Fractal analysis of agricultural nozzles spray
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Scientia Agrícola (Online) |
Texto Completo: | https://www.revistas.usp.br/sa/article/view/22740 |
Resumo: | Fractal scaling of the exponential type is used to establish the cumulative volume (V) distribution applied through agricultural spray nozzles in size x droplets, smaller than the characteristic size X. From exponent d, we deduced the fractal dimension (Df) which measures the degree of irregularity of the medium. This property is known as 'self-similarity'. Assuming that the droplet set from a spray nozzle is self-similar, the objectives of this study were to develop a methodology for calculating a Df factor associated with a given nozzle and to determine regression coefficients in order to predict droplet spectra factors from a nozzle, taking into account its own Df and pressure operating. Based on the iterated function system, we developed an algorithm to relate nozzle types to a particular value of Df. Four nozzles and five operating pressure droplet size characteristics were measured using a Phase Doppler Particle Analyser (PDPA). The data input consisted of droplet size spectra factors derived from these measurements. Estimated Df values showed dependence on nozzle type and independence of operating pressure. We developed an exponential model based on the Df to enable us to predict droplet size spectra factors. Significant coefficients of determination were found for the fitted model. This model could prove useful as a means of comparing the behavior of nozzles which only differ in not measurable geometric parameters and it can predict droplet spectra factors of a nozzle operating under different pressures from data measured only in extreme work pressures. |
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Scientia Agrícola (Online) |
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Fractal analysis of agricultural nozzles spray pesticides applicationmodeling Fractal scaling of the exponential type is used to establish the cumulative volume (V) distribution applied through agricultural spray nozzles in size x droplets, smaller than the characteristic size X. From exponent d, we deduced the fractal dimension (Df) which measures the degree of irregularity of the medium. This property is known as 'self-similarity'. Assuming that the droplet set from a spray nozzle is self-similar, the objectives of this study were to develop a methodology for calculating a Df factor associated with a given nozzle and to determine regression coefficients in order to predict droplet spectra factors from a nozzle, taking into account its own Df and pressure operating. Based on the iterated function system, we developed an algorithm to relate nozzle types to a particular value of Df. Four nozzles and five operating pressure droplet size characteristics were measured using a Phase Doppler Particle Analyser (PDPA). The data input consisted of droplet size spectra factors derived from these measurements. Estimated Df values showed dependence on nozzle type and independence of operating pressure. We developed an exponential model based on the Df to enable us to predict droplet size spectra factors. Significant coefficients of determination were found for the fitted model. This model could prove useful as a means of comparing the behavior of nozzles which only differ in not measurable geometric parameters and it can predict droplet spectra factors of a nozzle operating under different pressures from data measured only in extreme work pressures. Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2012-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/2274010.1590/S0103-90162012000100002Scientia Agricola; v. 69 n. 1 (2012); 6-12Scientia Agricola; Vol. 69 Núm. 1 (2012); 6-12Scientia Agricola; Vol. 69 No. 1 (2012); 6-121678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/22740/24764Copyright (c) 2015 Scientia Agricolainfo:eu-repo/semantics/openAccessAgüera, FranciscoNuyttens, DavidCarvajal, FernandoSánchez-Hermosilla, Julián2015-07-07T19:14:31Zoai:revistas.usp.br:article/22740Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2015-07-07T19:14:31Scientia Agrícola (Online) - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Fractal analysis of agricultural nozzles spray |
title |
Fractal analysis of agricultural nozzles spray |
spellingShingle |
Fractal analysis of agricultural nozzles spray Agüera, Francisco pesticides application modeling |
title_short |
Fractal analysis of agricultural nozzles spray |
title_full |
Fractal analysis of agricultural nozzles spray |
title_fullStr |
Fractal analysis of agricultural nozzles spray |
title_full_unstemmed |
Fractal analysis of agricultural nozzles spray |
title_sort |
Fractal analysis of agricultural nozzles spray |
author |
Agüera, Francisco |
author_facet |
Agüera, Francisco Nuyttens, David Carvajal, Fernando Sánchez-Hermosilla, Julián |
author_role |
author |
author2 |
Nuyttens, David Carvajal, Fernando Sánchez-Hermosilla, Julián |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Agüera, Francisco Nuyttens, David Carvajal, Fernando Sánchez-Hermosilla, Julián |
dc.subject.por.fl_str_mv |
pesticides application modeling |
topic |
pesticides application modeling |
description |
Fractal scaling of the exponential type is used to establish the cumulative volume (V) distribution applied through agricultural spray nozzles in size x droplets, smaller than the characteristic size X. From exponent d, we deduced the fractal dimension (Df) which measures the degree of irregularity of the medium. This property is known as 'self-similarity'. Assuming that the droplet set from a spray nozzle is self-similar, the objectives of this study were to develop a methodology for calculating a Df factor associated with a given nozzle and to determine regression coefficients in order to predict droplet spectra factors from a nozzle, taking into account its own Df and pressure operating. Based on the iterated function system, we developed an algorithm to relate nozzle types to a particular value of Df. Four nozzles and five operating pressure droplet size characteristics were measured using a Phase Doppler Particle Analyser (PDPA). The data input consisted of droplet size spectra factors derived from these measurements. Estimated Df values showed dependence on nozzle type and independence of operating pressure. We developed an exponential model based on the Df to enable us to predict droplet size spectra factors. Significant coefficients of determination were found for the fitted model. This model could prove useful as a means of comparing the behavior of nozzles which only differ in not measurable geometric parameters and it can predict droplet spectra factors of a nozzle operating under different pressures from data measured only in extreme work pressures. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-02-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.revistas.usp.br/sa/article/view/22740 10.1590/S0103-90162012000100002 |
url |
https://www.revistas.usp.br/sa/article/view/22740 |
identifier_str_mv |
10.1590/S0103-90162012000100002 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/sa/article/view/22740/24764 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2015 Scientia Agricola info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2015 Scientia Agricola |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz |
publisher.none.fl_str_mv |
Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz |
dc.source.none.fl_str_mv |
Scientia Agricola; v. 69 n. 1 (2012); 6-12 Scientia Agricola; Vol. 69 Núm. 1 (2012); 6-12 Scientia Agricola; Vol. 69 No. 1 (2012); 6-12 1678-992X 0103-9016 reponame:Scientia Agrícola (Online) instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Scientia Agrícola (Online) |
collection |
Scientia Agrícola (Online) |
repository.name.fl_str_mv |
Scientia Agrícola (Online) - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
scientia@usp.br||alleoni@usp.br |
_version_ |
1800222791551680512 |