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

Abstract

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.

Comparison of Downdraught and Up Draft Passive Air Conduction Systems (PACS) in a Winery Building

“…In the case of dense neighborhood in greater distance (Site B), both UD and DD PACS perform stronger than in Site A (lower neighborhood density in closer distance) in the cellar and hall spaces, that proximity of neighbor buildings and objects-even in weaker density-can influence the ventilation rates. These results correlate with previous works [13,43,53], examining and proving significant effects of neighbor objects on the NV performance.…”

“…The territory is an agricultural area on the boundaries of Villány, where the dwellers usually cultivate grapes, so the vegetation is mainly formulated by linearly organized vineyards, with an average of 2 m heights (Figure 3). Since the modeling of the surrounding (e.g., vegetation, buildings) can significantly affect the aerodynamic circumstances [13,43] two sites were considered, one with two direct neighbors and the other with more neighbor buildings but in further distance, respectively. Here, the scientific opportunity was occurred to investigate the effects of the different neighborhoods on the PACS of the winery under the same weather conditions.…”

A parametric study on the effects of green roofs, green walls and trees on air quality, temperature and velocity

“…In this case study, the temperature and velocity variations are computed using coupled flow and energy equations. The flow model is based on the RANS equations with the standard k-ε turbulence model, as described in [28][29][30][31]. The segregated fluid temperature energy model is employed in this simulation.…”

Improving the Energy Efficiency of Buildings Based on Fluid Dynamics Models: A Critical Review

“…In certain cases, however, some models are not suitable ones. A case study using different RANS models was studied in [103]. The standard and realizable k-ε models had better accuracy, compared with the standard k-ω and SST k-ω model.…”