Improving Wind Speed Forecasting for Urban Air Mobility Using Coupled Simulations

Abstract

Hazardous weather, turbulence, wind, and thermals pose a ubiquitous challenge to Unmanned Aircraft Systems (UAS) and electric-Vertical Take-Off and Landing (e-VTOL) aircrafts, and the safe integration of UAS into urban area requires accurate high-granularity wind data especially during landing and takeoff phases. Two models, namely, Open-Source Field Operation and Manipulation (OpenFOAM) software package and Weather Research and Forecasting (WRF) model, are used in the present study to simulate airflow over Downtown Oklahoma City, Oklahoma, United States. Results show that computational fluid dynamics wind simulation driven by the atmospheric simulation significantly improves the simulated wind speed because the accurate modeling of the buildings affects wind patterns. The evaluation of different simulations against six Micronet stations shows that WRF-CFD numerical evaluation is a reliable method to understand the complicated wind flow within built-up areas. The comparison of wind distributions of simulations at different resolutions shows better description of wind variability and gusts generated by the urban flows. Simulations assuming anisotropy and isotropy of turbulence show small differences in the predicted wind speeds over Downtown Oklahoma City given the stable atmospheric stratification showing that turbulent eddy scales at the evaluation locations are within the inertial subrange and confirming that turbulence is locally isotropic.