Abstract

Unmanned Aerial Vehicles (UAVs) are seeing increased use in agricultural settings due to their potential to be integrated with systems for applying pesticides. They can target specific areas while offering the potential to reduce chemical waste and improve application efficiency. However, this means that spray deposition efficiency is strongly influenced by rotor-induced downwash, which affects droplet transport, drift, and uniformity. This study presents a combined computational and experimental investigation of downwash–spray interactions in a hexacopter platform. CFD is used to predict the performance of various sprayer configurations that differ in the number, spacing, and positioning of nozzles. Rotor-induced airflow is modeled using an actuator disk approach in ANSYS Fluent 2025, and spray behavior is predicted using the Discrete Phase Model. Pure water was used as the working fluid for both the CFD simulations and experimental validation to ensure consistency between numerical and physical testing conditions. Numerical results indicate that a two-nozzle under-rotor setup maximizes performance characteristics such as deposition area, density, and uniformity for the designed agricultural UAV, providing a theoretically effective deposition area of 9.375 m2, an effective application rate of 0.03387 mL/m2, and a coefficient of variation of 45.3%. Compared to the best-performing boom configuration, this represents an approximately 13.5% improvement in spray uniformity. These results are validated through experimental testing using a modular UAV sprayer system and deposition measurements obtained from water-sensitive paper in controlled indoor conditions, achieving a droplet size of 502 µm, swath width of 1.8 m, 0.8% area coverage, and a coefficient of variation of 36.5%. While differences were observed between predicted and measured droplet size distributions, the CFD and experimental results demonstrated similar trends in spray coverage and deposition uniformity. Future work will refine simulations to better match experimental conditions and investigate canopy interaction, crosswind effects, and field-scale performance.

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