Influence of the atmospheric boundary layer stability on aerial spraying studied by computational fluid dynamics
文献类型: 外文期刊
作者: Tang, Qing 1 ; Zhang, Ruirui 1 ; Chen, Liping 1 ; Deng, Wei 1 ; Xu, Min 1 ; Xu, Gang 1 ; Li, Longlong 1 ;
作者机构: 1.Beijing Acad Agr & Forestry Sci, Res Ctr Intelligent Equipment, Beijing 100097, Peoples R China
2.Natl Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China
3.Natl Ctr Int Res Agr Aerial Applicat Technol, Beijing 100097, Peoples R China
关键词: Aerial application; Computational fluid dynamics; Droplet drift; Atmospheric stability; Wing tip vortex
期刊名称:BIOSYSTEMS ENGINEERING ( 影响因子:5.002; 五年影响因子:5.321 )
ISSN: 1537-5110
年卷期: 2022 年 215 卷
页码:
收录情况: SCI
摘要: Atmospheric stability can significantly influence the spray drift in aerial applications; however, to date its effects remain unclear. In this study, a large spatiotemporal aerial application simulation model was constructed using different atmospheric boundary layer (ABL) stabilities. Three sets of ABL stability conditions were considered: unstable, stable, and neutral. Velocity, temperature, turbulence kinetic energy, and turbulence dissipation rate were set in detail as boundary conditions. The simulation results indicated that, using a simulation of the typical fixed-wing agricultural aircraft operating at typical altitudes and speeds, the upwind vortex decays more slowly than the downwind vortex, while the movement of the downwind vortex is also faster. The strength of the vortex was found to influence the droplet concentration. Droplets dispersed more quickly under unstable conditions probably because of the turbulent kinetic energy were greater. Droplets under stable conditions moved much rapidly downwind but drifted at lower altitudes than under unstable conditions. The diameter of most of the drift spray droplets was <100 mm. The simulation results indicated that off-target deposition in the stable case was greater than in the unstable case by nearly 300% around at downwind distances of 100 m, 180 m, 700 m, and ~200% at around 220 m and 550 m. Therefore, unstable atmospheric conditions, which are most likely to occur from 06:00 and 19:00 during a day appear to be a better choice for reducing drift losses. The simulation results are expected to help improve the comprehensive understanding of aerial application drift and to assist in choosing appropriate times and conditions to perform such operations.(c) 2022 IAgrE. Published by Elsevier Ltd. All rights reserved.
- 相关文献
作者其他论文 更多>>
-
Toward a remote sensing method based on commercial LiDAR sensors for the measurement of spray drift and potential drift reduction
作者:Li, Longlong;Zhang, Ruirui;Chen, Liping;Ding, Chenchen;Tang, Qing;Liu, Boqin;Li, Longlong;Zhang, Ruirui;Chen, Liping;Ding, Chenchen;Tang, Qing;Liu, Boqin;Hewitt, Andrew J.;He, Xiongkui
关键词:LiDAR; Point clouds; Spray drift; Drift reduction percentage; Nozzles; Sprayers
-
Design and experiments with a SLAM system for low-density canopy environments in greenhouses based on an improved Cartographer framework
作者:Tan, Haoran;Yang, Minli;Tan, Haoran;Zhao, Xueguan;Zhai, Changyuan;Fu, Hao;Chen, Liping;Zhao, Xueguan;Zhai, Changyuan;Chen, Liping;Zhao, Xueguan
关键词:mobile robot; lidar; simultaneous localization and mapping (SLAM); greenhouse; perception
-
Optimized Design of Robotic Arm for Tomato Branch Pruning in Greenhouses
作者:Ma, Yuhang;Chen, Liping;Feng, Qingchun;Sun, Yuhuan;Guo, Xin;Zhang, Wanhao;Wang, Bowen;Chen, Liping;Feng, Qingchun;Guo, Xin;Chen, Liping
关键词:agricultural robot; tomato pruning; manipulator; structural optimization
-
Research on Individual Tree Canopy Segmentation of Camellia oleifera Based on a UAV-LiDAR System
作者:Wang, Liwan;Zhang, Linhuan;Zhang, Ruirui;Zhang, Linhuan;Yi, Tongchuan;Zhang, Danzhu;Zhu, Aobin
关键词:Camellia oleifera; UAV; point cloud data; Canopy Height Models; parameter optimization
-
Navigation line extraction algorithm for corn spraying robot based on YOLOv8s-CornNet
作者:Guo, Peiliang;Diao, Zhihua;Ma, Shushuai;He, Zhendong;Zhao, Suna;Zhao, Chunjiang;Li, Jiangbo;Zhang, Ruirui;Yang, Ranbing;Zhang, Baohua
关键词:agricultural robotics; computer vision; deep learning; navigation line extraction; network lightweight
-
Multi-scale feature adaptive fusion model for real-time detection in complex citrus orchard environments
作者:Zhang, Yunfeng;Li, Li;Wen, Yifeng;Chun, Changpin;Li, Li;Xu, Gang
关键词:Lightweight; Multi -scale feature adaptive fusion module; Real-time detection; Complex environments; Citrus harvesting equipment
-
Determination of lead content in oilseed rape leaves in silicon-free and silicon environments based on deep transfer learning and fluorescence hyperspectral imaging
作者:Zhou, Xin;Zhao, Chunjiang;Sun, Jun;Cheng, Jiehong;Xu, Min;Zhao, Chunjiang;Zhao, Chunjiang
关键词:Stacked convolution auto-encoder; Deep transfer learning; Silicon environment; Lead; Nondestructive testing