Determinação de parâmetros físico-químicos do óleo diesel a partir de curvas de destilação utilizando técnicas quimiométricas

Detalhes bibliográficos
Ano de defesa: 2011
Autor(a) principal: Helga Gabriela Aleme
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://hdl.handle.net/1843/SFSA-8XST7U
Resumo: Diesel is the most consumed fuel in Brazil (49 biL in 2010), which is related to extensive road network in this country. For the consumption of this fuel, it is necessary to verify whether it is appropriate to operating in the diesel engine. This is carried out by analyzing physicochemical parameters, such as distillation, specific gravity, and viscosity, according to Resolution No. 33 of ANP. These physicochemical parameters are time consuming, have high cost of implementation and maintenance of equipment, and consume high purity solvents. Thus, alternative methods for predicting parameters related to the fluidity, flammability and content biodiesel in diesel were proposed in this paper, using multivariate calibration PLS and distillation curves. Low prediction errors were obtained in all predictions, when compared to other analytical techniques, such as infrared spectroscopy, which proves the efficiency of the calibration models constructed from distillation curves. In addition, high correlation between reference and predicted values were obtained in all predictions, indicating the good fit of the models built. This method has low cost, reduces analysis time, is easy to implement and can replace the currently used standard methodology. In addition to evaluate whether the samples of diesel oil are suitable for consumption, it is necessary to determine their origin and type, since this prediction may be an efficient mechanism in enforcement actions and combat cases of tax evasion that are related to simulation of the commercialization of diesel to the states where the tax is lower. Thus, the chemometric techniques PCA and LDA jointly with distillation curves were used to classify and predict origin and type of diesel samples from five refineries and two types. With the PCA it was possible to classify the samples into six groups, according to the origin and type, while by using LDA the origin and type were predicted, with 95.3% accuracy.
id UFMG_e9f4771352f2e7a1e594a659ea445cd1
oai_identifier_str oai:repositorio.ufmg.br:1843/SFSA-8XST7U
network_acronym_str UFMG
network_name_str Repositório Institucional da UFMG
repository_id_str
spelling Determinação de parâmetros físico-químicos do óleo diesel a partir de curvas de destilação utilizando técnicas quimiométricasQuímica analíticaCombustíveis dieselCalibraçãoAnalise multivariadaQuimiometriaEspectroscopia de emissaoParâmetros físico-químicosÓleo dieselCalibraçãoTécnicas quimiométricasDiesel is the most consumed fuel in Brazil (49 biL in 2010), which is related to extensive road network in this country. For the consumption of this fuel, it is necessary to verify whether it is appropriate to operating in the diesel engine. This is carried out by analyzing physicochemical parameters, such as distillation, specific gravity, and viscosity, according to Resolution No. 33 of ANP. These physicochemical parameters are time consuming, have high cost of implementation and maintenance of equipment, and consume high purity solvents. Thus, alternative methods for predicting parameters related to the fluidity, flammability and content biodiesel in diesel were proposed in this paper, using multivariate calibration PLS and distillation curves. Low prediction errors were obtained in all predictions, when compared to other analytical techniques, such as infrared spectroscopy, which proves the efficiency of the calibration models constructed from distillation curves. In addition, high correlation between reference and predicted values were obtained in all predictions, indicating the good fit of the models built. This method has low cost, reduces analysis time, is easy to implement and can replace the currently used standard methodology. In addition to evaluate whether the samples of diesel oil are suitable for consumption, it is necessary to determine their origin and type, since this prediction may be an efficient mechanism in enforcement actions and combat cases of tax evasion that are related to simulation of the commercialization of diesel to the states where the tax is lower. Thus, the chemometric techniques PCA and LDA jointly with distillation curves were used to classify and predict origin and type of diesel samples from five refineries and two types. With the PCA it was possible to classify the samples into six groups, according to the origin and type, while by using LDA the origin and type were predicted, with 95.3% accuracy.Universidade Federal de Minas Gerais2019-08-09T13:02:53Z2025-09-09T00:14:18Z2019-08-09T13:02:53Z2011-08-26info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttps://hdl.handle.net/1843/SFSA-8XST7UHelga Gabriela Alemeinfo:eu-repo/semantics/openAccessporreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMG2025-09-09T00:14:18Zoai:repositorio.ufmg.br:1843/SFSA-8XST7URepositório InstitucionalPUBhttps://repositorio.ufmg.br/oairepositorio@ufmg.bropendoar:2025-09-09T00:14:18Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.none.fl_str_mv Determinação de parâmetros físico-químicos do óleo diesel a partir de curvas de destilação utilizando técnicas quimiométricas
title Determinação de parâmetros físico-químicos do óleo diesel a partir de curvas de destilação utilizando técnicas quimiométricas
spellingShingle Determinação de parâmetros físico-químicos do óleo diesel a partir de curvas de destilação utilizando técnicas quimiométricas
Helga Gabriela Aleme
Química analítica
Combustíveis diesel
Calibração
Analise multivariada
Quimiometria
Espectroscopia de emissao
Parâmetros físico-químicos
Óleo diesel
Calibração
Técnicas quimiométricas
title_short Determinação de parâmetros físico-químicos do óleo diesel a partir de curvas de destilação utilizando técnicas quimiométricas
title_full Determinação de parâmetros físico-químicos do óleo diesel a partir de curvas de destilação utilizando técnicas quimiométricas
title_fullStr Determinação de parâmetros físico-químicos do óleo diesel a partir de curvas de destilação utilizando técnicas quimiométricas
title_full_unstemmed Determinação de parâmetros físico-químicos do óleo diesel a partir de curvas de destilação utilizando técnicas quimiométricas
title_sort Determinação de parâmetros físico-químicos do óleo diesel a partir de curvas de destilação utilizando técnicas quimiométricas
author Helga Gabriela Aleme
author_facet Helga Gabriela Aleme
author_role author
dc.contributor.author.fl_str_mv Helga Gabriela Aleme
dc.subject.por.fl_str_mv Química analítica
Combustíveis diesel
Calibração
Analise multivariada
Quimiometria
Espectroscopia de emissao
Parâmetros físico-químicos
Óleo diesel
Calibração
Técnicas quimiométricas
topic Química analítica
Combustíveis diesel
Calibração
Analise multivariada
Quimiometria
Espectroscopia de emissao
Parâmetros físico-químicos
Óleo diesel
Calibração
Técnicas quimiométricas
description Diesel is the most consumed fuel in Brazil (49 biL in 2010), which is related to extensive road network in this country. For the consumption of this fuel, it is necessary to verify whether it is appropriate to operating in the diesel engine. This is carried out by analyzing physicochemical parameters, such as distillation, specific gravity, and viscosity, according to Resolution No. 33 of ANP. These physicochemical parameters are time consuming, have high cost of implementation and maintenance of equipment, and consume high purity solvents. Thus, alternative methods for predicting parameters related to the fluidity, flammability and content biodiesel in diesel were proposed in this paper, using multivariate calibration PLS and distillation curves. Low prediction errors were obtained in all predictions, when compared to other analytical techniques, such as infrared spectroscopy, which proves the efficiency of the calibration models constructed from distillation curves. In addition, high correlation between reference and predicted values were obtained in all predictions, indicating the good fit of the models built. This method has low cost, reduces analysis time, is easy to implement and can replace the currently used standard methodology. In addition to evaluate whether the samples of diesel oil are suitable for consumption, it is necessary to determine their origin and type, since this prediction may be an efficient mechanism in enforcement actions and combat cases of tax evasion that are related to simulation of the commercialization of diesel to the states where the tax is lower. Thus, the chemometric techniques PCA and LDA jointly with distillation curves were used to classify and predict origin and type of diesel samples from five refineries and two types. With the PCA it was possible to classify the samples into six groups, according to the origin and type, while by using LDA the origin and type were predicted, with 95.3% accuracy.
publishDate 2011
dc.date.none.fl_str_mv 2011-08-26
2019-08-09T13:02:53Z
2019-08-09T13:02:53Z
2025-09-09T00:14:18Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1843/SFSA-8XST7U
url https://hdl.handle.net/1843/SFSA-8XST7U
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Minas Gerais
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMG
instname:Universidade Federal de Minas Gerais (UFMG)
instacron:UFMG
instname_str Universidade Federal de Minas Gerais (UFMG)
instacron_str UFMG
institution UFMG
reponame_str Repositório Institucional da UFMG
collection Repositório Institucional da UFMG
repository.name.fl_str_mv Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)
repository.mail.fl_str_mv repositorio@ufmg.br
_version_ 1856414073136087040