{"title":"Computational fluid dynamics investigation of aerodynamics for agricultural drones","authors":"","doi":"10.1016/j.compag.2024.109528","DOIUrl":null,"url":null,"abstract":"<div><div>An extensive investigation of the aerodynamic characteristics of agricultural drones is important to improve the efficiency of agricultural production. In this study, a computational fluid dynamics (CFD) model that characterizes aerodynamics for agricultural drones was developed. The numerical simulations were performed to predict the lift force for an individual propeller and airflow fields for the drone. The CFD model was validated against the measured propeller lift force with respect to its rotating speed, and then eight turbulence models were examined to propose an appropriate one that would best predict the propeller lift force. Based on the simulation results, an analytical solution was derived to calculate the power consumption for the drone when hovering. Moreover, the flow fields for the agricultural drone were analyzed qualitatively and quantitatively, and the effect of crosswind speed on the propeller lift force was checked. The results demonstrate that the lift force and the power input of the propeller increase nonlinearly with the increase of propeller rotating speed, and obviously the power consumption to keep the drone hovering decreases while the total energy consumption increases during pesticide spraying.</div></div>","PeriodicalId":50627,"journal":{"name":"Computers and Electronics in Agriculture","volume":null,"pages":null},"PeriodicalIF":7.7000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Electronics in Agriculture","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168169924009190","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
An extensive investigation of the aerodynamic characteristics of agricultural drones is important to improve the efficiency of agricultural production. In this study, a computational fluid dynamics (CFD) model that characterizes aerodynamics for agricultural drones was developed. The numerical simulations were performed to predict the lift force for an individual propeller and airflow fields for the drone. The CFD model was validated against the measured propeller lift force with respect to its rotating speed, and then eight turbulence models were examined to propose an appropriate one that would best predict the propeller lift force. Based on the simulation results, an analytical solution was derived to calculate the power consumption for the drone when hovering. Moreover, the flow fields for the agricultural drone were analyzed qualitatively and quantitatively, and the effect of crosswind speed on the propeller lift force was checked. The results demonstrate that the lift force and the power input of the propeller increase nonlinearly with the increase of propeller rotating speed, and obviously the power consumption to keep the drone hovering decreases while the total energy consumption increases during pesticide spraying.
期刊介绍:
Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.