• Nuclear Engineering and Technology
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• v.17 no.3
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• pp.216-223
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• 1985

The Gaussian plume model is widely used to calculate the concentrations of gaseous radioactive effluents in the atmosphere. This model assumes that the terrain is flat, so that the dispersion coefficients which are the most important parameters in this model must be compensated in complex terrain such as in Korea. In this study the compensation of vertical dispersion coefficient in two dimensional x-z plane has been accomplished by comparing the Gaussian plume model with numerical model. The results show that the concentractions of radioactive effluents over complex terrain are more dilluted than those expected over flat terrain.

• Journal of Radiation Protection and Research
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• v.15 no.2
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• pp.51-56
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• 1990

The dispersing model of radioactive plume in the atmosphere was assumed to form finite ellipseshaped volumes rather than a single plume and gamma absorbed doses from the plume were computed using the proposed model. The results obtained were compared with those computed by the Gaussian plume and the circular approximation models. The results computed by the proposed ellipse-shaped approximation model were close to those by the Gaussian plume model. and more accurate than those by the circular approximation model. The computing time for the proposed approximation model was one fortieth of that for the Gaussian plume model.

• Journal of the Korean Institute of Gas
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• v.8 no.1 s.22
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• pp.13-17
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• 2004

To evaluate suitability of the Gaussian plume model for the small scale release of a dense toxic gas, experimental concentrations of the small scale release of chlorine were compared with theoretical concentrations calculated by the Gaussian plume model using various dispersion coefficients. As a result, Ive found that the dispersion of chlorine gas was fairly varied with dispersion coefficient and atmospheric stability and that chlorine concentrations were well estimated by the Gaussian plume model using Briggs' dispersion coefficient and the effective release hight.

• Journal of computational fluids engineering
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• v.4 no.3
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• pp.12-20
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• 1999

The computations of the flowfield and pollutant dispersion over a flat plate and the Russian hills of various slopes are described. The Gaussian plume and the puff model have been used to calculate concentration of pollutant. The Reynolds-averaged unsteady incompressible Navier-Stokes equation with low Reynolds κ-ε model has been used to calculate the flowfield. The flow data of a flat plate and the Russian hills from Navier-Stokes equation solutions has been used as the input data for the puff model. The computational results of flowfield agree well with experimental results of both a flat plate and Russian hills. The concentration prediction by the Gaussian plume model and the Gaussian puff model also agrees flirty well with experiments.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2004.06a
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• pp.368-376
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• 2004

The estimation of the diffusion coefficients of the Gaussian plume model and the release rate by assimilation of tracer-gas measurements on Younggwang site was tested. Diffusion coefficients were modified by linear programming of both the measurements and the simulated using the Gaussian plume model. The application of the modified diffusion coefficients improved the prediction ability of the Gaussian plume model on both 3 km and 8 km arc lines. And, the release rate of tracer gas was estimated using least squares method. The optimal source rate was estimated by minimizing the errors between the measured concentrations and the computed ones by the Gaussian plume model. The obtained release rate showed a good agreement with the real release rate of the Younggwang experiment in 24%.

• Journal of Environmental Science International
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• v.15 no.4
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• pp.319-324
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• 2006

Release rate is one of the important items for the environmental impact assessment caused by radioactive materials in case of an accidental release from the nuclear facilities. In this study, the uncertainty of the estimated release rate is evaluated using Monte Carlo method. Gaussian plume model and linear programming are used for estimating the release rate of a source material. Tracer experiment is performed at the Yeoung-Kwang nuclear site to understand the dispersion characteristics. The optimized release rate was 1.56 times rather than the released source as a result of the linear programming to minimize the sum of square errors between the observed concentrations of the experiment and the calculated ones using Gaussian plume model. In the mean time, 95% confidence interval of the estimated release rate was from 1.41 to 2.53 times compared with the released rate as a result of the Monte Carlo simulation considering input variations of the Gaussian plume model. We confirm that this kind of the uncertainty evaluation for the source rate can support decision making appropriately in case of the radiological emergencies.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2009.10a
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• pp.171-172
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• 2009

• Journal of Radiation Protection and Research
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• v.23 no.1
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• pp.1-6
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• 1998

A diffusion model of radioactive liquid effluents is developed and applied for YGN NPP's site, based on the Gaussian plume type model. Due to the complexity of oceanic diffusion characteristics of YGN site, a simple and reliable statistical model based on Reg. Guide 1.113 is developed. Also, a computer code package to calculate dilution factors as a function of plant operation conditions and pathway of radioactive materials. A liquid effluents diffusion model is developed by dividing the diffusion range into two categories, i. e, a near field mixing region and a far field mixing region. In the near field, the initial mixing is affected by a buoyance force, a high initial turbulence and momentum which is characterized by a plant operation condition and environmental conditions. The far field mixing is similar to gaseous effluents diffusion. So, beyond the near field region, wellknown Gaussian plume model was adopted. A different area averages of Gaussian plume equation was taken for each radioactive exposure pathway. As a result, we can get different dilution factors for different pathways. Results shows that present dilution factors used for YGN ODCM is too much overestimated compared with dilution factors calculated with the developed model.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.1-20
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• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.4
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• pp.449-456
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• 2007

Dispersion coefficient preprocessing schemes have been examined to improve plume dispersion model performance in complex coastal areas. The performances of various schemes for constructing the sigma correction order were evaluated through estimations of statistical measures, such as bias, gross error, R, FB, NMSE, within FAC2, MG, VG, IOA, UAPC and MRE. This was undertaken for the results of dispersion modeling, which applied each scheme. Environmental factors such as sampling time, surface roughness, plume rising, plume height and terrain rolling were considered in this study. Gaussian plume dispersion model was used to calculate 1 hr $SO_2$ concentration 4 km downwind from a power plant in Boryeung coastal area. Here, measured data for January to December of 2002 were obtained so that modelling results could be compared. To compare the performances between various schemes, integrated scores of statistical measures were obtained by giving weights for each measure and then summing each score. This was done because each statistical measure has its own function and criteria; as a result, no measure can be taken as a sole index indicative of the performance level for each modeling scheme. The best preprocessing scheme was discerned using the step-wise method. The most significant factor influencing the magnitude of real dispersion coefficients appeared to be sampling time. A second significant factor appeared to be surface roughness, with the rolling terrain being the least significant for elevated sources in a gently rolling terrain. The best sequence of correcting the sigma from P-G scheme was found to be the combination of (1) sampling time, (2) surface roughness, (3) plume rising, (4) plume height, and (5) terrain rolling.