ABSTRACT
BACKGROUND: During unmanned aerial vehicles (UAVs) spraying, downwash and crosswind generate back pressure in comprehensive, which changes in spatial atomization characteristics of spraying droplets. However, the process of such atomization characteristics needs to be clarified. This study focuses on the effect of rotor speed and crosswind speed on spatial atomization characteristics. The computational fluid dynamics (CFD) models of the distributions of airflow, back pressure and atomization characteristics were established, and verification was conducted by developing a validation platform. RESULTS: The CFD results indicated that small droplets of 65-130 µm atomized by negative pressure would be coalesced near the nozzle, while large droplets of 390-520 µm atomized by positive pressure would be aggregated further away. Crosswind caused atomization stratification with droplet sizes of approximately 90 µm, 320 µm and 390 µm. When crosswind speed increased from 3 m/s to 6 m/s, the spraying drifted from 0.5 m to 1 m. When rotor speed increased from 2000 RPM to 3000 RPM, droplet distribution was expanded and droplet particle size was more uniform. Verification results demonstrated that the spraying distribution and the droplet size variation were consistent with the CFD. CONCLUSIONS: Spatial atomization characteristics were highly correlated with airflow and back pressure. Moreover, as crosswind generated droplet drift and atomization stratification and downwash could improve the uniformity of droplet distribution, spraying performance was superior by enhancing downwash to restrain the adverse effect of crosswind in real applications. © 2023 Society of Chemical Industry.
Subject(s)
Hydrodynamics , Particle SizeABSTRACT
BACKGROUND: A key challenge for unmanned aerial vehicle (UAV) spraying sometimes used in tea plantations is the downwash flow structure there stronger than in crops. In addition, the UAV spray is affected by the relationship between the nozzle design and the pesticide. However, there is little current research on this aspect. As a preliminary step this study focuses on the most appropriate pesticide for a designated nozzle in a six-rotor UAV according to the nozzle-pesticide relationship using a three-dimensional computational fluid dynamics model. This model considers the downwash flow structure effect and nozzle spray performance in hover. Nozzle FVP110-02, widely used in six-rotor UAVs, is used as a representative nozzle and bifenthrin and tea saponin water, commonly used in tea plantations, are used as the pesticides. RESULTS: The downwash flow structure of the six-rotor UAV in hover was conveniently controlled by the flight height and rotational speed, thereby causing the turbulence to be more stable. For nozzle FVP110-02, bifenthrin was more appropriate than tea saponin water at the same concentration, whilst bifenthrin and tea saponin water at a concentration of 1:1000 showed the best performance under identical working conditions. CONCLUSION: The numerical model developed here was shown to be effective for investigating the relationship between nozzle and pesticide. Our findings will help to not only improve UAV spraying for tea cultivation but also provide guidelines for pesticide selection in crops. Further work will address the comparison of the rigorous qualification of the numerical simulations with the measurements by the field test. © 2023 Society of Chemical Industry.
Subject(s)
Pesticides , Pesticides/analysis , Unmanned Aerial Devices , Crops, Agricultural , TeaABSTRACT
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.
ABSTRACT
BACKGROUND: One theoretical advantage of using unmanned aerial vehicles (UAVs) to spray pesticides for maturing corn is that the strong downwash penetrates canopies. However, only few studies have been conducted to examine in-canopy downwash characteristics. This paper investigated the downwash by a six-rotor UAV in mature cornfields. 3D wind speeds in corn canopies and an open area were measured, and comparisons conducted. RESULTS: The downwash by the UAV resulted in in-canopy maximum wind speeds. Z-dimensional downwash was sensitive to all factors, whereas the X- and Y-dimensional downwashes were related to layers and crop positions. Meanwhile, when comparing with the downwash between a 2 m hovering position and the optimal flight parameters, the X-dimensional and Y-dimensional motion time of top-layer downwash generally advanced by 3.8 s and 1.6 s, whereas both motion time and the strength of the Z-dimensional downwash were impeded by ≈2.2-s hysteresis at middle layers and ≈4.5-s time reduction, respectively. Thus, combined with distributions, the corn on the left or right might not be sprayed sufficiently. Furthermore, under the convergence requirement error of 0.01, the overall correlation of the model was ≈0.846 in terms of the Z-dimensional downwash and ≈0.55 and 0.61 for the X- and Y-dimensions, respectively. CONCLUSION: The selection of operation parameters should mainly consider the Z-dimensional downwash. The optimal operation parameters were a height of 2 m with a speed of 4 m s-1 . Meanwhile, the canopy effect could influence the uniformity, motion and strength of downwash. Predictions could be achieved before operation. © 2022 Society of Chemical Industry.
Subject(s)
Pesticides , Unmanned Aerial Devices , Pesticides/analysis , Wind , Zea maysABSTRACT
In this article, we present a versatile gas detector that can operate on an unmanned aerial vehicle (UAV) or unmanned ground vehicle (UGV). The device has six electrochemical modules, which can be selected to measure specific gases, according to the mission requirements. The gas intake is realized by a miniaturized vacuum pump, which provides immediate gas distribution to the sensors and improves a fast response. The measurement data are sent wirelessly to the operator's computer, which continuously stores results and presents them in real time. The 2 m tubing allows measurements to be taken in places that are not directly accessible to the UGV or the UAV. While UAVs significantly enhanced the versatility of sensing applications, point gas detection is challenging due to the downwash effect and gas dilution produced by the rotors. In our work, we demonstrated the method of downwash effect reduction at aerial point gas measurements by applying a long-distance probe, which was kept between the UAV and the examined object. Moreover, we developed a safety connection protecting the UAV and sensor in case of accidental jamming of the tubing inside the examined cavity. The methods presented provide an effective gas metering strategy using UAVs.
ABSTRACT
Multi-rotor unmanned aerial vehicles (UAVs) for plant protection are widely used in China's agricultural production. However, spray droplets often drift and distribute nonuniformly, thereby harming its utilization and the environment. A variable spray system is designed, discussed, and verified to solve this problem. The distribution characteristics of droplet deposition under different spray states (flight state, environment state, nozzle state) are obtained through computational fluid dynamics simulation. In the verification experiment, the wind velocity error of most sample points is less than 1 m/s, and the deposition ratio error is less than 10%, indicating that the simulation is reliable. A simulation data set is used to train support vector regression and back propagation neural network with multiple parameters. An optimal regression model with the root mean square error of 6.5% is selected. The UAV offset and nozzle flow of the variable spray system can be obtained in accordance with the current spray state by multi-sensor fusion and the predicted deposition distribution characteristics. The farmland experiment shows that the deposition volume error between the prediction and experiment is within 30%, thereby proving the effectiveness of the system. This article provides a reference for the improvement of UAV intelligent spray system.
Subject(s)
Agriculture , Regression Analysis , WindABSTRACT
The plume dispersion model AERMOD provides an efficient method for modeling ground-level pollutant concentrations in wakes of buildings. In recent years, several studies have shown that the downwash algorithms within AERMOD often perform poorly in certain applications. Some studies have proposed modifications to the downwash algorithm in AERMOD to bring the model closer to representing the underlying physical processes associated with building downwash and closer to more accurately modeling observed pollutant concentrations. One such study by Monbureau et al. (2018) made changes to the model that significantly improved its ability to model ground level concentrations for a simple case of a single rectangular building with an elevated, effluent-emitting stack experiencing winds perpendicular to the upwind side of the building. The present study introduces a simple algorithm to enhance AERMOD's ability to appropriately match the dispersion pattern in the complex flow case of non-orthogonal winds. This algorithm, which is based on a rich set of Large-Eddy Simulations (LES), applies to a variety of building dimensions, stack locations, and stack heights. A sensitivity analysis demonstrates how additional modifications to the downwash algorithm may further improve AERMOD in modeling the spatial location of observed ground-level effluent.
ABSTRACT
Unmanned aerial vehicles (UAV) have been used to monitor gas emissions for research projects, though downwash, the airflow produced by the UAV rotors, is potentially capable of artificially altering gas concentration measurements. Anemometers, placed at ten different distances below a 6-rotor UAV, measured air speeds in the downwash region. The collected data was used in combination with UAV rotor speed data to determine the stabilization time of the downwash region after the UAV has returned to a stable hovering position. The stabilization time will determine the amount of time after UAV movement until reliable concentration readings can be obtained within the downwash region. This paper presents stabilization times after vertical upward and rotational UAV movement.
ABSTRACT
Accurate measurement of the downwash flow field of plant protection unmanned aerial vehicles (UAVs) is essential for analyzing the spatial distribution of droplets. To realize on-line rapid detection of the downwash flow field of a multi-rotor UAV, a flexible polypropylene detection device based on the principle of full bridge strain effect was proposed. Its performance principle was based on the physical deformation caused by wind pressure. The Fluid Flow and Static Structural modules of ANSYS 16.0 finite element software were used to simulate one-way fluid-solid coupling interaction. The surface of the resistive strain gauge embedded in the flexible detecting structure responded well to wind speed variation, hence it was suitable for downwash airflow wind field detection. By solving the strain force on the surface of the flexible detection structure, the length and layout of the grating wire of the strain gauge on the surface of the flexible detection structure were optimized. Meanwhile at 4 m·s-1 wind speed, the output voltage at varied bridge flexible acquisition systems in the acquisition card was measured. Results indicated coefficient of variation of 3.67%, 1.63% and 1.5%, respectively, which proved the good data acquisition consistency of the system. Through calibration test, the regression equation for the relationship between output voltage and wind speed for three unique sensor signal measuring circuits was established. The determination coefficients R2 for single bridge, half bridge and full bridge circuits were 0.9885, 0.9866 and 0.9959, respectively. In conclusion, by applying the multi-rotor plant protection UAV test platform, the results indicated the maximum relative error of the wind speed at each sampling point of the system at 1.0 m altitude was below 5.61%. Simulated and measured value had an RMSE maximum error of 0.1246 m·s-1. Moreover, downwash airflow detection not only has high accuracy but also has high sensitivity. Thus, there is convenience and practicability in the plant protection offered by this approach. The rapid measurement of UAV wind field and the established two-dimensional wind field model can provide a basis for precise application of agricultural aviation.
ABSTRACT
The wide adoption of combined heat and power (CHP) can not only improve energy efficiency, but also strengthens energy system resiliency. While CHP reduces overall emissions compared to generating the same amount of electricity and heat separately, its on-site nature also means that CHP facilities operate in populated areas, raising concerns over their near-source air quality impact. Evaluation of the near-source impact of distributed CHP is limited by emission data availability, especially in terms of particulate matter (PM). In this paper, we report on stack emission testing results of a community-scale CHP plant with two natural gas turbine units (15â¯MW each) from measurements conducted in both 2010 and 2015, and assess the near-source air quality impact using an integrated modeling framework using the stack test results, site-specific meteorological data and terrain profiles with buildings. The NOx removal efficiency by selective catalytic reduction (SCR) is estimated to be â¼83% according to the emission testing. The integrated framework employs AERMOD to screen air quality in a 2.7â¯â¯kmâ¯×â¯2.3â¯â¯km domain from 2011 to 2015 to identify the highest ground-level concentrations (GLCs). Examining the corresponding meteorological conditions, we find that those high GLCs appeared during the stable atmospheric boundary layer with relative high wind speed. Next, the worse-case scenarios identified from the screening process are simulated using the detailed Unsteady Reynolds Averaged Navier-Stokes (URANS) model coupled with a chemistry solver. The results generally show low GLCs of primary PM2.5 for this case study. However, our analysis also suggests greater building downwash impacts with the presence of taller and denser urban structures. Therefore, the near-source impact of natural gas-fired CHP in large metropolitan areas is worthy of further investigation.
Subject(s)
Air Pollutants/analysis , Air Pollution/analysis , Environmental Monitoring/methods , Natural Gas/analysis , Particulate Matter/analysis , Power Plants , Hot Temperature , Models, Theoretical , Urbanization , WindABSTRACT
High fidelity, scale-resolving numerical simulations of flow and pollutant dispersion around several elongated isolated buildings are presented in this paper. The embedded large eddy simulation (ELES) is used to model flow and concentration fields for six test cases with various source-building geometries. Specifically, the influence of building aspect ratio, wind direction, and source location is examined with these cases. Results obtained from the present ELES model are evaluated using available wind tunnel measurements, including those of streamwise and spanwise velocities, turbulent kinetic energy, and streamwise, lateral, and spanwise pollutant concentrations. Comparisons indicate that the ELES provides realistic representations of the flow and concentration fields observed in wind tunnel experiments, and captures several complex phenomena including the lateral shift and enhanced descent of the plume for rotated/elongated buildings. Furthermore, the ELES provides a means to study the advective and turbulent concentration fluxes, plume shapes, and geometry of vortical structures that is used to examine turbulent transport of pollutants around buildings. We investigate the enhancement of vertical and lateral plume spread as the building aspect ratio is increased. In addition, through the study of advective and turbulent concentration fluxes, we shed light on the physics behind higher ground-level concentrations observed for rotated buildings.
ABSTRACT
Air quality data collection near pollution sources is difficult, particularly when sites are complex, have physical barriers, or are themselves moving. Small Unmanned Aerial Vehicles (UAVs) offer new approaches to air pollution and atmospheric studies. However, there are a number of critical design decisions which need to be made to enable representative data collection, in particular the location of the air sampler or air sensor intake. The aim of this research was to establish the best mounting point for four gas sensors and a Particle Number Concentration (PNC) monitor, onboard a hexacopter, so to develop a UAV system capable of measuring point source emissions. The research included two different tests: (1) evaluate the air flow behavior of a hexacopter, its downwash and upwash effect, by measuring air speed along three axes to determine the location where the sensors should be mounted; (2) evaluate the use of gas sensors for CO2, CO, NO2 and NO, and the PNC monitor (DISCmini) to assess the efficiency and performance of the UAV based system by measuring emissions from a diesel engine. The air speed behavior map produced by test 1 shows the best mounting point for the sensors to be alongside the UAV. This position is less affected by the propeller downwash effect. Test 2 results demonstrated that the UAV propellers cause a dispersion effect shown by the decrease of gas and PN concentration measured in real time. A Linear Regression model was used to estimate how the sensor position, relative to the UAV center, affects pollutant concentration measurements when the propellers are turned on. This research establishes guidelines on how to develop a UAV system to measure point source emissions. Such research should be undertaken before any UAV system is developed for real world data collection.
ABSTRACT
Accumulation records of pollutant metals in peat have been frequently used to reconstruct past atmospheric deposition rates. While there is good support for peat as a record of relative changes in metal deposition over time, questions remain whether peat archives represent a quantitative or a qualitative record. Several processes can potentially influence the quantitative record of which downwashing is particularly pertinent as it would have a direct influence on how and where atmospherically deposited metals are accumulated in peat. The aim of our study was two-fold: first, to compare and contrast the retention of dissolved Pb, Cu, Zn and Ni in peat cores; and second, to test the influence of different precipitation intensities on the potential downwashing of metals. We applied four 'rainfall' treatments to 13 peat cores over a 3-week period, including both daily (2 or 5.3 mm day(-1)) and event-based additions (37 mm day(-1), added over 1h or over a 10h rain event). Two main trends were apparent: 1) there was a difference in retention of the added dissolved metals in the surface layer (0-2 cm): 21-85% for Pb, 18-63% for Cu, 10-25% for Zn and 10-20% for Ni. 2) For all metals and both peat types (sphagnum lawn and fen), the addition treatments resulted in different downwashing depths, i.e., as the precipitation-addition increased so did the depth at which added metals could be detected. Although the largest fraction of Pb and Cu was retained in the surface layer and the remainder effectively immobilized in the upper peat (≤ 10 cm), there was a smearing effect on the overall retention, where precipitation intensity exerts an influence on the vertical distribution of added trace metals. These results indicate that the relative position of a deposition signal in peat records would be preserved, but it would be quantitatively attenuated.
Subject(s)
Environmental Monitoring , Metals/analysis , Soil Pollutants/analysis , Sphagnopsida/chemistry , Water Pollutants, Chemical/analysis , Atmosphere/chemistry , Rain/chemistry , Soil/chemistryABSTRACT
Accurate dating of peat accumulation is essential for quantitatively reconstructing past changes in atmospheric metal deposition and carbon burial. By analyzing fallout radionuclides (210)Pb, (137)Cs, (241)Am, and (7)Be, and total Pb and Hg in 5 cores from two Swedish peatlands we addressed the consequence of estimating accumulation rates due to downwashing of atmospherically supplied elements within peat. The detection of (7)Be down to 18-20 cm for some cores, and the broad vertical distribution of (241)Am without a well-defined peak, suggest some downward transport by percolating rainwater and smearing of atmospherically deposited elements in the uppermost peat layers. Application of the CRS age-depth model leads to unrealistic peat mass accumulation rates (400-600 g m(-2) yr(-1)), and inaccurate estimates of past Pb and Hg deposition rates and trends, based on comparisons to deposition monitoring data (forest moss biomonitoring and wet deposition). After applying a newly proposed IP-CRS model that assumes a potential downward transport of (210)Pb through the uppermost peat layers, recent peat accumulation rates (200-300 g m(-2) yr(-1)) comparable to published values were obtained. Furthermore, the rates and temporal trends in Pb and Hg accumulation correspond more closely to monitoring data, although some off-set is still evident. We suggest that downwashing can be successfully traced using (7)Be, and if this information is incorporated into age-depth models, better calibration of peat records with monitoring data and better quantitative estimates of peat accumulation and past deposition are possible, although more work is needed to characterize how downwashing may vary between seasons or years.
ABSTRACT
An analytical treatment to quantify the losses captured in the induced power factor, k, is provided for flapping wings in normal hover, including the effects of non-uniform downwash, tip losses and finite flapping amplitude. The method is based on a novel combination of actuator disc and lifting line blade theories that also takes into account the effect of advance ratio. The model has been evaluated against experimental results from the literature and qualitative agreement obtained for the effect of advance ratio on the lift coefficient of revolving wings. Comparison with quantitative experimental data for the circulation as a function of span for a fruitfly wing shows that the model is able to correctly predict the circulation shape of variation, including both the magnitude of the peak circulation and the rate of decay in circulation towards zero. An evaluation of the contributions to induced power factor in normal hover for eight insects is provided. It is also shown how Reynolds number can be accounted for in the induced power factor, and good agreement is obtained between predicted span efficiency as a function of Reynolds number and numerical results from the literature. Lastly, it is shown that for a flapping wing in hover k owing to the non-uniform downwash effect can be reduced to 1.02 using an arcsech chord distribution. For morphologically realistic wing shapes based on beta distributions, it is shown that a value of 1.07 can be achieved for a radius of first moment of wing area at 40% of wing length.