uDALES: large-eddy-simulation software for urban flow, dispersion, and microclimate modelling

Tom Grylls, Ivo Suter, Birgit Sützl, Sam Owens, David Meyer, Maarten van Reeuwijk

Journal of Open Source Software · 2021

Abstract

With continuing urbanization, challenges associated with the urban environment such as air quality, heat islands, pedestrian thermal comfort, and wind loads on tall buildings, are in- creasingly relevant. Our ability to realistically capture processes such as the transport of heat, moisture, momentum and pollutants, and those of radiative transfer in urban environments is key to understanding and facing these challenges ( Oke et al., 2017 ). The turbulent nature of the urban flow field and the inherent heterogeneity and wide range of scales associated with the urban environment result in a complex modelling problem. Large-eddy simulation (LES) is an approach to turbulence modelling used in computational fluid dynamics to simu- late turbulent flows over a wide range of spatial and temporal scales. LES is one of the most promising tools to model the interactions typical of urban areas due to its ability to resolve the urban flow field at resolutions of O(1 m, 0.1 s), over spatial domains of O(100 m), and time periods of O(10 h). Although there are many scalable LES models for atmospheric flows, to our knowledge, only few are capable of explicitly representing buildings and of modelling the full range of urban processes (e.g. PALM-4U Resler et al. (2017); Maronga et al. (2020); or OpenFoam Weller et al. (1998)). uDALES (urban Dutch Atmospheric LES) is an extension of DALES (Dutch Atmospheric LES; Heus et al. (2010), Tomas et al. (2015)). It has the additional functionality of modelling buildings within the fluid domain and therefore the capability to model urban environments at the microclimate scale with wet thermodynamics (Table 1). The uDALES framework includes tools to enable users to model a wide variety of idealized and complex urban morphologies (Sützl, 2021 ; Sützl et al., 2021 ). uDALES uses an Arakawa C-grid and typically uses second- order central-differencing schemes. For scalar quantities, e.g. for pollution concentration, it is possible to use a kappa-sch