Predicting the Wind Field at the Wake of Buildings: Insights from High-Fidelity Simulations and Turbulence Structure Based Low-Order Modeling

In this study, we investigate the wind flow dynamics in the wake of buildings using high-fidelity simulations, including Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulations (LES), conducted with the high-order spectral-element solver Nek5000/NekRS. By employing realistic boundary conditions, our simulations accurately represent the complex and turbulent wind flow conditions encountered in urban environments.

Our analysis identifies two dominant turbulence structures that significantly influence the flow in the wake of an obstacle: the main wake structure and the horseshoe/acceleration vortex around buildings. We further explore how varying building aspect ratios and wind flow angles affect the wake characteristics, providing a detailed description of the wake structure for each case.

Informed by our high-fidelity simulations, we propose a turbulence phenomenology-based approach for low-order modeling of flow around buildings. This approach leverages the results from our simulations and integrates data-driven techniques to generalize analytical expressions derived from the governing equations. Specifically, we extend these expressions, initially developed for simple cases involving unit cuboids and zero wind angle, to accommodate a broader range of building geometries and wind flow conditions. Importantly, these low-order models offer a real-time method for estimating the flow structure around buildings with negligible computational cost, especially compared to CFD simulations. The model was validated against independent wind-tunnel and real-world wind and energy production observations, showing excellent agreement between predictions and measured results.

Our findings contribute to the development of more accurate and computationally efficient models for predicting wind flow around buildings, with potential applications for optimizing wind energy projects in complex urban and suburban environments.