Improving UASS pesticide application: optimizing and validating drift and deposition simulations

作者：Qing Tang, Ruirui Zhang, Liping Chen, Pan Zhang, Longlong Li, Gang Xu, Tongchuan Yi, Andrew Hewitt · 发表于：Pest Management Science · 年份：2024 · DOI：10.1002/ps.8412 · 被引用次数：6 · 研究领域：Plant Surface Properties and Treatments、Biomimetic flight and propulsion mechanisms、Lattice Boltzmann Simulation Studies

BACKGROUND: As unmanned aerial spraying systems (UASS) usage grows rapidly worldwide, a critical research study was conducted to optimize the simulation of UASS applications, aiming to enhance pesticide delivery efficiency and reduce environmental impact. The study examined several key aspects for accurate simulation of UASS application with lattice Boltzmann method (LBM). Based on these discussions, the most suitable grid size and simulation parameters were selected to create a robust model for optimizing UASS performance in various pest management scenarios, potentially leading to more targeted and sustainable pest control practices. RESULTS: The effect of stability parameter, grid size around the rotor and near ground, and parameters at wake flow were carefully analyzed to improve the precision of pesticide drift predictions and deposition patterns. Optimal grid sizes were identified as 0.2 m generally, 0.025 m near rotors, and a 0.1 + 0.2 m scheme for ground proximity, with finer grids improving accuracy but increasing computation time. Wake resolution and threshold significantly influenced simulation results, while wake distance had minimal impact beyond a certain point. The LBM's accuracy was validated by comparing simulated downwash flow and droplet deposition with field test data. CONCLUSION: This study optimized UASS simulation parameters, balancing computational efficiency with accuracy. The validated model enhances our ability to design more effective UASS for pest...