (1959), whereas the transverse dispersion coefficient was similar with the coefficient evaluated by experiments of Sayre and Chang (1968), Fischer et al. (1979).