• Journal of Radiation Protection and Research
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• v.23 no.4
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• pp.251-257
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• 1998

A diffusion model of radioactive gaseous effluents is improved to apply for domestic nuclear power plants. Up to now, XOQDOQ computer code package developed by U. S NRC has been used for the assessment of radioactive plume dispersion by normal operation of domestic nuclear power plants. XOQDOQ adopts the straight-line Gaussian plume model which was basically derived for the plane terrain. However, since there are so many mountains in Korea, the several shortcomings of XOQDOQ are improved to consider the complex terrain effects. In this work, wind direction change is considered by modifying the wind rose frequency using meteorological data of the local weather stations. In addition, an effective height correction model, a plume reduction model due to plume penetration into mountain, and a wet deposition model are adopted for more realistic assessments. The proposed methodology is implemented in Yongkwang nuclear power plants, and can be used for other domestic nuclear power plants.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.5
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• pp.539-544
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• 2000

A simple analytic model is proposed here to analyze the concentration deficit field caused by a large area of vegetated area. With non-dimensional deposition velocity chosen as small parameter, the regular perturbation method is exploited to derive the mass balance equation and the dynamic equations for the concentration deficit field, Analytic solutions to those equations are obtained in a closed form for several cases of interest, assuming that the concentration field is stationary and the plume can be nicely approximated as Gaussian for a point source. The results suggest that quite a negligible fraction (less than 1%) of the gaseous air pollutants emitted into the air is removed by the vegetated area of which width is 4 km in wind-wise direction, the typical dimension of the Restricted Development Zones around the metropolitan regions in South Korea.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.E4
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• pp.215-221
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• 2002

The real-time modeling system, named AirWatch System, has been developed to evaluate the environmental impact from a large source. It consists of stack TMS (TeleMetering System) that measures the emission data from the source, AWS (Automatic Weather Station) that monitors the weather data and computer system with the dispersion modeling software. The modeling theories used in the system are Gaussian plume and puff models. The Gaussian plume model is used for the dispersion in the simple terrain with a point meteorological data while the puff model is for the dispersion in complex terrain with three dimensional wind fields. The AirWatch System predicts the impact of the emitted pollutants from the large source on the near-by environment on the real -time base and the alarm is issued to control the emission rate if the calculated concentrations exceed the modeling significance level.

• 대한방사선방어학회:학술대회논문집
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• 2009.04a
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• pp.146-147
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• 2009

• Journal of Korean Society for Atmospheric Environment
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• v.14 no.2
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• pp.81-94
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• 1998

Six complex terrain dispersion models recommended by the U. S. Environmental Protection Agency were investigated using a hypothetical case in which a plume approaches complex terrain. The six models considered were Valley, CTSCREEN, COMPLEX 1, SHORTZ, RTDM, and CTDMPLUS, the latter four being closely studied. Highest concentrations were predicted for 48 receptors and plume behaviors were compared for stable and unstable meteorological conditions. Under stable conditions, ground-level concentrations were determined by the height of the plume centerline above the terrain. The concentrations estimated by SHORTZ and COMPLEX I were higher than those estimated by CTSCREEN, with CTDMPLUS predicting the lowest concentrations. In particular, the height of the lift midpoint, as well as the co.nterline of the plume, are important in the model calculation of CTDMPLUS. Under unstable conditions, the vertical dispersion plays a key role in determining ground -level concentrations. For this case, concentrations predicted by CTDMPLUS were the 'highest, whereas those predicted by SHORTZ were the lowest. Concentration distributions predicted by CTDMPLUS are quite similar to typical Gaussian distributions even on complex terrain, except for a slight shift of the plume centerline due to the of(tract of the geostrophic wind. In addition,24-hour average concentrations were estimated for comparison with results from the Valley model. Among the four models studied closely, CTDMPLUS predicted the lowest 24-hour average concentrations, but the concentrations estimated by Valley were lower than those estimated by CTDMPLUS.

• Journal of Radiation Protection and Research
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• v.12 no.2
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• pp.28-36
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• 1987

Gaussian plume model is used to assess environmental dose for abnormal radioactive release in nuclear facility, but there has a problem to use it for complex terrain. In this report, MATTEW and WIND04 Codes which had been verified were used to calculate wind field in the complex terrain. Under the base of these codes principle, wind fields were obtained from the calculation of the finite difference approximation for advection-diffusion equations which satisfy the mass-conservative law. Particle concentrations and external doses were calculated by using PIC model which approximate the particle to radioactive cloud, and atmospheric diffusion of the particles from the random walk method. The results show that the adjusted wind fields and the distributions of the exposure dose vary with the topography of the complex terrain.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.621-632
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• 2013

The most important things for a forest fire detection system are the exact extraction of the smoke from image and being able to clearly distinguish the smoke from those with similar qualities, such as clouds and fog. This research presents an intelligent forest fire detection algorithm via image processing by using the Gaussian Mixture model (GMM), which can be applied to detect smoke at the earliest time possible in a forest. GMMs are usually addressed by making the model adaptive so that its parameters can track changing illuminations and by making the model more complex so that it can represent multimodal backgrounds more accurately for smoke plume segmentation in the forest. Also, in this paper, we suggest a way to classify the smoke plumes via a feature extraction using HSL(Hue, Saturation and Lightness or Luminanace) color space analysis.

• Journal of Radiation Protection and Research
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• v.28 no.4
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• pp.311-319
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• 2003

We developed a grid-based Gaussian plume model to evaluate tracer release data measured at Young Gwang nuclear site in 1996. Downwind distance was divided into every 10m from 0.1km to 20km, and crosswind distance was divided into every 10m centering released point from -5km to 5km. We determined dispersion factors, ${\sigma}_y\;and\;{\sigma}_z$ using Pasquill-Gifford method computed by atmospheric stability. Forecasting ability of the grid-based Gaussian plume model was better at the 3km away from the source than 8km. We confirmed that dispersion band must be modified if receptor is far away from the source, otherwise P-G method is not appropriate to compute diffusion distance and diffusion strength in case of growing distance. So, we developed an empirical equation using linear programming. An objective function was designed to minimize sum of the absolute value between observed and computed values. As a result of application of the modified dispersion equation, prediction ability was improved rather than P-G method.

• Journal of Radiation Protection and Research
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• v.38 no.2
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• pp.60-67
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• 2013

A diffusion coefficient is an important parameter in the prediction of atmospheric dispersion using a Gaussian plume model, and its modelling approach varies. In this study, dispersion coefficients recommended by the U. S. Nuclear Regulatory Commission's (U. S. NRC's) regulatory guide and the Canadian Nuclear Safety Commission's (CNSC's) regulatory guide, and used in probabilistic accident consequence analysis codes MACCS and MACCS2 have been investigated. Based on the atmospheric dispersion model for a hypothetical accidental release recommended by the U. S. NRC, its influence to atmospheric dispersion factor was discussed. It was found that diffusion coefficients are basically predicted from a Pasquill- Gifford curve, but various curve fitting equations are recommended or used. A lateral dispersion coefficient is corrected with consideration for the additional spread due to plume meandering in all models, however its modelling approach showed a distinctive difference. Moreover, a vertical dispersion coefficient is corrected with consideration for the additional plume spread due to surface roughness in all models, except for the U. S. NRC's recommendation. For a specified surface roughness, the atmospheric dispersion factors showed differences up to approximately 4 times depending on the modelling approach of a dispersion coefficient. For the same model, the atmospheric dispersion factors showed differences by 2 to 3 times depending on surface roughness.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.1
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• pp.102-112
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• 2023

This research mainly focuses on the transport and dispersion of chemical agent plume according to the Lagrangian Puff Model and Lagrangian Particle Model of NBC_RAMS(Nuclear, Biological, Chemical Reporting And Modeling S/W System). NBC_RAMS was developed with the purposes of estimating the fate of Chemical, Biological, and Radioactive(CBR) agent plumes and evaluating damages in the Republic of Korea. First, it calculates the local weather pattern, i.e. wind speed, wind direction, and temperature, by considering the effects of land uses and topography. The plume behaviors are calculated by adopting the Lagrangian Puff Model(LPFM) or Lagrangian Particle Model(LPTM). In this research, we assumed a virtual chemical agent exposure event in a stable atmospheric condition during the summer season. The plume behaviors were estimated by both LPFM and LPTM on the used area(urbanized and dry area) and the agricultural land. The higher heat flux in the used area led to stronger winds and further downward movement moving of the chemical agent than the farmland. The lateral dispersion of the chemical plume was emphasized in the Lagrangian Puff Model because it adopted Gaussian distribution.