Parameters influencing deposit estimation when using water sensitive papers
AbstractThe aim of the study was to assess the possibility of using water sensitive papers (WSP) to estimate the amount of deposit on the target when varying the spray characteristics. To identify the main quantities influencing the deposit, some simplifying hypotheses were applied to simulate WSP behaviour: log-normal distribution of the diameters of the drops and circular stains randomly placed on the images. A very large number (4704) of images of WSPs were produced by means of simulation. The images were obtained by simulating drops of different arithmetic mean diameter (40-300 μm), different coefficient of variation (0.1-1.5), and different percentage of covered surface (2-100%, not considering overlaps). These images were considered to be effective WSP images and then analysed using image processing software in order to measure the percentage of covered surface, the number of particles, and the area of each particle; the deposit was then calculated. These data were correlated with those used to produce the images, varying the spray characteristics. As far as the drop populations are concerned, a classification based on the volume median diameter only should be avoided, especially in case of high variability. This, in fact, results in classifying sprays with very low arithmetic mean diameter as extremely or ultra coarse. The WSP image analysis shows that the relation between simulated and computed percentage of covered surface is independent of the type of spray, whereas impact density and unitary deposit can be estimated from the computed percentage of covered surface only if the spray characteristics (arithmetic mean and coefficient of variation of the drop diameters) are known. These data can be estimated by analysing the particles on the WSP images. The results of a validation test show good agreement between simulated and computed deposits, testified by a high (0.93) coefficient of determination.
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Copyright (c) 2013 Emanuele Cerruto, Claudia Aglieco, Sabina Failla, Giuseppe Manetto
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