Prediction and visualization of 3D wake field of a rectangular high-rise building in tropical island cities based on UAV measurements

It is especially crucial to utilize measured data as samples to increase the accuracy of wind field prediction. However, scarce wake field measured data of high-rise buildings leads to the deviation between prediction results and the actual wake distribution. In this study, a six-rotor unmanned aerial vehicle wind measurement system (UAVWMS) equipped with an anemometer is used to measure the wake field of a rectangular high-rise building in a tropical island city, and the characteristics of fluctuating wind velocity spectra and distribution patterns of the wind velocity and turbulence intensity in the wake region are analyzed; the Kriging method is adopted to predict and visualize the three-dimensional (3D) wake field based on the measured data from UAVWMS. The results show that the exponential law is better than the logarithmic law in fitting the incoming wind velocity profile in the tropical island city. The measured points in the wake region, located near the central axis of the building, exhibit a pronounced reduction in wind velocity and an increase in turbulence intensity compared to those in the incoming region. Compared to the incoming wind velocity spectra and empirical spectra, the peak frequencies of wake wind velocity spectra shift to the high-frequency band. In addition, the wake wind velocity spectra are lower in the low-frequency band and higher in the high-frequency band. When designing a measured scheme based on UAVWMS, it's crucial to place measured points surrounding the target spatial wake field as much as possible. It helps enhance the accuracy of predicting wind parameters within the 3D spatial wake field. The research results provide a theoretical reference for the measurement, prediction and visualization of the wake field of high-rise buildings in dense urban buildings.