Fractal analysis of agricultural nozzles spray

Detalhes bibliográficos
Autor(a) principal: Agüera, Francisco
Data de Publicação: 2012
Outros Autores: Nuyttens, David, Carvajal, Fernando, Sánchez-Hermosilla, Julián
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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spelling 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
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