Density and electrical conductivity for aqueous mixtures of monoethylene glycol and sodium chloride: experimental data and data-driven modeling for composition determination

Detalhes bibliográficos
Autor(a) principal: Chiavone Filho, Osvaldo
Data de Publicação: 2021
Outros Autores: Moura Neto, Mário Hermes de, Monteiro, Mateus Fernandes, Ferreira, Fedra A. V., Silva, Dannielle Janainne, Figueiredo, Camila S., Ciambelli, João Rafael Perroni, Pereira, Leonardo S., Nascimento, Jailton Ferreira do
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRN
Texto Completo: https://repositorio.ufrn.br/handle/123456789/44882
Resumo: Monoethylene glycol (MEG) is a gas hydrate inhibitor widely applied for natural gas flow assurance. A series of density and electrical conductivity measurements of water + MEG + NaCl mixtures are reported, allowing the supervision of the MEG regeneration unit. Density (509 data points) and electrical conductivity (212 data points) measurements were performed in wide ranges of temperature, T = 278.15−363.15 K, and concentration of solvents and NaCl up to almost saturation. The theory of solutions was applied for density description using excess volume, which was correlated with the Redlich−Kister equation. The resulting absolute and relative mean deviations are 0.00127 g·cm−3 and 0.12%, indicating accurate representation. A semi- empirical correlation with 15 adjustable parameters was considered for electrical conductivity of water + MEG + NaCl mixtures. The obtained absolute and relative mean deviations are 1.49 mS·cm−1 and 5.70%. The properties functions presented an approximately orthogonal behavior to each other, allowing the determination of mixture composition from experimental density and electrical conductivity data. The Matlab environment was found to be robust in solving the nonlinear system of two equations with constraints. The proposed methodology was extensively tested, and deviations less than 0.0060 and 0.0011 in solvents and NaCl mass fractions were obtained, respectively, demonstrating the required accuracy for industrial application
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spelling Chiavone Filho, OsvaldoMoura Neto, Mário Hermes deMonteiro, Mateus FernandesFerreira, Fedra A. V.Silva, Dannielle JanainneFigueiredo, Camila S.Ciambelli, João Rafael PerroniPereira, Leonardo S.Nascimento, Jailton Ferreira do2021-11-10T21:33:54Z2021-11-10T21:33:54Z2021-04-09MOURA-NETO, MARIO H.; MONTEIRO, Mateus Fernandes; FERREIRA, F. A. S. V. M. ; SILVA, D. J. ; FIGUEIREDO, C. S. ; CIAMBELLI, J. R. P. ; PEREIRA, L. S. ; DO NASCIMENTO, JAILTON FERREIRA ; CHIAVONE-FILHO, O. . Density and Electrical Conductivity for Aqueous Mixtures of Monoethylene Glycol and Sodium Chloride: Experimental Data and Data?driven Modeling for Composition Determination. JOURNAL OF CHEMICAL AND ENGINEERING DATA, v. 66, p. 1-15, 2021. Disponível em: https://pubs.acs.org/doi/10.1021/acs.jced.0c00962. Acesso em: 16 jun. 2021.https://doi.org/10.1021/acs.jced.0c00962.0021-95681520-5134https://repositorio.ufrn.br/handle/123456789/4488210.1021/acs.jced.0c00962ACS PublicationsAttribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessDensity and Electrical ConductivityMonoethylene GlycolData-DrivenComposition DeterminationDensity and electrical conductivity for aqueous mixtures of monoethylene glycol and sodium chloride: experimental data and data-driven modeling for composition determinationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleMonoethylene glycol (MEG) is a gas hydrate inhibitor widely applied for natural gas flow assurance. A series of density and electrical conductivity measurements of water + MEG + NaCl mixtures are reported, allowing the supervision of the MEG regeneration unit. Density (509 data points) and electrical conductivity (212 data points) measurements were performed in wide ranges of temperature, T = 278.15−363.15 K, and concentration of solvents and NaCl up to almost saturation. The theory of solutions was applied for density description using excess volume, which was correlated with the Redlich−Kister equation. The resulting absolute and relative mean deviations are 0.00127 g·cm−3 and 0.12%, indicating accurate representation. A semi- empirical correlation with 15 adjustable parameters was considered for electrical conductivity of water + MEG + NaCl mixtures. The obtained absolute and relative mean deviations are 1.49 mS·cm−1 and 5.70%. The properties functions presented an approximately orthogonal behavior to each other, allowing the determination of mixture composition from experimental density and electrical conductivity data. The Matlab environment was found to be robust in solving the nonlinear system of two equations with constraints. The proposed methodology was extensively tested, and deviations less than 0.0060 and 0.0011 in solvents and NaCl mass fractions were obtained, respectively, demonstrating the required accuracy for industrial applicationengreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8811https://repositorio.ufrn.br/bitstream/123456789/44882/2/license_rdfe39d27027a6cc9cb039ad269a5db8e34MD52ORIGINALDensityElectricalConductivity_ChiavoneFilho_2021.pdfDensityElectricalConductivity_ChiavoneFilho_2021.pdfapplication/pdf5083796https://repositorio.ufrn.br/bitstream/123456789/44882/1/DensityElectricalConductivity_ChiavoneFilho_2021.pdf52b295beda69d488438626263c515b7cMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81484https://repositorio.ufrn.br/bitstream/123456789/44882/3/license.txte9597aa2854d128fd968be5edc8a28d9MD53123456789/448822021-11-12 11:29:18.127oai:https://repositorio.ufrn.br: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Repositório de PublicaçõesPUBhttp://repositorio.ufrn.br/oai/opendoar:2021-11-12T14:29:18Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false
dc.title.pt_BR.fl_str_mv Density and electrical conductivity for aqueous mixtures of monoethylene glycol and sodium chloride: experimental data and data-driven modeling for composition determination
title Density and electrical conductivity for aqueous mixtures of monoethylene glycol and sodium chloride: experimental data and data-driven modeling for composition determination
spellingShingle Density and electrical conductivity for aqueous mixtures of monoethylene glycol and sodium chloride: experimental data and data-driven modeling for composition determination
Chiavone Filho, Osvaldo
Density and Electrical Conductivity
Monoethylene Glycol
Data-Driven
Composition Determination
title_short Density and electrical conductivity for aqueous mixtures of monoethylene glycol and sodium chloride: experimental data and data-driven modeling for composition determination
title_full Density and electrical conductivity for aqueous mixtures of monoethylene glycol and sodium chloride: experimental data and data-driven modeling for composition determination
title_fullStr Density and electrical conductivity for aqueous mixtures of monoethylene glycol and sodium chloride: experimental data and data-driven modeling for composition determination
title_full_unstemmed Density and electrical conductivity for aqueous mixtures of monoethylene glycol and sodium chloride: experimental data and data-driven modeling for composition determination
title_sort Density and electrical conductivity for aqueous mixtures of monoethylene glycol and sodium chloride: experimental data and data-driven modeling for composition determination
author Chiavone Filho, Osvaldo
author_facet Chiavone Filho, Osvaldo
Moura Neto, Mário Hermes de
Monteiro, Mateus Fernandes
Ferreira, Fedra A. V.
Silva, Dannielle Janainne
Figueiredo, Camila S.
Ciambelli, João Rafael Perroni
Pereira, Leonardo S.
Nascimento, Jailton Ferreira do
author_role author
author2 Moura Neto, Mário Hermes de
Monteiro, Mateus Fernandes
Ferreira, Fedra A. V.
Silva, Dannielle Janainne
Figueiredo, Camila S.
Ciambelli, João Rafael Perroni
Pereira, Leonardo S.
Nascimento, Jailton Ferreira do
author2_role author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Chiavone Filho, Osvaldo
Moura Neto, Mário Hermes de
Monteiro, Mateus Fernandes
Ferreira, Fedra A. V.
Silva, Dannielle Janainne
Figueiredo, Camila S.
Ciambelli, João Rafael Perroni
Pereira, Leonardo S.
Nascimento, Jailton Ferreira do
dc.subject.por.fl_str_mv Density and Electrical Conductivity
Monoethylene Glycol
Data-Driven
Composition Determination
topic Density and Electrical Conductivity
Monoethylene Glycol
Data-Driven
Composition Determination
description Monoethylene glycol (MEG) is a gas hydrate inhibitor widely applied for natural gas flow assurance. A series of density and electrical conductivity measurements of water + MEG + NaCl mixtures are reported, allowing the supervision of the MEG regeneration unit. Density (509 data points) and electrical conductivity (212 data points) measurements were performed in wide ranges of temperature, T = 278.15−363.15 K, and concentration of solvents and NaCl up to almost saturation. The theory of solutions was applied for density description using excess volume, which was correlated with the Redlich−Kister equation. The resulting absolute and relative mean deviations are 0.00127 g·cm−3 and 0.12%, indicating accurate representation. A semi- empirical correlation with 15 adjustable parameters was considered for electrical conductivity of water + MEG + NaCl mixtures. The obtained absolute and relative mean deviations are 1.49 mS·cm−1 and 5.70%. The properties functions presented an approximately orthogonal behavior to each other, allowing the determination of mixture composition from experimental density and electrical conductivity data. The Matlab environment was found to be robust in solving the nonlinear system of two equations with constraints. The proposed methodology was extensively tested, and deviations less than 0.0060 and 0.0011 in solvents and NaCl mass fractions were obtained, respectively, demonstrating the required accuracy for industrial application
publishDate 2021
dc.date.accessioned.fl_str_mv 2021-11-10T21:33:54Z
dc.date.available.fl_str_mv 2021-11-10T21:33:54Z
dc.date.issued.fl_str_mv 2021-04-09
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.citation.fl_str_mv MOURA-NETO, MARIO H.; MONTEIRO, Mateus Fernandes; FERREIRA, F. A. S. V. M. ; SILVA, D. J. ; FIGUEIREDO, C. S. ; CIAMBELLI, J. R. P. ; PEREIRA, L. S. ; DO NASCIMENTO, JAILTON FERREIRA ; CHIAVONE-FILHO, O. . Density and Electrical Conductivity for Aqueous Mixtures of Monoethylene Glycol and Sodium Chloride: Experimental Data and Data?driven Modeling for Composition Determination. JOURNAL OF CHEMICAL AND ENGINEERING DATA, v. 66, p. 1-15, 2021. Disponível em: https://pubs.acs.org/doi/10.1021/acs.jced.0c00962. Acesso em: 16 jun. 2021.https://doi.org/10.1021/acs.jced.0c00962.
dc.identifier.uri.fl_str_mv https://repositorio.ufrn.br/handle/123456789/44882
dc.identifier.issn.none.fl_str_mv 0021-9568
1520-5134
dc.identifier.doi.none.fl_str_mv 10.1021/acs.jced.0c00962
identifier_str_mv MOURA-NETO, MARIO H.; MONTEIRO, Mateus Fernandes; FERREIRA, F. A. S. V. M. ; SILVA, D. J. ; FIGUEIREDO, C. S. ; CIAMBELLI, J. R. P. ; PEREIRA, L. S. ; DO NASCIMENTO, JAILTON FERREIRA ; CHIAVONE-FILHO, O. . Density and Electrical Conductivity for Aqueous Mixtures of Monoethylene Glycol and Sodium Chloride: Experimental Data and Data?driven Modeling for Composition Determination. JOURNAL OF CHEMICAL AND ENGINEERING DATA, v. 66, p. 1-15, 2021. Disponível em: https://pubs.acs.org/doi/10.1021/acs.jced.0c00962. Acesso em: 16 jun. 2021.https://doi.org/10.1021/acs.jced.0c00962.
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