EULERIAN-LAGRANGIAN MODEL FOR DOWNSCALING WIND FIELDS AND PARTICLES DISPERSION WITH APPLICATION TO BEIRUT CITY

Abstract

The study of pollutant dispersion in urban areas is complex due to its dependency on the atmospheric boundary layer (ABL) flow and the near buildings perturbed flow. Computational fluid dynamics (CFD) models with the RANS turbulent closure schemes are a good compromise between accuracy and computational cost when solving such problems. In this study, we created a tool for solving wind flow in urban areas using the prognostic approach that is based on CDF models, and the diagnostic approach that is based on imposing mass continuity by solving an optimization equation. However, the use of standard RANS closure schemes with standard sand-grain rough wall function in the prognostic model show inconsistency with inlet conditions. To solve this issue, we implemented a new formulation of the Richards and Hoxey wall function and a modification of the k-ε model, and we derived a modification for the k-ω model. We implemented two methods for calculating the concentration field. The first one is under the Eulerian framework by solving the concentration transport equation and the second one under the Lagrangian framework by using the particle method with core radius spreading for diffusion. We tested the flow and dispersion models by simulating the wind field in an empty domain using different variations with k-ε and k-ω models. Then, by simulating the flow and particles dispersion around a building using the modified k-ε and k-ω models with the new wall function formulation and using the k-ω SST by resolving the viscous sublayer. Moreover, we simulated the flow field using the modified k-ε model for a domain containing an array of buildings.