Three-dimensional computational fluid dynamics investigation of the dispersion of radioactive cloud

The evaluation of spatial distributions of plume dispersion into the atmosphere is an important task for estimating the release of radioactive gas. The Gaussian Plume Model (GPM) represents the most adopted implementation for submersion dose evaluations from an emission stack. The radioactive cloud dispersion is obtained by calculating the Brigg’s coefficients that varies with the meteorological conditions, mainly the wind speed and the atmosphere stability. The ideal scenarios for GPMs are nuclear plants that are located usually few hundred meters far from population centers. Once the spatial distributions of contaminants are known, doses can be calculated multiplying the radionuclide concentration in a certain point by Dose Conversion Factors. On the other hand, nuclear medicine and hadrontherapy centers are situated in populated areas and GPM models can excessively overestimate submersion doses. For this reason, the correct estimation of a radioactive plume dispersion can be estimated with computational fluid-dynamics (CFD) models. Subsequently, the radionuclide dispersion can be implemented in the Monte Carlo code FLUKA to make more accurate dose evaluations. In this work, comparisons between the results obtained with the U.S. Department of Energy (DOE)-certified software Hotspot and CFD Ansys Fluent are performed in order to compare a GPM model with a CFD model at short and long distances. CFD numerical results have been obtained by solving the steady-state Reynolds Averaged Navier-Stokes (RANS) equations using the k-ε turbulence closure model. The RANS modelling is modified to account for atmospheric stability, thermal stratification, and ground roughness effects. The Monin-Obukhov Similarity Theory (MOST) is employed to define consistent inflow conditions to simulate different levels of atmospheric stability. An unstructured hybrid mesh with local refinement regions is generated to accurately resolve the plume transport region and the flow field close to the ground and the chimney. Numerical results have been obtained by considering different stability atmospheric conditions and comparisons and differences between GPM and CFD models are presented and discussed.