From active grids to fan-array wind generators: A review of turbulence generation, control, and artificial intelligence integration in wind tunnels

Wind tunnel testing has undergone a significant transformation. Traditionally, it focused on generating uniform, low-turbulence flows for clean aerodynamic testing of aircraft models. Early advancements broadened this scope to include homogeneous and isotropic turbulence, as well as atmospheric boundary layers, which are crucial for civil engineering applications. However, modern demands, ranging from civil engineering to the low-altitude economy (e.g., drones), now require the ability to reproduce complex, spatiotemporally rich turbulence. This need has driven the emergence of novel approaches that enable more precise, adaptable, and programable flow generation. The review is structured to examine advances in active turbulence generation methods, multi-fan driving modes, control system architectures, and the emerging role of artificial intelligence in flow modulation. As a representative realization, we present a detailed case study of the Harbin Institute of Technology-Shenzhen (HIT-Sz), multi fan wind tunnel (MFWT), a high-resolution 768-fan array system capable of hybrid modulation, gust replication, and real-time feedback-driven control. These advancements position MFWTs as critical experimental platforms for next-generation aerodynamic testing, marking a significant shift toward robust and adaptable simulation of realistic atmospheric conditions for unmanned aerial vehicles (UAVs) and civil structures operating in complex, turbulent environments.