Computational Simulation of Wind Microclimate in Complex Urban Models and Mitigation Using Trees

Due to a rapid increase in urbanisation, accurate wind microclimate assessment is of crucial importance. Evaluating wind flows around buildings is part of the planning application process in the design of new developments. In this study, computational fluid dynamics (CFD) simulations are carried out for a case study, representing the East Village in the London Olympic Park. Following a validation test against experimental data for a simpler urban configuration, the key input parameters, including appropriate boundary conditions, mesh setting and type of turbulence model, are selected for the Olympic Park model. All the simulations are conducted using the commercial code STARCCM+ under steady-state conditions with the Reynolds-averaged Navier–Stokes (RANS) method. The turbulence is modelled using different common variants of eddy-viscosity models (EVMs) including standard k-ε, realizable k-ε and standard and shear stress transport (SST) k-ω. The results demonstrate that standard and realisable k-ε models correlate very well with the experimental data, while some discrepancies are found with standard and SST k-ω. Following the determination of areas of high velocity, appropriate tree planting is proposed to overcome the effect of corner and downwash acceleration. With the optimised arrangement of trees and using specific types of tree (e.g., birch), wind speeds at the pedestrian level are reduced by 3.5, 25 and 66% in three main regions of interest. Moreover, we investigate the effects of tree heights. The obtained results illustrate that the wind velocity reduces when the crowns of the trees are located closer to the buildings and the ground. Our high-resolution CFD simulation and results offer a quantitative tool for wind microclimate assessment and optimised design and arrangement of trees around buildings to improve pedestrian comfort.

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.