Reconciling Gaussian plume and Computational Fluid Dynamics models of particulate dispersion. (January 2020) - Joseph, G.M.D.; Hargreaves, D.M.; Lowndes, I.S.
Abstract: Computational Fluid Dynamics (CFD) is increasingly used to model particulate dispersion in situations where Gaussian Dispersion models are inappropriate or inaccurate. However, there is evidence which indicates that many CFD models under-predict lateral plume spread. This paper aims to address this by implementing a strategy which incorporates wind direction variability into CFD models using a formulation which is also used in the UK-ADMS plume spread module. In the present work, a series of CFD simulations are run at various wind angles. The outputs from these simulations are weighted using a Gaussian probability density function and combined to produce a plume. The standard k − ε model has been employed to solve the RANS equations of the flow field for stable, neutral and unstable atmospheric stabilities, coupled with the Lagrangian Particle tracking model to model dispersion. By comparing the CFD accretion profiles to UK-ADMS dry deposition results, it is observed that the proposed modelling methodology produces lateral spreading of the plume which is comparable to that obtained using UK-ADMS. However, the Lagrangian integral time scale constant, c L, which governs the influence turbulence has on the dispersion, must also be modified to bring absolute values of accretion rates in line with those observed in UK-ADMS. Highlights: CFD dispersion/deposition models are difficult with Gaussian models. Wind direction variability should be included in CFD dispersion models. Predictions from CFD models are highly sensitive to dispersion parameters. CFD models perform best under stable atmospheric conditions.