• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.4
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• pp.147-157
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• 1987

Five finite difference schemes (explicit, Bresler, implicit, upstream, and Chaudhari scheme) for the convective dispersion model are analyzed numerically to investigate their characteristics and applicabilities. Camparative study results show that the conditionally stable Chaudhari scheme has the smallest numerical dispersion and that the unconditionally stable Bresler scheme has the overshooting in regions of oscillation. Explicit scheme is the most accurate for a dispersion-dominated flow whereas Chaudhari scheme is for a convection-dominated flow. The computation time (CPU) is the shortest for the explicit or Chaudhari scheme with the same order of magnitude and is always the longest for the Bresler scheme.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.04a
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• pp.167-168
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• 2000

복잡한 구조를 갖고 시간에 따라서 변하는 바람장내에서 공장굴뚝과 같은 점오염원에서 배출되는 오염물질의 확산을 계산하기 위해서 라그란지안 입자확산모텔(Lagrangian Particle Dispersion Model, LPDM)을 사용하는 것이 최근의 연구 동향이다. 구윤서(1999a, 1999b)는 중립 및 안정한 대기조건에서 바람장 계산시 비평형 2.5 난류모델을 이용한 LPDM을 개발하여 복잡한 대기흐름내 확산현상을 보다 정확히 모사할 수 있는 LPDM을 제시하였다. (중략)

• Journal of Environmental Impact Assessment
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• v.10 no.2
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• pp.123-133
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• 2001

Gaussian dispersion model is the most widely used tool for the ground level air pollution simulation. Though in spite of the convenience there are important problems on the Pasquill- Gifford' stability classification scheme which was used to define the turbulent state of the atmosphere or to describe the dispersion capabilities of the atmosphere which was each covers a broad range of stability conditions, and that they were very site specific, and the vertical dispersion calculation formula on the case of the unstable atmospheric condition. This paper was carried out to revise the Gaussian dispension model for the purposed of increase the modeling performance and propose the revised model, which was composed of the turbulent characteristics in the unstable atmospheric conditions. The proposed models in this study were composed of the profile method, Monin-Obukhove length, the probability density function model and the lateral dispersion function which was composed of the turbulent parameters, $u_*$(friction velocity), $w_*$(convective velocity scale), $T_L$(lagrangian time scale) for the model specific. There were very good performance results compare with the tracer experiment result on the case of the short distance (<1415m) from the source, but increase the simulation error(%) to stand off the source in the all models. In conclusion, the revised Gaussian dispersion model using the turbulent characteristics may be a good contribution for the development of the air pollution simulation model.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.8 s.251
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• pp.796-805
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• 2006

In this study, the problem of using the mixing index as a measure of the mixing performance for a certain flow field has been discussed. The flow model subjected to this study is the two-dimensional unsteady lid-driven cavity flow. The transport equation for the concentration within the cavity was solved by using the finite volume method where the convective terms are discretized with the central difference scheme. It was shown that both the concentration dispersion and the mixing index depend highly on the initial distribution of the concentration, and therefore the mixing index obtained from the concentration dispersion equation loses its universal applicability.

• Journal of the Korean Society of Safety
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• v.10 no.2
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• pp.56-63
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• 1995

A simulation of contaminant dispersion in a water reservoir has been done using 2-D finite difference method(FDM). The steady state velocity field of the reservoir was computed using stream function-vorticity formulation of Wavier-Stokes equation and continuity equation. Based on the computed steady state velocity field, the transient convective diffusion equation of the contaminant dispersion was computed. For the 1m$\times$1m reservoir model with inlet and outlet attached, it was shown that the center of circulation located toward right. For the numerical values of v =0.01($\textrm{cm}^2$/s) and D=0.6($\textrm{cm}^2$/s) and the flow of 50($\textrm{cm}^3$/s ), it was determined that the outflow had to be shut down in 18 seconds to prevent from severe pollution. Also the required time was computed to be 6 seconds for the inflow of 100 ($\textrm{cm}^3$/s). The result of this study is considered, hopefully, to be useful for the design of the water reservoir systems that are the subjects to various contamination.

• Journal of Environmental Science International
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• v.12 no.3
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• pp.265-274
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• 2003

The Pasquill-Gifford stability category is a very important scheme of the Gaussian type dispersion model defined the complex turbulence state of the atmosphere by A grade(very unstable) to F grade(very stable). But there has been made a point out that this stability category might decrease the predictability of the model because it was each covers a broad range of stability conditions, and that they were very site specific. The APSM (Air Pollution Simulation Model) was composed of the turbulent parameters, i.e. friction velocity(${\mu}$$\_$*/), convective velocity scale($\omega$$\_$*/) and Monin-Obukhov length scale(Ｌ) for the purpose of the performance increasing on the case of the unstable atmospheric conditions. And the PDF (Probability Density Function)model was used to express the vertical dispersion characteristics and the profile method was used to calculate the turbulent characteristics. And the performance assessment was validated between APSM and EPA regulatory models(TEM, ISCST), tracer experiment results. There were very good performance results simulated by APSM than that of TEM, ISCST in the short distance (<1415 m) from the source, but increase the simulation error(%) to stand off the source in others. And there were differences in comparison with the lateral dispersion coefficient($\sigma$$\_$y/) which was represent the horizontal dispersion characteristics of a air pollutant in the atmosphere. So the different calculation method of $\sigma$$\_$y/ which was extrapolated from a different tracer experiment data might decrease the simulation performance capability. In conclusion, the air pollution simulation model showed a good capability of predict the air pollution which was composed of the turbulent parameters compared with the results of TEM and ISCST for the unstable atmospheric conditions.

• Journal of Nuclear Fuel Cycle and Waste Technology
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• v.1 no.1
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• pp.49-55
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• 2013

To characterize quantitatively the transport of $^{99}Tc$ and the global fallout ($^{137}Cs$, $^{90}Sr$, and $^{239+240}Pu$) for soils in Korea, the transport parameters of a convective-dispersion model, apparent migration velocity, and apparent dispersion coefficient were estimated from the vertical depth profiles of the radionuclides in soils. The vertical profiles of $^{99}Tc$ were measured from a pot experiment for paddy soil that had been sampled from a rice-field around the Gyeongju radioactive waste repository in Korea, and the vertical depth distributions of the global fallout $^{137}Cs$, $^{90}Sr$, and $^{239+240}Pu$ were measured from the soil samples that were taken from local areas in Korea. The front edge of the $^{99}Tc$ profiles reached a depth of about 12 cm in 138 days, indicating a faster movement than the fallout radionuclides. A weak adsorption of $^{99}Tc$ on the soil particles by the formation of Tc(VII) and a high water infiltration velocity seemed to have controlled the migration of $^{99}Tc$. The apparent migration velocity and dispersion coefficient of $^{99}Tc$ for the disturbed paddy soil were 2.88 cm/y and 6.3 $cm^2/y$, respectively. The majority of the global fallout $^{137}Cs$, $^{90}Sr$, and $^{239+240}Pu$ were found in the top 20 cm of the soils even after a transport of about 30 years. The transport parameters for the global fallout radionuclides were 0.01-0.1cm/y ($^{137}Cs$), 0.09-0.13cm/y ($^{90}Sr$), and 0.09-0.18cm/y ($^{239+240}Pu$) for the apparent migration velocity: 0.21-1.09 $cm^2/y$ ($^{137}Cs$), 0.12-0.7$cm^2/y$ ($^{90}Sr$), and 0.09-0.36$cm^2/y$ ($^{239+240}Pu$) for the apparent dispersion coefficient.

• Nuclear Engineering and Technology
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• v.25 no.1
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• pp.154-165
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• 1993

A stochastic method using continuous time Markov process is presented to model the one-dimensional convective nuclide transport in geologic media, which have usually heterogeneous feature in physical/geochemical parameters such as velocity, dispersion coefficient, and retardation factor resulting poor description by conventional deterministic advection-dispersion model. The primary desired quantities from a stochastic model are the mean values and variance of the state variables as a function of time. The time-dependent probability distributions of nuclides are presented for each discretized compartment given the volumetric groundwater flux and the intensity of transition. Since this model is discrete in medium space, physical/geochemical parameters which affect nuclide transport can be easily incorporated for the heterogeneous media as well as remarkably layered media having spatially varied parameters. Even though the Markov process model developed in this study was shown to be sensitive to the number of discretized compartments showing numerical dispersion as the number of compartments are increased, this could be easily calibrated by comparing with the analytical deterministic model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.3
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• pp.129-138
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• 1993

In this study, the applicability of finite analytic method (FAM) is studied by selecting linearized-Burgers equation and Burgers equation which have convective and diffusive behaviors as the model equation of Navier-Stokes equations and by comparing numerical solution of finite difference method (FDM) and finite analytic method. The results are as follows. It is shown that the convergence of FAM for steady-state analytic solution of linearized-Burgers equation and Burgers equation is better than that of FDM under the same criteria. Also the accuracy of FAM for transient solution of Burgers equation is excellent. Especially, it is shown that oscillation phenomenon due to dispersion errors which occur according to the choice of grid size in FDM does not occur in FAM at all. So, it can be thought that FAM is numerically very stable scheme, which is free from dispersion errors.

• Journal of Applied Biological Chemistry
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• v.43 no.1
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• pp.25-30
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• 2000

The main form of nitrogen fertilizer applied to lowland rice is urea, but little is known about its transport in waterlogged soil. This study was conducted to investigate the transport of urea in waterlogged soil column using WAVE (simulation of the substances Water and Agrochemicals in the soil, crop and Vadose Environment) model which includes the parameters for urea adsorption and hydrolysis, The adsorption distribution coefficient and hydrolysis rate of urea were measured by batch experiments. A transport experiment was carried out with the soil column which was pre-incubated for 45 days under flooded condition. The urea hydrolysis rate (k) was $0.073h^{-1}$. Only 5% of the applied urea remained in soil column at 4 days after urea application. The distribution coefficient ($K_d$) of urea calculated from adsorption isotherm was $0.21Lkg^{-1}$, so it was assumed that urea that urea was a weak-adsorbing material. The maximum concentration of urea was appeared at the convective water front because transport of mobile and weak-adsorbing chemicals, such as urea, is dependent on water convective flow. The urea moved down to 11 cm depth only for 2 days after application, so there is a possibility that unhydrolyzed urea could move out of the root zone and not be available for crops. A simulated urea concentration distribution in waterlogged soil column using WAVE model was slightly different from the measured concentration distribution. This difference resulted from the same hydrolysis rate applied to all soil depths and overestimated hydrodynamic dispersion coefficient. In spite of these limitations, the transport of urea in waterlogged soil column could be predict with WAVE model using urea hydrolysis rate (k) and distribution coefficient ($K_d$) which could be measured easily from a batch experiment.