Nozzle with a Feedback Channel for Agricultural Drones

applied sciences

Article Nozzle with a Feedback Channel for Agricultural Drones

Seong Kuen Kim, Hibal Ahmad, Jong Woon Moon and Sung Yong Jung *

Department of Mechanical Engineering, Chosun University, Gwangju 61452, Korea; [email protected] (S.K.K.); [email protected] (H.A.); [email protected] (J.W.M.) * Correspondence: [email protected]; Tel.: +82-62-230-7051; Fax: +82-62-230-7055

Abstract: In recent years, small drones have been used in agriculture, for spraying water and pesticides. Although spraying systems affect the efficiency of agricultural drones considerably, research on the spraying system of drones is insufficient. In this paper, a new nozzle with a feedback channel is proposed for agricultural drones. The proposed nozzle was manufactured through 3D printing, and its performance was compared with that of the nozzle used in commercial agricultural drones. Images taken with a high-speed camera were digitally processed, to track the area and location of spray particles, and the spraying characteristics were evaluated based on the size and uniformity of the droplets obtained from the images. The proposed nozzle provided a better performance, as it could spray smaller droplets more uniformly. Commercial nozzle droplets have an average diameter of 1.76 mm, and the proposed nozzle has been reduced to a maximum of 215 µm. In addition, the full width at half maximum (FWHM) of the commercial nozzle is 0.233, but the proposed nozzle is up to 1.519; the proposed nozzle provided better performance, as it could spray smaller droplets more uniformly. Under the condition of 30 kg, the best performance in the proposed nozzle, the minimum value of the average droplet diameter of the nozzle without feedback channel is 595 µm and the maximum value of FWHM is 1.329. Therefore, a comparison of the performance of the proposed nozzle with that of a nozzle with no feedback channel indicates that the feedback channel effectively Citation: Kim, S.K.; Ahmad, H.; reduces the droplet diameter and improves the spraying uniformity. It is expected that the proposed Moon, J.W.; Jung, S.Y. Nozzle with a nozzle can be useful for designing the spraying systems of agricultural drones. Feedback Channel for Agricultural Drones. Appl. Sci. 2021, 11, 2138. Keywords: feedback channel nozzle; agricultural drone; flow visualization; spraying uniformity https://doi.org/10.3390/app11052138

Academic Editors: Alberto Boschetto and Paolo Renna 1. Introduction Drones are unmanned aerial vehicles, ranging from large ones that can fly thousands Received: 6 January 2021 Accepted: 24 February 2021 of kilometers to small ones that can fly in limited spaces [1]. Early drones were developed Published: 28 February 2021 for military purposes and to aid search and rescue operations, but drones have since been developed for various civilian purposes, such as transportation and fire suppression [2]. In

Publisher’s Note: MDPI stays neutral 2014, the global market size of drones reached 700 million USD, and it is expected to grow with regard to jurisdictional claims in to approximately 1.7 billion USD by 2025 [3]. Most studies on drones have focused on published maps and institutional afﬁl- improving the ﬂight time for practical commercial applications. Gattie et al. [4,5] estimated iations. the weight of the drone and number of rotors depending on the maximum power demand of the battery and made suggestions regarding the propellers and some performance requirements underlying the design. In addition, an aerodynamic analysis method that improves durability by maintaining the balance is proposed. Abdilla et al. [6] presented a

Copyright: © 2021 by the authors. capacity model for the lithium-polymer batteries used in commercial quad-rotors, resulting Licensee MDPI, Basel, Switzerland. in maximum durability at the optimum mass value and an excellent propulsion system. This article is an open access article Drones are also employed in agricultural ﬁelds, because the aerial spraying technol- distributed under the terms and ogy reduces labor costs and removes the risk of physical damage to the crops and soil conditions of the Creative Commons from the wheels or tracks of a machine. In addition to improving the durability of the Attribution (CC BY) license (https:// battery life and propulsion, Primicerio et al. [7] developed an agricultural drone that can creativecommons.org/licenses/by/ generate management maps of vineyards through multispectral image analysis for ease of 4.0/).

Appl. Sci. 2021, 11, 2138. https://doi.org/10.3390/app11052138 https://www.mdpi.com/journal/applsci Appl. Sci. 2021, 11, 2138 2 of 14

navigation. To improve the practical applications of agricultural drones in spraying water and pesticides, it is necessary to investigate the spraying system further. Edward [8] developed electrostatic spraying machines and presented system specifi- cations to increase the effectiveness of the deposition of pesticides, and experimentally ver- ified the possibility of spraying a volume median diameter of 50 µm. Rockwell et al. [9] developed a variable speed direct spraying nozzle for uniform spraying. Murtadha et al. [10] conducted experiments and COMSOL software simulations of spraying water on targets with different shapes to establish a direct relationship between water flow and current in electrostatic spraying methods. Sharda et al. [11] proposed a local automatic selectivity control nozzle that can accurately control the amount of pesticide to reduce environmental pollution, while reducing the costs. However, these studies on optimizing the spraying system are only applicable to ground spraying systems. Aerial spraying technology was first used in large manned aircraft to combat pests in early 1906. Later, in 1975, electrostatic spraying technology was applied to medium-sized aircraft [12–14]. Xue et al. [15] developed precision technologies that can adjust the spraying rate, such as variable-speed spraying technology and positioning technology. In 1990, the first unmanned aerial spraying technology was employed in the agricultural sector [16,17]. Most of the previous aerial spraying techniques had been applied to medium-sized unmanned aerial vehicles. However, recently, compact-sized small drones have received significant attention in the field of aerial spraying technology, owing to their high maneu- verability. Even though different companies develop agricultural drones, the spraying system generally consists of a commercial pump and nozzle. In recent years, research has also been conducted to select suitable nozzles and pumps for use in agricultural drones. Yu et al. [18] evaluated the performance of three types of pumps and 18 types of nozzles currently in use, by using a pressure-flow curve, injection flow rate, injection angle, and droplet size. Chen et al. [19] compared the performance by selecting three nozzles, to ex- tend the flight time of agricultural drones by reducing the amount of pesticide spraying per unit area. However, these studies have been limited to evaluating the nozzle performance, and research on the spray system is insufficient. Therefore, further research into spraying systems for agricultural drones is needed [20,21]. The spraying performance of agricultural drones can be evaluated through various factors, such as the effective spray width, spray uniformity, droplet size, spray droplet adhesion rate, and scattering characteristics. However, research on existing agricultural drones focuses mainly on improving the effective spray width. In addition to the spaying width, the important issue in agricultural spraying is to maintain an even liquid distribution and to avoid the drift of the droplets. Especially, drifting is an important and costly problem because it requires additional air flows in some applications. It is well-known that this drift problem depends on the droplet size. The droplet size also affects the penetration performance of the spray into the crops. Therefore, in this study, we developed a nozzle with a feedback channel for the spraying system of agricultural drones that can improve the effective spray width, droplet size, and spray uniformity.

2. Proposed Design of Agricultural Drone Nozzle The fluidic oscillator can also be found in previous studies, and a number of visualization studies have been conducted to find out the flow characteristics of fluid vibrators. In this study, a new nozzle was designed, using the flow characteristics of a fluid vibra- tor [22–25]. A nozzle with a feedback channel generates an oscillating jet flow through the interaction of the feedback block and the chamber with the inner block, without additional external equipment. This oscillation can generate a uniform spraying, compared to a conventional nozzle. When fluid is supplied into the feedback channel, a Coanda effect occurs in which the airflow ejected in close proximity to a wall of the feedback chamber adheres to the wall. The nozzle with a feedback channel uses this effect to generate a cross-flow through the feedback flow path inside the nozzle, thereby causing the fluid to vibrate at the outlet. Appl. Sci. 2021, 11, x FOR PEER REVIEW 3 of 15 Appl. Sci. 2021, 11, x FOR PEER REVIEW 3 of 15

Appl. Sci. 2021, 11, 2138 through the feedback flow path inside the nozzle, thereby causing the fluid to vibrate at3 of 14 the outlet.through the feedback flow path inside the nozzle, thereby causing the fluid to vibrate at theFan-shaped outlet. commercial nozzles are generally used in agricultural drones, owing to Fan-shaped commercial nozzles are generally used in agricultural drones, owing to their wide spray width, but the nozzles provide low uniformity. To overcome this prob- their wideFan-shaped spray width, commercial but the nozzles nozzles areprov generallyide low uniformity. used in agricultural To overcome drones, this owing prob- to lem, we tried to improve the spraying uniformity of agricultural drones by the oscillating lem,their we wide tried spray to improve width, butthe spraying the nozzles uniformity provide lowof agricultural uniformity. drones To overcome by the oscillating this problem, characteristic of the nozzle with a feedback channel. Figure 1 shows the expected spraying characteristicwe tried to improveof the nozzle the with spraying a feedback uniformity channel. of Figure agricultural 1 shows drones the expected by the spraying oscillating distributions with the conventional and the feedback channel nozzles. Figure 2 shows the distributionscharacteristic with of the the nozzle conventional with a feedbackand the feedback channel. channel Figure1 nozzles.shows the Figure expected 2 shows spraying the proposed design for an agricultural drone nozzle that can generate periodic oscillation proposeddistributions design with for the an conventionalagricultural drone and the nozzle feedback that channelcan generate nozzles. periodic Figure oscillation2 shows the and improve the spraying uniformity. In general, fluid oscillation effectively occurs when andproposed improve design the spraying for an agriculturaluniformity. In drone general, nozzle fluid that oscillation can generate effectively periodic occurs oscillation when a fluid is discharged into a space filled with the same phase fluid. By contrast, when a a andfluid improve is discharged the spraying into a uniformity.space filled Inwith general, the same fluid phase oscillation fluid. effectivelyBy contrast, occurs when when a fluid is ejected on to a different phase, the oscillation is reduced, and the formation of fluida fluid is ejected is discharged on to a intodifferent a space phase, filled the with oscillation the same is phasereduced, fluid. and By the contrast, formation when of a atomized droplets becomes difficult. Therefore, in this study, in contrast to a conventional atomizedfluid is ejecteddroplets on becomes to a different difficult. phase, Therefore, the oscillation in this study, is reduced, in contrast and to a the conventional formation of feedback channel nozzle, a certain amount of air is injected through the main inlet, and feedbackatomized channel droplets nozzle, becomes a certain difficult. amount Therefore, of air inis thisinjected study, through in contrast the main to a conventionalinlet, and waterwaterfeedback is introduced is introduced channel through nozzle,through an a additionalan certain additional amount channe channe ofl installed airl installed is injected at theat the throughoutlet outlet neck. theneck. mainThe The sizeinlet, size of of and the feedbackthewater feedback is introducedchannel channel nozzle throughnozzle was was an70 additionalmm70 mm in lengin leng channelth andth and 30 installed 30mm mm in atinwidth thewidth outlet for for application neck.application The to size to of smallsmallthe agricultural feedback agricultural channeldrones, drones, the nozzle theoutlet outlet was height 70 height mm was inwas 10 length 10mm, mm, andand and 30the mmthe nozzle nozzle in width height height for was applicationwas 2 mm.2 mm. to TheThe proposedsmall proposed agricultural nozzle nozzle was drones, was built, built, theusing outletusing digital digital height light light was processing 10processing mm, and 3D 3D theprinting printing nozzle to heighttoevaluate evaluate was the 2the mm. sprayingsprayingThe proposedperformance. performance. nozzle was built, using digital light processing 3D printing to evaluate the spraying performance.

(a) (a) (b)( b)

FigureFigureFigure 1. Expected 1. 1. ExpectedExpected trajectory trajectory trajectory of spray of ofspray sprayfor for(a) for commercial(a) ( acommercial) commercial nozzle nozzle nozzle and and (b and) ( developedb) ( bdeveloped) developed nozzle. nozzle. nozzle.

Figure 2. Structure of the proposed nozzle. FigureFigure 2. Structure 2. Structure of the of proposedthe proposed nozzle. nozzle. 3. Experiment Methods 3. Experiment3.3.1. Experiment Spraying Methods PerformanceMethods The spraying performance of an agricultural drone was evaluated, using parameters 3.1. Spraying Performance 3.1. Sprayingsuch as sprayingPerformance uniformity, droplet size and speed, adhesion rate of spray particles, and ThescatteringThe spraying spraying characteristics. performance performance Theof an of selected agriculturan agricultur variablesal droneal drone depend was was evaluated, onevaluated, the objective using using parameters andparameters evaluator. such as spraying uniformity, droplet size and speed, adhesion rate of spray particles, and such Theas spraying Korean uniformity, government droplet uses spraying size and uniformityspeed, adhesion as a criterionrate of spray for agriculturalparticles, and drone certiﬁcation [21]. Therefore, in this study, the spraying performance of the proposed and conventional drone types was compared, based on the spraying uniformity and droplet size. These parameters can evaluate the sole effect of the nozzle design on the spray performance without the inﬂuence of external factors, such as wind and temperature. Appl. Sci. 2021, 11, 2138 4 of 14

Actually, the spray uniformity in the agricultural drone certiﬁcation means that the width has effective spraying amount within the maximum spraying width from one point. This effective width can be used to decide the distance between the cross-ﬂights of the agricultural drone. The full width at half maximum (FWHM) is a value that represents the width of a curve between points on half of the maximum value and is used to indicate the size of the function for spaying distributions. In this study, FWHM was used to calculate the spraying width, and the spraying uniformity was compared in terms of the spraying amount and droplet size according to the radial position.

3.2. Tested Nozzles The spraying performance of the proposed nozzle was compared with that of two other nozzles. The first was a fan-shaped commercial nozzle (TEEJET XR11002, Spray Systems), which is currently employed in commercial agricultural drones. The other was a nozzle without a feedback channel to confirm the feedback channel effect on the designed nozzle. Except for the feedback channel, the other physical dimensions were the same as those of the proposed nozzle. The flow rate for the nozzle test was determined at 500 mL/min, which was similar to the condition in real-world applications.

3.3. Measurement of Spraying Performance Figure3 shows a schematic diagram of the experimental setup used to measure the spraying performance. The main flow was injected by using an air pump (Wob-L Piston Gas Pump WA80DC, YLKTECH), and the supply of water through the additional channel was controlled through hydrostatic pressure. After generating a main flow of 8.1 L/min at the main inlet by using an air pump, spraying was performed by applying hydrostatic pressure. For changing the hydrostatic pressure, a weight was added to the upper part of the water piston, and the spraying performance was confirmed by changing the weight from 0 to 50 kg, in 10 kg increments. The static pressure was measured at the point Appl. Sci. 2021, 11, x FOR PEER REVIEWindicated in Figure3. The pressure and flow rates corresponding to different loads on5 of the 15 water piston are summarized in Figure4. Without load, the pressure and flow rates were 0.05 bar and 50 mL/min, respectively. The pressure and flow rates are found to increase with increasing loads. The rate of change is found to increase further for loads heavier than correction30 kg. When during the loadimage was processing; higher than however, 30 kg, asalmost the load particles increased, were bothinvolved the pressure in the depth and offlow field rate of increased.imaging.

FigureFigure 3. 3. SchematicSchematic of of the the experimental experimental setup setup for for measuring measuring the the spraying spraying performance.

Figure 4. Variations of flow rate and pressure with various loads.

3.4. Measurement of Spraying Performance Figure 5 shows the image-processing procedure. The processed images were obtained by sequentially performing threshold correction and noise reduction on the original image, using Image J software. The particle-tracking function in Image J software was employed with the processed images for extracting spraying droplet information, including position and size. In order to check the reliability of the procedure for automatic obtaining the droplet size, we compared the value with a manual calculation for 100 droplets. The measurement accuracy in the size was about 5.3%. Figure 6 shows representative processed images for the newly proposed nozzle obtained at locations 1 and 2. For statistical analysis, spraying images were captured for 1 s, and the final droplet information was summed and averaged. From the droplet information, the spraying performances were compared by calculating various parameters, such as FWHM and droplet distributions, with respect to the radial position.

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correction during image processing; however, almost particles were involved in the depth of field of imaging.

Appl. Sci. 2021, 11, 2138 5 of 14 Figure 3. Schematic of the experimental setup for measuring the spraying performance.

Figure 4. Variations of flow rate and pressure with various loads. Figure 4. Variations of flow rate and pressure with various loads. The images of spraying particles were captured at 2000 frames per second, with a 3.4.high-speed Measurement camera of (Fastcam Spraying Mini Performance UX50, Photron, San Diego, CA, USA). The obtained images were analyzed, using a digital image-processing technique. The origin was set at the centerFigure of the5 shows nozzle exitthe in image-processing the analysis, and the procx-axisedure. and z-axis The represent processed the radial images were ob- tainedand spraying by sequentially directions, respectively.performing As threshol shown ind Figurecorrection3, to confirm and noise the distribution reduction on the origi- nalof particlesimage, overusing a wideImage range, J software. spraying waterThe particle-tracking droplets were visualized function in four in areasImage and J software was employedphotographed with by the moving processed the camera images±50 mm for in extracting the x-axis and spraying 50 mm indroplet the z-axis. information, includ- The spray shape maintained a shape close to that of a curtain because the nozzle had ing position and size. In order to check the reliability of the procedure for automatic ob- a flat exit. In addition, the commercial nozzle used in this study was a fan-shaped nozzle taininghaving athe curtain-type droplet size, spaying wedistribution. compared Therefore,the value2D with measurement a manual was calculation sufficient for 100 droplets.to compare The measurement the results in accuracy terms of uniformity, in the size because was about the spraying 5.3%. Figure thickness 6 shows is small representative processedenough to involveimages the for depth the newly of field ofproposed imaging; however,nozzle obtained the spraying at locations distribution 1 hadand 2. For statis- ticala thickness analysis, in depth spraying because images the thickness were iscaptured small enough for 1 to s, involve and the the depthfinal droplet of field information of imaging. Several blurred droplets, due to being out of focus, were removed by the wasthreshold summed correction and duringaveraged. image From processing; the however,droplet almostinformation, particles werethe spraying involved in performances werethe depth compared of field ofby imaging. calculating various parameters, such as FWHM and droplet distributions, with respect to the radial position. 3.4. Measurement of Spraying Performance

Figure5 shows the image-processing procedure. The processed images were obtained by sequentially performing threshold correction and noise reduction on the original image, using Image J software. The particle-tracking function in Image J software was employed with the processed images for extracting spraying droplet information, including position and size. In order to check the reliability of the procedure for automatic obtaining the droplet size, we compared the value with a manual calculation for 100 droplets. The measurement accuracy in the size was about 5.3%. Figure6 shows representative processed images for the newly proposed nozzle obtained at locations 1 and 2. For statistical analysis, spraying images were captured for 1 s, and the ﬁnal droplet information was summed and averaged. From the droplet information, the spraying performances were compared by calculating various parameters, such as FWHM and droplet distributions, with respect to the radial position. Appl. Sci. 2021, 11, x FOR PEER REVIEW 6 of 15

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(a) (b) (a) (b)

(c) (d) (c) (d) Figure 5. Image processing procedure. (a) Original image, (b) threshold correction, (c) noise reduc- Figure 5. Image tion,processingFigure and 5. (Imaged procedure.) particle processing tracking. (a) Original procedure. image, (a) Original (b) threshold image, correction, (b) threshold (c) correction,noise reduc- (c) noise reduction, tion, and (d) particleand (tracking.d) particle tracking.

(a) (a) Figure 6. Cont. Appl. Sci. 2021, 11, 2138 7 of 14 Appl. Sci. 2021, 11, x FOR PEER REVIEW 7 of 15

(b)

FigureFigure 6. Representative 6. Representative images images obtain obtaineded at the at location the location of (a) of 1 (anda) 1 ( andb) 2 (forb) 2different for different weights. weights.

4. Result 4. Result 4.1. Spraying Distributions 4.1. Spraying Distributions The spatial distributions of the spraying area, the average planar area covered by the The spatial distributionsliquid phase, of were the spraying obtained area, by dividing the average the image, planar in area order covered to sub-analyzing by the the windows liquid phase, werehaving obtained a size by dividing of 64 by 64the pixels. image, The in order spaying to sub-analyzing area values were the windows obtained by summing the having a size of 64area by of64 thepixels. droplets The spayin inside theg area sub-analyzing values were windows. obtained Theby summing final spatial the distributions were area of the dropletsevaluated inside the and sub-analyzing converted to windows. contour plotThe final at each spatial sub-window, distributions by averagingwere values from evaluated and converted2000 images. to contour plot at each sub-window, by averaging values from 2000 images. Figure7 compares the contours of the spraying distributions. The contours of the Figure 7 comparesspraying the area contours at location of the 1, inspra Figureying3 ,distributions. are represented The in Figurecontours8, for of athe clearer comparison spraying area at locationof spraying 1, in distributions.Figure 3, are represented Large amounts in Figure of droplets 8, for are a clearer ejected compari- along the centerline of the son of spraying distributions.nozzle in all Large cases, amounts and thedroplet of droplets amount are ejected decreases along with the increasing centerline distance from the of the nozzle in allnozzle cases, tip.and Inthe addition, droplet amou for thent quantitativedecreases with comparison, increasing thedistance line profilefrom of the spraying the nozzle tip. In addition,amount forfor eachthe quantitative load at z = comparison, 5 is shown in the Figure line profile9. Figure of 9the is spraying the sum of the spraying amount for each loadamount at zfor = 5 1 is s atshown the z in = 5Figure position, 9. Figure and we 9 canis the see sum that of the the spraying spraying width increases as amount for 1 s at thethe loadz = 5 increases.position, and In the we commercial can see that nozzle, the spraying the sprayed width water increases is concentrated as near the the load increases.nozzle In thetip, commercial but the developed nozzle, the nozzle sprayed has water distinct is concentrated values farther near from thethe nozzle tip, as nozzle tip, but thewell. developed In order nozzle to compare has distinct the spaying values amount farther in from terms the of nozzle mass flow tip, rates,as the mass flow well. In order to comparerates were the obtained spaying byamount calculating in terms the of volume mass flow of the rates, entire the droplet mass flow sprayed for 1 s, with rates were obtainedan by assumption calculating of the spherical volume droplets. of the entire The comparison droplet sprayed of corresponding for 1 s, with mass flow rates is an assumption of representedspherical droplets. in Figure The 10 comp. Asarison represented of corresponding in Figures9 massand 10 flow, both rates the is spraying amount represented in Figureand effective10. As represented spraying angle in Figures increased 9 and as the10, loadboth increased. the spraying This amount means that the proposed and effective sprayingnozzle angle with incr a highereased as load the makes load increased. it easier to This make means a uniform that the spray. proposed nozzle with a higher load makes it easier to make a uniform spray.

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(a)

(b) (c)

(d) (e)

Figure 7. Contours of spraying area for (a) commercial and (b–e) proposed nozzle with a load of (b) 0 kg, (c) 30 kg, (d) 40 kg, and (e) 50 kg. Figure 7. Contours of spraying area for (a) commercial and (b–e) proposed nozzle with a load of (b4.2.) 0 kg, Droplet (c) 30 Sizekg, (d) 40 kg, and (e) 50 kg. The distribution of the average droplet size for 1 s in the radial position from the center of the nozzle is shown in Figure 11a. In all cases, the larger droplets are observed at the center of the nozzles. Compared with the proposed nozzle, the commercial nozzle has a sharp peak distribution. The droplet size in the commercial nozzle was reduced to 10% at x/D = 1.5. The proposed nozzle has a much smaller droplet size than the commercial nozzle, and the size gradually decreases as the radial position increases. These distributions show that the proposed nozzle can produce a more uniform droplet size over a wider range than commercial nozzles. Appl. Sci. 2021, 11, x FOR PEER REVIEW 9 of 15 Appl. Sci. 2021, 11, 2138 9 of 14

(a) (b)

Figure 8. Contour of spraying area at the measured location of 1 in Figure3 for the developed nozzle with a load of (a) 0 kg, (b) 30 kg, (c) 40 kg, and (d) 50 kg. Figure 8. Contour of spraying area at the measured location of 1 in Figure 3 for the developed nozzle with a load of (a) 0 kg, (b) 30 kg, (c) 40 kg, and (d) 50 kg.

Figure 9. Line profile of spraying amount of the developed nozzle at z = 5.

Figure 9. Line proﬁle of spraying amount of the developed nozzle at z = 5.

Figure 11b shows the averaged diameter of whole measured droplets that was obtained from each of the droplet area values, with an assumption of spherical particles. The draft potential is the one of the criterion for the nozzle selection. Although the draft is related with many factors such as droplet size, surrounding wind, drone propeller speed, and height of spraying drone operation, the droplet size is the most important for that. Typi- cally, commercial nozzles in agricultural applications have a diameter range of 300–500 µm, and some operate between 400 and 700 µm. In addition, Lee et al. [26] reported that a good Appl. Sci. 2021, 11, 2138 10 of 14

spray effect can be obtained when the diameter of the spray particles is in the range of 150 to 440 µm, and the suitable diameter is 250 to 500 µm, to avoid scattering. The commercial nozzle had a droplet size of 1.70 mm exceeding the suitable range for the sprayer. However, the feedback channel nozzle has a droplet size of 226 µm for a 30 kg load suitable for agricultural applications. For load conditions of 40 and 50 kg, the diameters are 265 and Appl. Sci. 2021, 11, x FOR PEER REVIEW 10 of 15 280 µm, respectively, sufﬁcient to prevent scattering. The reduction in droplet size indicates that the proposed nozzle can improve the performance of agricultural drones.

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FigureFigure 10. 10. ComparisonComparison of of mass mass flow ﬂow rates with an assumption of spherical droplets.

4.2. Droplet Size The distribution of the average droplet size for 1 s in the radial position from the center of the nozzle is shown in Figure 11a. In all cases, the larger droplets are observed at the center of the nozzles. Compared with the proposed nozzle, the commercial nozzle has a sharp peak distribution. The droplet size in the commercial nozzle was reduced to 10% at x/D = 1.5. The proposed nozzle has a much smaller droplet size than the commercial nozzle, and the size gradually decreases as the radial position increases. These distributions show that the proposed nozzle can produce a more uniform droplet size over a wider range than commercial nozzles. Figure 11b shows the averaged diameter of whole measured droplets that was obtained from each of the droplet area values, with an assumption of spherical particles. The draft potential is the one of the criterion for the nozzle selection. Although the draft is related with many factors such as droplet size, surrounding wind, drone propeller speed, and height of spraying drone operation, the droplet size is the most important for that. (a) Typically, commercial nozzles in agricultural applications(b) have a diameter range of 300–

Figure 11. (a) Distributions of500 averaged μm, and particle some size operate along abetween radial direction 400 and for 700 the originalμm. In nozzleaddition, and theLee feedback et al. [26] channel reported Figurenozzle 11. with(a) Distributions various load. of (averagedbthat) Comparison a good particle spray ofsize the effectalong total a can droplet radial be diobtained diameter.rection for Thewhen the leftoriginal the and diameter rightnozzle axes and of are thethe forfeedback spray the developed particles channel nozzle andis in the withcommercial various load. nozzles, (b) Comparison respectively.range of the of total 150 droplet to 440 diameter. μm, and The the left suitable and right diameter axes are for is the 250 developed to 500 μandm, commercial to avoid scattering.nozzles, respectively. The commercial nozzle had a droplet size of 1.70 mm exceeding the suitable range for the sprayer. However, the feedback channel nozzle has a droplet size of 226 μm for a 30 kg 4.3. Spraying Uniformity load4.3. Sprayingsuitable forUniformity agricultural applications. For load conditions of 40 and 50 kg, the diameters FigureareFigure 265 12 12aanda showsshows 280 μ m, the respectively, spraying amount amount sufficient at at various various to prevent radial radial scattering. positions. positions. TheThe The reductionspraying spraying in amount was obtained by summing the area of the particles at all z positions with the same dropletamount size was indicates obtained bythat summing the proposed the area no ofzzle the canparticles improve at all the z positions performance with the of sameagricul- radialradial position.position. The maximum amounts amounts in in the the commercial commercial and and proposed proposed nozzle nozzle without without tural drones. 2 loadload are are approximatelyapproximately 30,470 and and 1784 1784 mm mm2, respectively., respectively. The The spraying spraying amount amount increases increases 2 withwith the the load,load, reachingreaching 28,705 mm mm2 atat the the 50 50 kg kg load load condition. condition. Figure Figure 12b 12 showsb shows that that the the commercialcommercial nozzlenozzle has a much smaller smaller FWHM FWHM (0.233 (0.233 DD) than) than the the developed developed nozzle, nozzle, even even withoutwithout thethe loadload condition (1.017 (1.017 DD).). For For loads loads higher higher than than 30 30kg, kg, the the FWHM FWHM is similar, is similar, regardlessregardless ofof thethe loadload conditions. For the effective spraying and longer flight time of drones, uniform ejection is a key parameter. Even though the commercial nozzle has a higher spraying amount, the FWHM result indicates that the developed nozzle is superior in terms of the discharge uniformity. In addition, the proposed nozzle can reduce the amount of pesticide used, compared to the commercial nozzle. Figure 13 shows the standard deviation for the spraying amount at various radial positions normalized with the average value of the total spraying amount. All graphs show a similar trend, with the standard deviation decreasing along the radial direction from the center of the graph to x/D = ±1.5. The standard deviation in the developed nozzle increases with the applied load. The maximum standard deviations in the commercial and the developed nozzle with a load of 50 kg are approximately 17 and 11.5, respectively, confirming that the developed nozzle has a more uniform distribution. Appl. Sci. 2021, 11, 2138 11 of 14

Figure 12. (a) Variations of spraying amount along the radial position and (b) corresponding full width at half maximum (FWHM). For the effective spraying and longer ﬂight time of drones, uniform ejection is a key parameter. Even though the commercial nozzle has a higher spraying amount, the FWHM result indicates that the developed nozzle is superior in terms of the discharge uniformity. In addition, the proposed nozzle can reduce the amount of pesticide used, compared to the commercial nozzle. Figure 13 shows the standard deviation for the spraying amount at various radial positions normalized with the average value of the total spraying amount. All graphs show a similar trend, with the standard deviation decreasing along the radial direction from the center of the graph to x/D = ±1.5. The standard deviation in the developed nozzle increases with the applied load. The maximum standard deviations in the commercial and the developed nozzle with a load of 50 kg are approximately 17 and 11.5, respectively, conﬁrming that the developed nozzle has a more uniform distribution.

4.4. Effect of the Feedback Channel To confirm the effectiveness of the feedback channel, an experiment without a feedback channel was conducted with similar settings as the developed nozzle. The no-load experiment was excluded because the spraying amount was insufficient, as observed in the feedback nozzle experiment. Figure 14a shows the variation in droplet size along the radial position and the average droplet diameter for the non-feedback nozzle. The size variation is similar to that for the feedback nozzle. The larger droplets are observed at the nozzle center, and the size decreases with an increase in the radial distance. As shown in Figure 14b, the diameters in all the cases exceeded the appropriate range. This result shows that the feedback channel helps generate suitable sized droplets, as well as uniform spray. The spraying amount along the radial position and FWHM for the non-feedback nozzle are shown in Figure 15. Similar to the feedback scenario, the amount increased with a higher load, and the maximum amount was 20,036.8 mm2 for the 50 kg load. FWHM is 1.329 at 30 kg, 1.375 at 40 kg, and 1.375 at 50 kg. Compared to the developed nozzle, the non-feedback nozzle has lower spraying amounts and FWHM values, conﬁrming that the feedback channel is more effective for uniform spraying. Appl. Sci. 2021, 11, x FOR PEER REVIEW 12 of 15

(a) (b)

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Figure 12. (a) Variations of spraying amount along the radial position and (b) corresponding full width at half maximum (FWHM).

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1.329 at 30 kg, 1.375 at 40 kg, and 1.375 at 50 kg. Compared to the developed nozzle, the Figure 13. Normalized standard deviation of the spraying amount in various radial positions. The Figurenon-feedback 13. Normalized nozzle standard has lower deviation spraying of amouthe sprayingnts and amount FWHM in values, various confirming radial positions. that the The valuesvaluesfeedback are are normalized normalizedchannel is by more by th thee averagedeffective averaged forspraying spraying uniform amount. amount. spraying.

4.4. Effect of the Feedback Channel To confirm the effectiveness of the feedback channel, an experiment without a feedback channel was conducted with similar settings as the developed nozzle. The no-load experiment was excluded because the spraying amount was insufficient, as observed in the feedback nozzle experiment. Figure 14a shows the variation in droplet size along the radial position and the average droplet diameter for the non-feedback nozzle. The size variation is similar to that for the feedback nozzle. The larger droplets are observed at the nozzle center, and the size decreases with an increase in the radial distance. As shown in Figure 14b, the diameters in all the cases exceeded the appropriate range. This result shows that the feedback channel helps generate suitable sized droplets, as well as uniform spray. The spraying amount along the radial position and FWHM for the non-feedback nozzle are shown in Figure 15. Similar to the feedback scenario, the amount increased with a (ahigher) load, and the maximum amount was 20036.8 (mmb) 2 for the 50 kg load. FWHM is FigureFigure 14. 14.(a) Distributions(a) Distributions of averaged of averaged particle particle size along size alonga radial a direction radial direction and (b) andcomparison (b) comparison of total droplet of total diameter droplet for diameter the non- feedbackfor the nozzle. non-feedback nozzle.

(a) (b)

FigureFigure 15. 15. (a)( aVariations) Variations of of spraying spraying amount amount along along the the radial radial position position and and ( (b)) corresponding FWHMFWHM forfor thethe non-feedbacknon-feedback nozzle. nozzle.

5. Conclusions In this study, an advanced nozzle for an agricultural drone with a feedback channel was developed. The spraying performance was evaluated in terms of the droplet size and uniformity and compared with that of a fan-shaped commercial nozzle. The droplet size reduced by at least six to eight times with the proposed nozzle, making it suitable for use in sprayers. Variations in the spraying amount and the corresponding FWHM indicate that the developed nozzle has a better spraying uniformity than the commercial nozzle. To investigate the effect of the feedback channel, the spraying performance of the nozzle without the feedback channel was further investigated. Although the non- feedback nozzle diameter was smaller than that of the commercial nozzle, the droplet size increased as the feedback channel was removed, regardless of the load condition. The droplet diameter of the non-feedback nozzle was not appropriate for use in sprayers. In addition, the spraying uniformity of the non-feedback nozzle was lower than that with feedback. Considering both the droplet size and spraying uniformity, it was confirmed that the 30 kg load condition is optimal because the FWHM is almost independent of loads exceeding 30 kg, while the droplet size increased with increasing load. In addition to spraying performance, including droplet size and uniformity, the proposed nozzle reduces the consumption of water and pesticide. The flow rate for the developed nozzle with a 50 kg load is 150 mL/min, which is significantly lower than that of the commercial nozzle (500 mL/min). The developed nozzle would help improve the spraying performance and contribute to expanding the drone market in agricultural fields.

Author Contributions: Conceptualization, S.K.K. and S.Y.J.; methodology, S.K.K. and S.Y.J.; valida- tion, S.K.K., H.A., and J.W.M.; formal analysis, S.K.K.; investigation, S.K.K.; data curation, S.K.K.; writing—original draft preparation, S.K.K. and J.W.M.; writing—review and editing, S.K.K. and S.Y.J.; visualization, S.K.K., H.A., and J.W.M.; supervision, S.Y.J.; project administration, S.Y.J.; funding acquisition, S.Y.J. All authors have read and agreed to the published version of the manuscript. Funding: This study was supported by a research fund from Chosun University, Korea, 2020. Data Availability Statement: Not applicable. Conﬂicts of Interest: The authors declare no conﬂict of interest.

References 1. Newcome, L.R. Unmanned Aviation: A Brief History of Unmanned Aerial Vehicles; American Institute of Aeronautics and Astronautics: Orlando, FL, USA, 2004. 2. Cummings, M.L.; Bruni, S.; Mercier, S.; Mitchell, P. Automation Architecture for Single Operator, Multiple UAV Command and Control; Massachusetts Institute of Technology: Cambridge, MA, USA, 2007. 3. Rao, B.; Gopi, A.G.; Maione, R. The Societal Impact of Commercial Drones. Technol. Soc. 2016, 45, 83–90. [CrossRef] 4. Gatti, M.; Giulietti, F. Preliminary design analysis methodology for electric multirotor. IFAC Proc. Vol. 2013, 46, 58–63. [CrossRef] 5. Gatti, M.; Giulietti, F.; Turci, M. Maximum endurance for battery-powered rotary-wing aircraft. Aerosp. Sci. Technol. 2015, 45, 174–179. [CrossRef] 6. Abdilla, A.; Richards, A.; Burrow, S. Power and endurance modelling of battery-powered rotorcraft. In Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, 28 September–2 October 2015. 7. Primicerio, J.; Di Gennaro, S.F.; Fiorillo, E.; Genesio, L.; Lugato, E.; Matese, A.; Vaccari, F.P. A flexible unmanned aerial vehicle for precision agriculture. Precis. Agric. 2012, 13, 517–523. 8. Law, S.E. Electrostatic pesticide spraying: Concepts and practice. IEEE Trans. Ind. Appl. 1983, 1983, 160–168. [CrossRef] 9. Rockwell, A.; Ayers, P. A variable rate, direct nozzle injection field sprayer. Appl. Eng. Agric. 1996, 12, 531–538. [CrossRef] 10. Al-Mamury, M.; Balachandran, W.; Al-Raweshidy, H.; Manivannan, N. Computation model of electrostatic spraying in agriculture Industry. In Proceedings of the 2014 COMSOL Conference in Cambridge, London, UK, 17–19 September 2014. 11. Sharda, A.; Fulton, J.P.; McDonald, T.P.; Brodbeck, C.J. Real-time nozzle flow uniformity when using automatic section control on agricultural sprayers. Comput. Electr. Agric. 2011, 79, 169–179. [CrossRef] 12. Carlton, J.; Isler, D. Development of a device to charge aerial sprays electrostatically. Agric. Aviat. 1966, 8, 44–51. 13. Carlton, J. Electrical capacitance determination and some implications for an electrostatic spray-charging aircraft. Trans. ASAE 1975, 18, 641–0644. [CrossRef] 14. Carlton, J.; Bouse, L.; Kirk, I. Electrostatic charging of aerial spray over cotton. Trans. ASAE 1995, 38, 1641–1645. [CrossRef] 15. Xue, X.; Lan, Y. Agricultural aviation applications in USA. Nongye Jixie Xuebao Trans. Chin. Soc. Agric. Mach. 2013, 44, 194–201. Appl. Sci. 2021, 11, 2138 14 of 14

16. Johnson, L.F.; Bosch, D.F.; Williams, D.C.; Lobitz, B.M. Remote sensing of vineyard management zones: Implications for wine quality. Appl. Eng. Agric. 2001, 17, 557. [CrossRef] 17. Zhou, Z.; Zang, Y.; Luo, X.; Lan, Y.; Xue, X. Technology innovation development strategy on agricultural aviation industry for plant protection in China. Trans. Chin. Soc. Agric. Eng. 2013, 29, 1–10. 18. Yu, S.H.; Kim, Y.K.; Jun, H.J.; Choi, I.S.; Woo, J.K.; Kim, Y.J.; Yun, Y.T.; Choi, Y.; Alidoost, R.; Lee, J.K. Evaluation of Spray Characteristics of Pesticide Injection System in Agricultural Drones. J. Biosyst. Eng. 2020, 45, 272–280. [CrossRef] 19. Chen, P.; Lan, Y.; Huang, X.; Qi, H.; Wang, G.; Wang, J.; Wang, L.; Xiao, H. Droplet Deposition and Control of Planthoppers of Different Nozzles in Two-Stage Rice with a Quadrotor Unmanned Aerial Vehicle. Agronomy 2020, 10, 303. [CrossRef] 20. Jee, S.H.; Jeon, B.I.; Cho, H.C. Implementation of aerial application system for application uniformity. J. Korea Acad. Ind. Coop. Soc. 2016, 17, 597–604. 21. Comprehensive Test of Agricultural Unmanned Aerial Spreader; Foundation of Agri. Tech. Commercialization & Transfer: Iksan, Korea, 2016. 22. Raman, G.; Raghu, S. Cavity resonance suppression using miniature fluidic oscillators. AIAA J. 2004, 42, 2608–2612. [CrossRef] 23. Bobusch, B.C.; Woszidlo, R.; Bergada, J.M.; Nayeri, C.N.; Paschereit, C.O. Experimental study of the internal flow structures inside a fluidic oscillator. Exp. Fluids 2013, 54, 1–12. [CrossRef] 24. Sieber, M.; Ostermann, F.; Woszidlo, R.; Oberleithner, K.; Paschereit, C.O. Lagrangian coherent structures in the flow field of a fluidic oscillator. Phys. Rev. Fluids 2016, 1, 050509. [CrossRef] 25. Ostermann, F.; Woszidlo, R.; Nayeri, C.N.; Paschereit, C.O. Properties of a sweeping jet emitted from a fluidic oscillator. J. Fluid Mech. 2018, 857, 216–238. [CrossRef] 26. Lee, S. Study on the Structures of the Nozzle for the Spray. J. Biosyst. Eng. 1993, 18, 100–109.