Urban-Scale Computational Fluid Dynamics Simulations with Boundary Conditions from Similarity Theory and a Mesoscale Model

Demetri Bouris,Anastasios Kopanidis,Efstathios Konstantinidis,Elena Leivaditou,John Skordas,Qing Wang,Athanasios G Triantafyllou,Athina Krestou

doi:10.3390/en14185624

Abstract

Mesoscale numerical weather prediction models usually provide information regarding environmental parameters near urban areas at a spatial resolution of the order of thousands or hundreds of meters, at best. If detailed information is required at the building scale, an urban-scale model is necessary. Proper definition of the boundary conditions for the urban-scale simulation is very demanding in terms of its compatibility with environmental conditions and numerical modeling. Here, steady-state computational fluid dynamics (CFD) microscale simulations of the wind and thermal environment are performed over an urban area of Kozani, Greece, using both the k-ε and k-ω SST turbulence models. For the boundary conditions, instead of interpolating vertical profiles from the mesoscale solution, which is obtained with the atmospheric pollution model (TAPM), a novel approach is proposed, relying on previously developed analytic expressions, based on the Monin Obuhkov similarity theory, and one-way coupling with minimal information from mesoscale indices (Vy = 10 m, Ty = 100 m, L*). The extra computational cost is negligible compared to direct interpolation from mesoscale data, and the methodology provides design phase flexibility, allowing for the representation of discrete urban-scale atmospheric conditions, as defined by the mesoscale indices. The results compared favorably with the common interpolation practice and with the following measurements obtained for the current study: SODAR for vertical profiles of wind speed and a meteorological temperature profiler for temperature. The significance of including the effects of diverse atmospheric conditions is manifested in the microscale simulations, through significant variations (~30%) in the critical building-related design parameters, such as the surface pressure distributions and local wind patterns.

Highlights

The urban-scale microclimate is dependent on urban environmental parameters, local building design and construction, and on the parameters related to mesoscale weather
Among the many advanced turbulence modeling approaches that are available for computational fluid dynamics (CFD) simulations, Reynolds-averaged Navier–Stokes (RANS) models allow for an acceptable balance between accuracy and calculation time, and represent a valid alternative to other methods, such as LES, that have higher resource demands [3]
We investigate the use of analytic expressions [12], based on the Monin–Obukhov similarity theory, for prescribing boundary conditions of the main variables on the lateral boundaries of a CFD computational domain for an urban area

Summary

Introduction

The urban-scale microclimate is dependent on urban environmental parameters, local building design and construction, and on the parameters related to mesoscale weather. The requirements for the boundary conditions have been worked out, their application, especially within commercial CFD software, still remains a challenge in some cases [9,10], necessitating modification of the turbulence model constants [6] This creates an issue of whether or not to use the same constants for the land surface and the building surfaces. E.g., for wind energy assessment, time averaging for long time periods, in the order of years, is needed, and so steady-state simulations are usually performed In these cases, one approach is to use analytic expressions [19] for the interpolation process from the meso- to micro-scale. Through comparison of the vertical profiles with those from the more common interpolation practices, and with measurement data, our combination of analytic expressions from the Monin–Obukhov theory, with empirical relations for meteorological parameters, proves to be a reliable and versatile approach for defining boundary conditions for microscale simulations. Both the index of agreement (IOA) and the root mean square error (RMSE) showed good agreement

Urban Microscale Modeling

Results and Discussion

Conclusions