CFD Modeling and Experiment of Airflow at the Air Outlet of Orchard Air-Assisted Sprayer

doi:10.12133/j.smartag.2021.3.3.202106-SA007

Abstract

Abstract:

The tower-type sprayer produces swirling and irregular vertical airstream. The complex swirling results in airflow asymmetry between sides of the sprayer, and the vertical air velocity profile can be unpredictable when the rotational speed of the fan changes. The spray deposition is directly linked to the airflow pattern obtained from the sprayers. In order to study airflow field of this type of air-assisted sprayer, a CFD (Computational Fluid Dynamics) model for the tower-type sprayer was developed. A boundary condition setting method of UDF (User-Defined Function) sectional 3D air velocity was proposed. And the influences of turbulence models and the size of computational domain on CFD airflow simulation were studied. Using Fluent software, three different CFD models were established. The Model 1 took the average air velocity of 11 regions as the velocity inlet. The Model 2 used UDF segmented three-dimension air velocity line as the boundary condition. In order to further study the influence of the computational domain size on simulation, the Model 3 with a smaller computational domain was established. The turbulence model based on reynolds-averaged navier-stokes (RANS) control equation was used to calculate the airflow field in all models. In order to verify the reliability of the model, a three-dimensional measurement system of airflow field was designed, which was used for accurate and fast velocity measurement. The results showed that the Standard k-ε turbulence model, Realizable k-ε turbulence model, BSL k-w turbulence model, SST k-w turbulence model were suitable, and the Standard k-ε turbulence model was the best one. The CFD boundary condition setting method of UDF sectional three-dimension air velocity could improve the accuracy of simulation, and reduce the calculation complexity. With the same settings of other parameters, the performance of the CFD model with larger scale calculation domain was slightly better than that with smaller computational domain. The size of computational domain should be set to the appropriate extent, considering the calculation capacity and practical requirements of modelling. The research results could provide an important reference for CFD modeling of spray airflow field.

Key words: CFD, boundary condition, UDF, turbulence model, computational domain

CLC Number:

S224.3

ZHAI Changyuan, ZHANG Yanni, DOU Hanjie, WANG Xiu, CHEN Liping. CFD Modeling and Experiment of Airflow at the Air Outlet of Orchard Air-Assisted Sprayer[J]. Smart Agriculture, 2021, 3(3): 70-81.

References

1	袁会珠, 杨代斌, 闫晓静, 等. 农药有效利用率与喷雾技术优化[J]. 植物保护, 2011, 37(5): 14-20.
1	YUAN H, YANG D, YAN X, et al. Pesticide effective utilization rate and spray technology optimization[J]. Plant Protection, 2011, 37(5): 14-20.
2	何雄奎. 中国精准施药技术和装备研究现状及发展建议[J]. 智慧农业(中英文), 2020, 2(1): 133-146.
2	HE X. Research progress and developmental recommendations on precision spraying technology and equipment in China[J]. Smart Agriculture, 2020, 2(1): 133-146.
3	翟长远, 赵春江, WANG N, 等. 果园风送喷雾精准控制方法研究进展[J]. 农业工程学报, 2018, 34(10): 1-15.
3	ZHAI C, ZHAO C, WANG N, et al. Research progress on precision control methods of air-assisted spraying in orchards[J]. Transactions of the CSAE, 2018, 34(10): 1-15.
4	MIRANDA-FUENTES A, RODRIGUEZ-LIZANA A, GIL E, et al. Influence of liquid-volume and airflow rates on spray application quality and homogeneity in super-intensive olive tree canopies[J]. Science of the Total Environment, 2015. 537: 250-259.
5	LIAO J, LUO X, WANG P, et al. Analysis of the influence of different parameters on droplet characteristics and droplet size classification categories for air induction nozzle[J]. Agronomy, 2020, 10(2): ID 256.
6	YANG F, XUE X, CAI C, et al. Numerical simulation and analysis on spray drift movement of multirotor plant protection unmanned aerial vehicle[J]. Energies, 2018, 11(9): ID 2399.
7	LANDERS A J. Developments towards an automatic precision sprayer for fruit crop canopies[C]// Pittsburgh, Pennsylvania. Michigan, USA: American Society of Agricultural and Biological Engineers, 2010.
8	李龙龙, 何雄奎, 宋坚利, 等. 基于变量喷雾的果园自动仿形喷雾机的设计与试验. 农业工程学报, 2017, 33(1): 70-76.
8	LI L, HE X, SONG J, et al. Design and experiment of orchard automatic profiling sprayer based on variable spray[J]. Transactions of the CSAE, 2017, 33(1): 70-76.
9	QIU W, ZHAO S, DING W, et al. Effects of fan speed on spray deposition and for targeting air-assisted sprayer in pear orchard[J]. International Journal of Agricultural and Biological Engineering, 2016, 9(4): 53-62.
10	OSTERMAN A, GODESA T, HOCEVAR M, et al. Real-Time positioning algorithm for variable-geometry air-assisted orchard sprayer[J]. Computers and Electronics in Agriculture, 2013, 98: 175-182.
11	GU J, ZHU H, DING W. Unimpeded air velocity profiles of an air-assisted five-port sprayer[J]. Transactions of the ASABE, 2012, 55(5): 1659-1666.
12	SALCEDO R, PONS P, LLOP J, et al. Dynamic evaluation of airflow stream generated by a reverse system of an axial fan sprayer using 3D-ultrasonic anemometers. Effect of canopy structure[J]. Computers and Electronics in Agriculture, 2019, 163: 1-14.
13	陈建泽, 宋淑然, 孙道宗, 等. 远射程风送式喷雾机气流场分布及喷雾特性试验. 农业工程学报, 2017, 33(24): 72-79.
13	CHEN J, SONG S, SUN D, et al. Experiment on the distribution and spray characteristics of the air flow field of the long range air feed sprayer[J]. Transactions of the CSAE, 2017, 33 (24): 72-79
14	HOLOWNICKI R, DORUCHOWSKI G, SWIECH- OWSKI W, et al. Variable air assistance system for orchard sprayers; concept, design and preliminary testing[J]. Biosystems Engineering, 2017, 163: 134-149.
15	DUGA A T, RUYSEN K, DEKEYSER D, et al. CFD based analysis of the effect of wind in orchard spraying[J]. Chemical Engineering Transactions, 2015, 44(2015): 289-294.
16	HONG S W, ZHAO L, ZHU H. SAAS, a computer program for estimating pesticide spray efficiency and drift of air-assisted pesticide applications[J]. Computers and Electronics in Agriculture, 2018, 155: 58-68.
17	BAHLOL H Y, CHANDEL A K, HOHEISEL G A, et al. The smart spray analytical system: Developing understanding of output air-assist and spray patterns from orchard sprayers[J]. Crop Protection, 2020, 127: ID 104977.
18	王景旭, 祁力钧, 夏前锦. 靶标周围流场对风送喷雾雾滴沉积影响的CFD模拟及验证[J]. 农业工程学报, 2015, 31(11): 46-53.
18	WANG J, QI L, XIA Q. CFD simulation and validation of trajectory and deposition behavior of droplets around target affected by air flow field in greenhouse[J]. Transactions of the CSAE, 2015, 31(11): 46 -53.
19	SALCEDO R, VALLET A, GRANELL R, et al. Eulerian－Lagrangian model of the behaviour of droplets produced by an air-assisted sprayer in a citrus orchard[J]. Biosystems Engineering, 2017: 76-91.
20	HONG S W, ZHAO L, ZHU H. CFD simulation of pesticide spray from air-assisted sprayers in an apple orchard: Tree deposition and off-target losses[J]. Atmospheric Environment, 2018, 175: 109-119.
21	ATAM E, HONG S W, ARTECONI A. Thermofluid modelling of large-scale orchards for optimal design and control of active frost prevention systems[J]. Energies, 2020, 13(2): 378.
22	SALCEDO R, GRANELL R, PALAU G, et al. Design and validation of a 2D CFD model of the airflow produced by an airblast sprayer during pesticide treatments of citrus[J]. Computers and Electronics in Agriculture, 2015, 116: 150-161.
23	DEKEYSER D, DUGA A T, VERBOVEN P, et al. Assessment of orchard sprayers using laboratory experiments and computational fluid dynamics modeling[J]. Biosystems Engineering, 2013, 114: 157-169.
24	ENDALEW A M, HERTOG M, GEBREHIWOT M G, et al. Modelling airflow within model plant canopies using an integrated approach[J]. Computers and Electronics in Agriculture, 2009, 66(1): 9-24.
25	ENDALEW A M, DEBAER C, RUTTEN N, et al. A new integrated CFD modelling approach towards air-assisted orchard spraying—Part II: Validation for different sprayer types[J]. Computers and Electronics in Agriculture, 2010, 71(2): 137-147.
26	DUGA A T, DELELE M A, RUYSEN K, et al. Development and validation of a 3D CFD model of drift and its application to air-assisted orchard sprayers[J]. Biosystems Engineering, 2016, 154: 62-75.
27	GARCIA-RAMOS F J, MALON H, AGUIRRE A, et al. Validation of a CFD model by using 3D sonic anemometers to analyze the air velocity generated by an air-assisted sprayer equipped with two axial fans[J]. Sensors, 2015, 15(2): 2399-2418.
28	HONG S W, ZHAO L, ZHU H. CFD simulation of airflow inside tree canopies discharged from air-assisted sprayers[J]. Computers and Electronics in Agriculture, 2017, 149: 121-132.
29	BADULES J, VIDAL M, BONE A, et al. Comparative study of CFD models of the air flow produced by an air-assisted sprayer adapted to the crop geometry[J]. Computers and Electronics in Agriculture, 2018, 149: 166-174.
30	王福军. 计算流体动力学分析, CFD软件原理与应用[M]. 北京: 清华大学出版社, 2004.
30	WANG F. Computational fluid dynamics analysis, principle and application of CFD software[M]. Beijing: Tsinghua University Press, 2004.
31	YANG Y, TSE K T, JIN X, et al. A numerical tree canopy model and its application in computational wind engineering simulation[C]// The 7th International Colloquium on Bluff Body Aerodynamics & Applications. Amsterdam, Netherlands: Elsevier, 2012: 1429-1436.
32	MENTER F R. Two-equation eddy-viscosity turbulence models for engineering applications[J]. AIAA Journal, 1994: 1598-1605.
33	SALCEDO R, GRANELL R, PALAU G, et al. Design and validation of a 2D CFD model of the airflow produced by an airblast sprayer during pesticide treatments of citrus[J]. Computers and Electronics in Agriculture, 2015, 116: 150-161.
34	BADULES J, VIDAL M, BONE A, et al. Comparative study of CFD models of the air flow produced by an air-assisted sprayer adapted to the crop geometry[J]. Computers and Electronics in Agriculture, 2018, 149: 166-174.