{"title":"Numerical modelling of a variable rate spraying drone and comparison to experimental evaluations","authors":"Fatemeh Joudi-Sarighayeh , Hossein Mousazadeh , Mohammad Hasan Sabet Dizavandi , Farzad Mohammadi , Foad Hassanlou , Niloofar Ghasemi , Zahra Hajalioghli , Alireza Tafteh","doi":"10.1016/j.atech.2025.101064","DOIUrl":null,"url":null,"abstract":"<div><div>Safe and organic food supplying with decreased cost are two main perspectives for future agriculture. Considering this concept, spraying drones are one of the prominent cutting-edge technologies. This study focuses on the evaluation of a variable rate sprayer drone configured as an X-type quadcopter. Nozzles controlling by PWM, enables for variable rate spraying in precision agriculture concept. Therefor main objective is evaluating various research parameters through experimental and simulation methodologies. Numerical simulations were conducted using X-Flow software, which employs Lattice Boltzmann Methods (LBM) to effectively model fluid behaviour within a specified computational domain. The experimental evaluation encompassed some tests on nozzle flow rates across different PWM frequencies and duty cycles. Besides, some assessments of spray patterns are performed in both static and dynamic scenarios. The results demonstrated that with a measured nozzle's spray angle about 30 degrees, the spraying system efficiently atomizes liquid into fine droplets, that will enhance drift potential. Field tests performed at altitudes of 1.5 m and 1.8 m illustrated the stability and sensitivity of the spraying system in an open environment. These findings underscore the significance of precise adjustments in operational parameters to optimize spraying efficiency. Future research should explore additional influential factors and conduct field experiments under a range of environmental conditions to validate simulation outcomes and enhance practical applications in agriculture.</div></div>","PeriodicalId":74813,"journal":{"name":"Smart agricultural technology","volume":"12 ","pages":"Article 101064"},"PeriodicalIF":5.7000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart agricultural technology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772375525002977","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
Safe and organic food supplying with decreased cost are two main perspectives for future agriculture. Considering this concept, spraying drones are one of the prominent cutting-edge technologies. This study focuses on the evaluation of a variable rate sprayer drone configured as an X-type quadcopter. Nozzles controlling by PWM, enables for variable rate spraying in precision agriculture concept. Therefor main objective is evaluating various research parameters through experimental and simulation methodologies. Numerical simulations were conducted using X-Flow software, which employs Lattice Boltzmann Methods (LBM) to effectively model fluid behaviour within a specified computational domain. The experimental evaluation encompassed some tests on nozzle flow rates across different PWM frequencies and duty cycles. Besides, some assessments of spray patterns are performed in both static and dynamic scenarios. The results demonstrated that with a measured nozzle's spray angle about 30 degrees, the spraying system efficiently atomizes liquid into fine droplets, that will enhance drift potential. Field tests performed at altitudes of 1.5 m and 1.8 m illustrated the stability and sensitivity of the spraying system in an open environment. These findings underscore the significance of precise adjustments in operational parameters to optimize spraying efficiency. Future research should explore additional influential factors and conduct field experiments under a range of environmental conditions to validate simulation outcomes and enhance practical applications in agriculture.