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Issue 34, 2016
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Predicting the dynamic impact behaviour of spray droplets on flat plant surfaces

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Abstract

The dynamic impact behaviour of water droplets on plant surfaces was investigated based on a multiphase computational fluid dynamics (CFD) model. The study was conducted using the Volume Of Fluid (VOF) approach. The static contact angle of water droplets on leaf surfaces of different plants (apple, pear, leek and cabbage) was measured and found to vary between 54.9 and 138.2°. Impact experiments were conducted by monitoring the flow and impact characteristics of water droplets on leaves in still air with a high speed camera. Droplets were generated by an agricultural flat fan spray nozzle moving across the leaf at constant speed. The nozzle produced droplets with diameters ranging from 20.6 up to 550.8 μm, and droplet velocity values near the impact between 0.03 and 13.2 m s−1. The CFD model was capable of predicting the observed dynamic impact behaviour of droplets on the plant surfaces. The fate of the droplets after the impact process for adhesion, bouncing or splashing was accurately predicted for Weber numbers (We) in the range of 0.007 to 1096 and droplet Reynolds numbers (Re) between 5 to 8000. The process was highly dependent on the surface and droplet flow characteristics during the impact. Combinations of We, Re and Ohnesorge (Oh) numbers defined the droplet maximum spread factor, the number of secondary droplets generated as a result of the splashing process and the transition between the different impact outcomes. These criteria can then be used in field scale spray deposition and drift models to better understand agricultural spray operations.

Graphical abstract: Predicting the dynamic impact behaviour of spray droplets on flat plant surfaces

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Article information


Submitted
20 Apr 2016
Accepted
02 Aug 2016
First published
02 Aug 2016

This article is Open Access

Soft Matter, 2016,12, 7195-7211
Article type
Paper

Predicting the dynamic impact behaviour of spray droplets on flat plant surfaces

M. A. Delele, D. Nuyttens, A. T. Duga, A. Ambaw, F. Lebeau, B. M. Nicolai and P. Verboven, Soft Matter, 2016, 12, 7195
DOI: 10.1039/C6SM00933F

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