Author
Listed:
- Zongru Liu
(College of Engineering, South China Agricultural University, Guangzhou 510642, China)
- Rong Gao
(College of Engineering, South China Agricultural University, Guangzhou 510642, China)
- Yinwei Zhao
(College of Engineering, South China Agricultural University, Guangzhou 510642, China)
- Han Wu
(College of Engineering, South China Agricultural University, Guangzhou 510642, China)
- Yunting Liang
(College of Engineering, South China Agricultural University, Guangzhou 510642, China)
- Ke Liang
(College of Engineering, South China Agricultural University, Guangzhou 510642, China)
- Dong Liu
(College of Engineering, South China Agricultural University, Guangzhou 510642, China)
- Taoran Huang
(College of Engineering, South China Agricultural University, Guangzhou 510642, China)
- Shaoqiang Xie
(College of Engineering, South China Agricultural University, Guangzhou 510642, China)
- Jia Lv
(College of Engineering, South China Agricultural University, Guangzhou 510642, China)
- Jiyu Li
(College of Engineering, South China Agricultural University, Guangzhou 510642, China)
Abstract
Agricultural unmanned aerial vehicles (UAVs), increasingly integral to crop protection through spraying operations, are significantly influenced by their downwash fields, which in turn affect the distribution of spray droplets. The key parameters impacting spray deposition patterns are the velocity of the downwash airflow and its spatial extent. Understanding the interplay of these parameters can enhance the efficacy of UAV applications in agriculture. Previous research has predominantly focused on downwash airflow velocity, often neglecting the spatial scope of the downwash. This paper presents an applied foundational study grounded in the compressible Reynolds-averaged Navier–Stokes (RANS) equations. Leveraging a dependable k - ε turbulence model and dynamic mesh technology, it develops an effective three-dimensional computational fluid dynamics (CFD) approach to analyze the downwash field’s distribution characteristics during UAV hover. To validate the CFD method, a visualization test was conducted using EPS (expanded polystyrene foam) balls dispersed in the airspace beneath the UAV, illustrating the airflow’s spatial distribution. Additionally, a parameter η was introduced to quantify changes in the wind field’s range, enabling the mapping of the cross-sectional area of the downwash airflow at various velocities within the UAV’s airspace. The study reveals that the downwash field’s overall shape evolves from a “four-point type” to a “square-like” and then to an “ellipse-like” configuration. Lower downwash airflow velocities exhibit a more rapid expansion of the wind field area. High-velocity downwash areas are concentrated beneath each rotor, while lower-velocity zones coalesce under each rotor and extend downward, forming a continuous expanse. Within the UAV’s downwash area, the deposition of droplets is more pronounced. At a given nozzle position, an increase in downwash airflow velocity correlates with greater droplet deposition within the downwash field. This research bridges a gap in downwash field studies, offering a solid theoretical foundation for the development of future UAV downwash field models.
Suggested Citation
Zongru Liu & Rong Gao & Yinwei Zhao & Han Wu & Yunting Liang & Ke Liang & Dong Liu & Taoran Huang & Shaoqiang Xie & Jia Lv & Jiyu Li, 2024.
"Study on the Characteristics of Downwash Field Range and Consistency of Spray Deposition of Agricultural UAVs,"
Agriculture, MDPI, vol. 14(6), pages 1-29, June.
Handle:
RePEc:gam:jagris:v:14:y:2024:i:6:p:931-:d:1414137
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