Development of droplet characteristics prediction models for air induction nozzles based on wind tunnel tests

Liao, Juan; Hewitt, Andrew; Wang, Pei; Luo, Xiwen; Zhang, Ying; Zhou, Zhiyan; Lan, Yubin; O’Donnell, Chris

doi:10.25165/j.ijabe.20191206.5014

Cited by 8 publications

(8 citation statements)

References 23 publications

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“…using the stepwise method. Equation ( 9) is the equation of the input and output variables of the prediction model [41]. Based on Equation ( 9), the prediction model was developed, with a total of six variable conditions, such as the engine torque, engine speed, travel speed, slip ratio, and tillage depth, using the SPSS 21 software (SPSS Inc., Chicago, IL, USA).…”

Section: Regression Model Developmentmentioning

confidence: 99%

Development of a Prediction Model for Tractor Axle Torque during Tillage Operation

Kim

Baek

et al. 2020

Applied Sciences

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In general, the tractor axle torque is used as an indicator for making various decisions when engineers perform transmission fatigue life analysis, optimal design, and accelerated life testing. Since the existing axle torque measurement method requires an expensive torque sensor, an alternative method is required. Therefore, the aim of this study is to develop a prediction model for the tractor axle torque during tillage operation that can replace expensive axle torque sensors. A prediction model was proposed through regression analysis using key variables affecting the tractor axle torque. The engine torque, engine speed, tillage depth, slip ratio, and travel speed were selected as explanatory variables. In order to collect explanatory and dependent variable data, a load measurement system was developed, and a field experiment was performed on moldboard plow tillage using a tractor with a load measurement system. A total of eight axle torque prediction regression models were proposed using the measured calibration dataset. The adjusted coefficient of determination (R2) of the proposed regression model showed a range of 0.271 to 0.925. Among them, the prediction model E showed an adjusted R2 of 0.925. All of the prediction models were verified using a validation set. All of the axle torque prediction models showed an mean absolute percentage error (MAPE) of less than 2.8%. In particular, Model E, adopting engine torque, engine speed, and travel speed as variables, and Model H, adopting engine torque, tillage depth and travel speed as variables, showed MAPEs of 1.19 and 1.30%, respectively. Therefore, it was found that the proposed prediction models are applicable to actual axle torque prediction.

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Section: Regression Model Developmentmentioning

confidence: 99%

Development of a Prediction Model for Tractor Axle Torque during Tillage Operation

Kim

Baek

et al. 2020

Applied Sciences

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“…Moreover, height and downwind distance of the wind tunnel should be sufficient to contain enough sampling equipment or collectors. According to Table 3 , the length of the UASS is generally greater than 2 m, the height range lies between 0.5 and 0.7 m, and the size range of the rotor is 0.53–1.19 m. According to the specifications of the wind tunnel for spray testing mentioned in the literature ( Ling et al, 2018 ; Ding et al, 2019 ; Liao et al, 2019 ; Wang et al, 2020 , 2020b ), the width of most wind tunnel cross-sections ranges between 1.2 and 3 m, while the height is 1.1–2 m high. As the length of the rotor itself interferes with the current cross-sectional dimensions of the wind tunnel, the whole machine or the rotor are difficult to place inside the wind tunnel.…”

Section: Discussion and Further Recommendationsmentioning

confidence: 99%

Characteristics of unmanned aerial spraying systems and related spray drift: A review

et al. 2022

Self Cite

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Although drift is not a new issue, it deserves further attention for Unmanned Aerial Spraying Systems (UASS). The use of UASS as a spraying tool for Plant Protection Products is currently explored and applied worldwide. They boast different benefits such as reduced applicator exposure, high operating efficiency and are unconcerned by field-related constraints (ground slope, ground resistance). This review summarizes UASS characteristics, spray drift and the factors affecting UASS drift, and further research that still needs to be developed. The distinctive features of UASS comprise the existence of one or more rotors, relatively higher spraying altitude, faster-flying speed, and limited payload. This study highlights that due to most of these features, the drift of UASS may be inevitable. However, this drift could be effectively reduced by optimizing the structural layout of the rotor and spraying system, adjusting the operating parameters, and establishing a drift buffer zone. Further efforts are still necessary to better assess the drift characteristics of UASS, establish drift models from typical models, crops, and climate environments, and discuss standard methods for measuring UASS drift.

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“…The researchers [53][54][55] also reported corresponding findings that the root-to-shoot ratio was higher in aerated growth boxes with good oxygen circulation than under poor oxygen conditions. Another study concluded that different spraying intervals induce different integrated distribution patterns, shifting assimilates from roots to shoots [56][57][58][59].…”

Section: Discussionmentioning

confidence: 99%

Influence of Atomization Nozzles and Spraying Intervals on Growth, Biomass Yield, and Nutrient Uptake of Butter-Head Lettuce under Aeroponics System

et al. 2021

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The atomized nutrient solution droplet sizes and spraying intervals can impact the chemical properties of the nutrient solution, biomass yield, root-to-shoot ratio and nutrient uptake of aeroponically cultivated plants. In this study, four different nozzles having droplet sizes N1 = 11.24, N2 = 26.35, N3 = 17.38 and N4 = 4.89 µm were selected and misted at three nutrient solution spraying intervals of 30, 45 and 60 min, with a 5 min spraying time. The measured parameters were power of hydrogen (pH) and electrical conductivity (EC) values of the nutrient solution, shoot and root growth, ratio of roots to shoots (fresh and dry), biomass yield and nutrient uptake. The results indicated that the N1 presented significantly lower changes in chemical properties than those of N2, N3 and N4, resulting in stable lateral root growth and increased biomass yield. Also, the root-to-shoot ratio significantly increased with increasing spraying interval using N1 and N4 nozzles. The N1 nozzle also revealed a significant effect on the phosphorous, potassium and magnesium uptake by the plants misted at proposed nutrient solution spraying intervals. However, the ultrasonic nozzle showed a nonsignificant effect on all measured parameters with respect to spraying intervals. In the last, this research experiment validates the applicability of air-assisted nozzle (N1) misting at a 30-min spraying interval and 5 min of spraying time for the cultivation of butter-head lettuce in aeroponic systems.

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Development of droplet characteristics prediction models for air induction nozzles based on wind tunnel tests

Cited by 8 publications

References 23 publications

Development of a Prediction Model for Tractor Axle Torque during Tillage Operation

Development of a Prediction Model for Tractor Axle Torque during Tillage Operation

Characteristics of unmanned aerial spraying systems and related spray drift: A review

Influence of Atomization Nozzles and Spraying Intervals on Growth, Biomass Yield, and Nutrient Uptake of Butter-Head Lettuce under Aeroponics System

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