Tang Qing, Zhang Ruirui, Chen Liping, Zhang Pan, Li Longlong, Xu Gang, Yi Tongchuan, Hewitt Andrew
Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
National Center for International Research on Agricultural Aerial Application Technology, Beijing, China.
Pest Manag Sci. 2025 Jan;81(1):127-140. doi: 10.1002/ps.8412. Epub 2024 Sep 17.
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.
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.
This study optimized UASS simulation parameters, balancing computational efficiency with accuracy. The validated model enhances our ability to design more effective UASS for pest management, potentially leading to more precise and targeted pesticide applications. These advancements contribute to the development of sustainable pest control strategies, aiming to reduce pesticide usage and environmental impact while maintaining crop protection efficacy. © 2024 Society of Chemical Industry.
随着无人机喷雾系统（UASS）在全球范围内的使用迅速增长，开展了一项关键研究以优化无人机喷雾系统应用的模拟，旨在提高农药喷洒效率并减少对环境的影响。该研究使用格子玻尔兹曼方法（LBM）研究了准确模拟无人机喷雾系统应用的几个关键方面。基于这些讨论，选择了最合适的网格尺寸和模拟参数，以创建一个强大的模型，用于优化无人机喷雾系统在各种害虫管理场景中的性能，这可能会带来更具针对性和可持续性的害虫防治实践。
仔细分析了稳定性参数、旋翼周围和近地面的网格尺寸以及尾流处的参数的影响，以提高农药漂移预测和沉积模式的精度。确定的最佳网格尺寸一般为0.2米，旋翼附近为0.025米，地面附近为0.1 + 0.2米方案，更精细的网格提高了精度，但增加了计算时间。尾流分辨率和阈值对模拟结果有显著影响，而尾流距离在超过一定点后影响最小。通过将模拟的下洗流和液滴沉积与现场测试数据进行比较，验证了LBM的准确性。
本研究优化了无人机喷雾系统的模拟参数，在计算效率和准确性之间取得了平衡。经过验证的模型增强了我们设计更有效的无人机喷雾系统用于害虫管理的能力，这可能会带来更精确和有针对性的农药应用。这些进展有助于可持续害虫防治策略的发展，旨在减少农药使用和环境影响，同时保持作物保护效果。© 2024化学工业协会。
