The presence of tall buildings in cities affects momentum and scalar exchange within and above the urban canopy. As wake effects can be important over large distances, they are crucial for urban-flow modelling on and across different spatial scales. We explore the aerodynamic effects of tall buildings on the microscale to local scales with a focus on the interaction between the wake structure, canopy and roughness sublayer flow of the surroundings in a realistic urban setting in central London. Flow experiments in a boundary-layer wind tunnel use a 1:200 scale model with two tall buildings (81 m and 134.3 m) for two wind directions. Large changes in mean flow, turbulence statistics and instantaneous flow structure of the wake are evident when tall buildings are part of the complex urban canopy rather than isolated. In the near-wake, the presence of lower buildings displaces the core of the recirculation zone upwards, thereby reducing the vertical depth over which flow reversal occurs. This amplifies vertical shear at the rooftop and enhances turbulent momentum exchange. In the near part of the main wake, lateral velocity fluctuations and hence turbulence kinetic energy are reduced compared to the isolated building case as eddies generated in the urban canopy and roughness sublayer distribute energy down to smaller scales that dissipate more rapidly. Evaluation of a wake model for flow past isolated buildings suggests model refinements are needed to account for such flow-structure changes in tall-building canopies. Keywords Tall-building environments • Urban canopy • Urban flow • Wake model • Wind tunnel Nomenclature H Building (roof) height H NoTall Mean building height (No Tall) H ave Mean building height Electronic supplementary material The online version of this article (

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To help create a comfortable and healthy indoor and outdoor environment in which to live, there is a need to understand turbulent air flows within the urban environment. To this end, building on a previously reported method [1], we develop a fast-running Non-Intrusive Reduced Order Model (NIROM) for predicting the turbulent air flows found within an urban environment. To resolve larger scale turbulent fluctuations, we employ a Large Eddy Simulation (LES) model and solve the resulting computational model on unstructured meshes. The objective is to construct a rapid-running NIROM from these results that will have 'similar' dynamics to the original LES model. Based on Proper Orthogonal Decomposition (POD) and machine learning techniques, this Reduced Order Model (ROM) is six orders of magnitude faster than the high-fidelity LES model and we demonstrate how 'similar' it can be to the high-fidelity model by comparing statistical quantities such as the mean flows, Reynolds stresses and probability densities of the velocities. We also include validation of the high-fidelity model against data from wind tunnel experiments. This paper represents a key step towards the use of reduced order modelling for operational purposes with the tantalising possibility of it being used in place of Gaussian plume models, and the potential for greatly improved model fidelity and confidence.

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BackgroundInfluenza virus is responsible for annual deaths due to seasonal epidemics and is the cause of major pandemics which have claimed millions of human lives over the last century. Knowledge about respiratory virus transmission is advancing. Spread is likely through the air, but much work remains to be done to characterize the aerosols produced by infected individuals, including viral particle survival and infectivity. Although coughs have been characterized, little work has been done to examine coughs from infected individuals. The WeCoF project aims at providing evidence to support prevention measures to mitigate person-to-person influenza transmission in critical locations, such as hospitals, and during pandemics.FindingsA novel experimental cough chamber facility – the FLUGIE – has been developed to study the far-field aerodynamics and aerosol transport of droplets produced by the coughs from humans naturally-infected with influenza. The flow field of each cough is measured using Particle Image Velocimetry (PIV). A preliminary study involving 12 healthy individuals has been carried out in order to quantify the strengths of their coughs at a distance of 1 m from the mouth. The spatially averaged maximum velocity was determined and the average value was 0.41 m/s across 27 coughs of good data quality. The peak value of velocity was also extracted and compared with the average velocity.ConclusionsPreliminary results show that there is significant air motion associated with a cough (on the order of 0.5 m/s) as far away as 1 m from the mouth of the healthy person who coughs. The results from this pilot study provide the framework for a more extensive participant recruitment campaign that will encompass a statistically-significant cohort.