• 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)

• Proceedings of the Korea Air Pollution Research Association Conference
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• 1998.10a
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• pp.266-267
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• 1998

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.899-904
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• 2003

A new model for dense gas dispersion is formulated within the Lagrangian framework. In several accidental released situations, denser-than-air vapour clouds are formed which exhibit dispersion behavior markedly different from that observed for passive atmospheric pollutants. For relevant prediction of dense gas dispersion, the gravity and entrainment effects need to implemented. The model deals with negative buoyancy which is affected by gravity. Also, the model is subjected to entrainment. The mean downward motion of each particle was accounted for by considering the Langevin equation with buoyancy correction term.

• Journal of Ocean Engineering and Technology
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• v.23 no.2
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• pp.37-46
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• 2009

Typhoon Rusa in 2002 was recorded as causing the biggest damage due to flood in our country. With the enormous damage to the land, the flood was totally discharged to the open sea. As a result, in the coastal area, the discharging of a river had a big influence in comparison to the scale of the coastal area, which suffered damaged due to the discharging of the river. As it cleared the land, the load was totally discharging into the sea, where it caused various problems due to its influence on the ecosystem. These included changes to the environment, like a difference in salinity and the inflow of a land load. Therefore, in this study, a Lagrangian particle tracking model was constructed using a flow model capable of solving the behavior of a river plume, supposing Sachon Bay. It is performed the research able to tendency-like valuation and reappearance about real event. The result was that the model was well approximated the sea area tendency and the river plume of the specific event.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.5
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• pp.613-623
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• 1999

A Lagrangian particle dispersion mode l(LPDM) coupled with the prognostic flow model based on nonequilibrium level 2.5 turbulence closure has been dcveloped to simulate the dispersion from an elevated emission source. The proposed model did not require any empirical formula or data for the turbulent statistics such as velocity variances and Lagrangian time scales since the turbulence properties for LPDM were calculated from results of the flow model. The LPDM was validated by comparing the model results against the wind tunnel tracer experiment and ISCST3 model. The calculated wind profile and turbulent velocity variances were in good agreement with those measured in the wind tunnel. The ground level concentrations along the plume centerline as well as the dispersion codfficients also showed good agreement in comparison with the wind tunnel tracer experiment. There were some discrepancies on the horizontal spread of the plume in comparison with the ISCST3 but the maximum ground level concentrations were in a good confidence range. The results of comparisons suggested that the proposed LPDM with the flow model was an effective tool to simulate the dispersion in the flow situation where the turbulent characteristics were not available in advance.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.6
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• pp.757-765
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• 1999

Lagrangian particle dispersion model(LPDM) is an effective tool to calculate the dispersion from a point source since it dose not induce numerical diffusion errors in solving the pollutant dispersion equation. Fictitious particles are released to the atmosphere from the emission source and they are then transported by the mean velocity and diffused by the turbulent eddy motion in the LPDM. The concentration distribution from the dispersed particles in the calculation domain are finally estimated by applying a particle count method or a Gaussian kernel method. The two methods for calculating concentration profiles were compared each other and tested against the analytic solution and the tracer experiment to find the strength and weakness of each method and to choose computationally time saving method for the LPDM. The calculated concentrations from the particle count method was heavily dependent on the number of the particles released at the emission source. It requires lots fo particle emission to reach the converged concentration field. And resulting concentrations were also dependent on the size of numerical grid. The concentration field by the Gaussian kernel method, however, converged with a low particle emission rate at the source and was in good agreement with the analytic solution and the tracer experiment. The results showed that Gaussian kernel method was more effective method to calculate the concentrations in the LPDM.