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Recently, there has been a growing interest in utilizing computational fluid dynamics (CFD) for wind resistant design of tall buildings. A key factor that influences the accuracy and computational expense of CFD simulations is the size of the computational domain. In this paper, the effect of the computational domain on CFD predictions of wind loads on tall buildings is investigated with a series of sensitivity studies. Four distinct sources of domain error are identified which include wind-blocking effects caused by short upstream length, flow recirculation due to insufficient downstream length, global venturi effects due to large blockage ratios, and local venturi effects caused by insufficient clearance between the building and top and lateral domain boundaries. Domains based on computational wind engineering guidelines are found to be overly conservative when applied to tall buildings, resulting in uneconomic grids with a large cell count. A framework for optimizing the computational domain is proposed which is based on monitoring sensitivity of key output metrics to variations in domain dimensions. The findings of this paper help inform modellers of potential issues when optimizing the computational domain size for tall building simulations.

Recently, there has been a growing interest in utilizing computational fluid dynamics (CFD) for wind analysis of tall buildings. A key factor that influences the accuracy of CFD simulations in urban environments is the homogeneity of the atmospheric boundary layer (ABL). This paper aims to investigate solution inaccuracies in CFD simulations of tall buildings that are due to ABL inhomogeneity. The investigation involves two steps. In the first step, homogenous and inhomogeneous ABL conditions are generated in an empty computational domain by employing two different modelling approaches. In the second step, the homogenous and inhomogeneous conditions are each applied to an isolated tall building, and simulation results are compared to investigate impact of ABL inhomogeneity on wind load predictions. The study finds that ABL inhomogeneity can be a significant source of error and may compromise reliability of wind load predictions. The largest magnitude of inhomogeneity error occurred for pressure predictions on the windward building surface. Shortening the upstream domain length reduced inhomogeneity errors but increased errors due to wind-blocking effects. The study proposes a practical approach for detecting ABL inhomogeneity that is based on monitoring sensitivity of key output metrics to variations in upstream domain length.

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