Modification of Droplet Evaporation in the Simulation of Fine Droplet Motion Using AGDISP

Teske, Milton E.; Thistle, Harold W.; Londergan, R.J.

doi:10.13031/2013.36444

Cited by 17 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…in which ρ is the density of liquid water (set at 1000 kg m −3 ), d is the particle diameter, i is an index indicating the time-step, D is the diffusion coefficient of water vapour in air, RH is the effective relative humidity, 39 p s is the saturation vapour pressure of water, R w is the specific gas constant of water, T air is the temperature of the air, φ is the activity coefficient (assumed equal to 1), X water is the mass fraction of water in the droplet and T drop is the temperature of the droplet. Parcels (sets of particles with the same properties) are tracked in the Lagrangian mode with one-way coupling.…”

Section: Air Flow Modelmentioning

confidence: 99%

Evaluation of the pattern of spray released from a moving multicopter

Chyrva

Jermy

Strand

et al. 2022

Pest Management Science

View full text Add to dashboard Cite

BACKGROUND Multicopters are used for releasing particulates seeds, fertilizer and spray. Their low cost and high manoeuvrability make them attractive for spraying in steep terrain and areas where overspray is undesirable. This article describes a model of multicopter wake and its influence on particulate dispersion, which is computationally economical compared to many computational fluid dynamics (CFD) approaches, yet retains reasonable accuracy. RESULTS A model was successfully implemented in OpenFOAM. It features source terms for the rotor wash, Lagrangian particle tracking, an evaporation model, and a porous medium approach to model the effect of the ground vegetation. Predictions were validated against the field tests of Richardson et al. which used a DJI Agras MG‐1 multicopter in three different flights with airspeeds of 3.2–4.9 m s−1, ground speeds of 2.1–2.9 m s−1 and cross‐wind speeds of 0.04–2.2 m s−1. The effective swath width (30% line separation) was predicted to within one standard deviation. Sensitivity to a rotor rotational speed, flight height, flight velocity, multicopter roll and yaw angles, surface roughness length, plant height and leaf density was checked. CONCLUSION In all flight trials, the modelled swath was closest to the experimentally obtained swath when the surface roughness of the fetch was equal to 0.5 m (bushes) and the rotational speed of all rotors was equal to 2475 rpm with 0.75R (0.2 m) tall plant canopy (grass) introduced to the model. The model showed acceptable validity for flight velocities of ≤2.8–5 m s−1 when flight parameters can be approximately estimated. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

show abstract

Section: Air Flow Modelmentioning

confidence: 99%

Evaluation of the pattern of spray released from a moving multicopter

Chyrva

Jermy

Strand

et al. 2022

Pest Management Science

View full text Add to dashboard Cite

show abstract

“…A simple vortex wake model, patterned after the approach suggested by Reed (1953), and the subsequent development of a closure technique to recover the effects of atmospheric turbulence on the variance of released spray material about its mean trajectory (von Kármán and Howarth, 1938;Houbolt et al, 1964), led to the first version of AGDISP (Bilanin et al, 1989). Further implementation, funded by the USDA Forest Service (Teske et al, , 2011 led to its current version, AGDISP 8.29. This version of AGDISP includes the Tier I curves from AgDRIFT (Bird et al, 2002;), a sister model to AGDISP.…”

Section: Agdispmentioning

confidence: 99%

Prediction of Aerial Spray Release from UAVs

Teske¹,

Wachspress²,

Thistle³

2018

Transactions of the ASABE

View full text Add to dashboard Cite

Abstract. This article summarizes the ability of CHARM+AGDISP to predict the drift and deposition of sprays released from rotary wing unmanned aerial vehicles (UAVs). This predictive capability results from merging algorithms for spray transport, as found in AGDISP (AGricultural DISPersal), with CHARM (Comprehensive Hierarchical Aeromechanics Rotorcraft Model). The resulting software tracks the release of spray droplets from nozzles on the UAV to deposition on the ground. To date, both AGDISP and CHARM, a code that provides a complete representation of the time-varying, unsteady flow field surrounding a helicopter during transient maneuvering flight near the ground, have been extensively validated. The CHARM+AGDISP software is applied to two UAVs to explore the flow field regimes that present challenges for effective UAV operations. The simulations undertaken indicate flight conditions that yield acceptable deposition levels and minimize drift; inversely, conditions are also identified that result in off-target drift that may be problematic. Keywords: Aerial application, AGDISP, CHARM, Helicopter modeling, Unmanned aerial vehicle (UAV).

show abstract

“…Manufacturers are interested in knowing the size, percentage, or volume of droplets and where they are deposited to compare products, evaluate designs, and predict the effects of operating conditions such as pressure. Over the years, several simulation studies have been conducted to simulate various aspects of the impact of wind on water droplets in sprinklers [20][21][22][23][24][25]. Many factors affect the trajectory and loss of water droplets, which complicates the overall description and estimation of water droplet drift.…”

Section: Introductionmentioning

confidence: 99%

Modelling of Water Drop Movement and Distribution in No Wind and Windy Conditions for Different Nozzle Sizes

Zhu

Lewballah

Fordjour

et al. 2021

Water

View full text Add to dashboard Cite

A numerical model was developed to determine the water drop movement and mean droplet size diameter at any distance from a sprinkler as a function of nozzle size and pressure. Droplet size data from 4, 5, 6, and 7 mm nozzle sizes verified the model. Data for model prediction were generated throughout lab experiments. The results demonstrated that the correlation between the observed and predicted droplet size diameter values for all the nozzle sizes and pressures is quite good. Nozzle size and pressure had a major influence on droplet size. Higher pressure produced smaller droplets over the entire application profile. The wetted distance downwind from the sprinkler increased as wind velocity increased, for example at a constant working pressure of 300 kPa, at wind speeds of 3.5 m/s and 4.5 m/s, 20% and 32% of the total volume exceeded the wet radius respectively. Larger droplets (3.9–4.5 mm), accounting for 3.6% and 6.3% of the total number of distributed droplets, respectively. The model can also predict the droplet size distribution at any wind direction overall the irrigated pattern.

show abstract

Modification of Droplet Evaporation in the Simulation of Fine Droplet Motion Using AGDISP

Cited by 17 publications

References 0 publications

Evaluation of the pattern of spray released from a moving multicopter

Evaluation of the pattern of spray released from a moving multicopter

Prediction of Aerial Spray Release from UAVs

Modelling of Water Drop Movement and Distribution in No Wind and Windy Conditions for Different Nozzle Sizes

Contact Info

Product

Resources

About