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Description
Plume dispersion into the atmosphere of radioactive cloud emitted by a source can be affected by the presence of buildings and obstacles modifying the velocity and the spatial distribution fields respect to the classical Gaussian Plume Model. The Gaussian Plume Model (GPM) is often used to assess the submersion dose resulting from an emission stack. The dispersion of the radioactive cloud is determined by computing the Brigg's coefficients, which are influenced by meteorological factors such as wind speed and atmospheric stability. Huber et al. [1] has proposed a simplified model to estimate the increased dispersion caused by obstructions and buildings. This is achieved by incorporating modified parameters into the Gaussian Plume Model (GPM) framework. The model created by Huber includes modifications to the dispersion parameters and Brigg's coefficients to account for the looping movement of the plume in the lee of the buildings. This looping movement is caused by vortices generated in the flow field around the obstacles. Huber model simply takes into account basic characteristics, such as the maximum height of obstacles, without considering the actual geometry of the domain.
An accurate estimation of the dispersion of a radioactive plume can be obtained by recurring to computational fluid-dynamics (CFD) models. Furthermore, the dispersion of radionuclides can be incorporated into the Monte Carlo code FLUKA to enhance the accuracy of dose evaluation. Computational Fluid Dynamics (CFD) models are very valuable for assessing conditions in close proximity within urban environments, where the assumptions or the Gaussian Plume Model (GPM) cannot be used. This is especially crucial for nuclear medicine and hadrontherapy centers located in densely populated areas, in which GPM models might significantly overestimate radiation exposure. The model includes a chimney releasing radioactive gases together with adjacent buildings of an urban agglomeration of a hadrontherapy center. Accurate meshing of the domain for the CFD-simulation has been considered with settings of refinement size for calculation cells near the obstacle surfaces.
The study focuses on comparisons between Gaussian plume and fluid dynamic models to assess their performance at both short and long distances. The Reynolds Averaged Navier-Stokes equations and the k-ω turbulence closure model are used [2] and adapted in order to consider atmospheric stability, temperature stratification, and ground roughness effects. Numerical results have been obtained by considering various stability atmospheric conditions. Comparisons with the Huber approximation are reported.
[1] Alan H. Huber, “Evaluation of a method for estimating pollution concentrations downwind of influencing buildings”, Atmospheric Environment, 18(11), 2313-2338, 1967.
https://doi.org/10.1016/0004-6981(84)90003-9
[2] Breedt, H. J., Craig, K. J., & Jothiprakasam, V. D. (2018). Monin-Obukhov similarity theory and its application to wind flow
modelling over complex terrain. Journal of Wind Engineering and Industrial Aerodynamics, 182, 308-321.
| Scientific Topic 5 | Induced radioactivity and decommissioning |
|---|---|
| Scientific Topic 7 | Medical and industrial accelerators |
