Optimal Design of Experiments for Liquid–Liquid Equilibria Characterization via Semidefinite Programming
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/107314 https://doi.org/10.3390/pr7110834 |
Resumo: | Liquid–liquid equilibria (LLE) characterization is a task requiring considerable work and appreciable financial resources. Notable savings in time and effort can be achieved when the experimental plans use the methods of the optimal design of experiments that maximize the information obtained. To achieve this goal, a systematic optimization formulation based on Semidefinite Programming is proposed for finding optimal experimental designs for LLE studies carried out at constant pressure and temperature. The non-random two-liquid (NRTL) model is employed to represent species equilibria in both phases. This model, combined with mass balance relationships, provides a means of computing the sensitivities of the measurements to the parameters. To design the experiment, these sensitivities are calculated for a grid of candidate experiments in which initial mixture compositions are varied. The optimal design is found by maximizing criteria based on the Fisher Information Matrix (FIM). Three optimality criteria (D-, A- and E-optimal) are exemplified. The approach is demonstrated for two ternary systems where different sets of parameters are to be estimated. |
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Optimal Design of Experiments for Liquid–Liquid Equilibria Characterization via Semidefinite Programmingoptimal design of experimentsapproximate designssemidefinite programmingliquid–liquid equilibriaternary systemsLiquid–liquid equilibria (LLE) characterization is a task requiring considerable work and appreciable financial resources. Notable savings in time and effort can be achieved when the experimental plans use the methods of the optimal design of experiments that maximize the information obtained. To achieve this goal, a systematic optimization formulation based on Semidefinite Programming is proposed for finding optimal experimental designs for LLE studies carried out at constant pressure and temperature. The non-random two-liquid (NRTL) model is employed to represent species equilibria in both phases. This model, combined with mass balance relationships, provides a means of computing the sensitivities of the measurements to the parameters. To design the experiment, these sensitivities are calculated for a grid of candidate experiments in which initial mixture compositions are varied. The optimal design is found by maximizing criteria based on the Fisher Information Matrix (FIM). Three optimality criteria (D-, A- and E-optimal) are exemplified. The approach is demonstrated for two ternary systems where different sets of parameters are to be estimated.MDPI2019info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/107314http://hdl.handle.net/10316/107314https://doi.org/10.3390/pr7110834eng2227-9717Duarte, Belmiro P. M.Atkinson, Anthony C.Granjo, José F. O.Oliveira, Nuno M. C.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-03T09:49:56Zoai:estudogeral.uc.pt:10316/107314Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:23:41.113266Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Optimal Design of Experiments for Liquid–Liquid Equilibria Characterization via Semidefinite Programming |
title |
Optimal Design of Experiments for Liquid–Liquid Equilibria Characterization via Semidefinite Programming |
spellingShingle |
Optimal Design of Experiments for Liquid–Liquid Equilibria Characterization via Semidefinite Programming Duarte, Belmiro P. M. optimal design of experiments approximate designs semidefinite programming liquid–liquid equilibria ternary systems |
title_short |
Optimal Design of Experiments for Liquid–Liquid Equilibria Characterization via Semidefinite Programming |
title_full |
Optimal Design of Experiments for Liquid–Liquid Equilibria Characterization via Semidefinite Programming |
title_fullStr |
Optimal Design of Experiments for Liquid–Liquid Equilibria Characterization via Semidefinite Programming |
title_full_unstemmed |
Optimal Design of Experiments for Liquid–Liquid Equilibria Characterization via Semidefinite Programming |
title_sort |
Optimal Design of Experiments for Liquid–Liquid Equilibria Characterization via Semidefinite Programming |
author |
Duarte, Belmiro P. M. |
author_facet |
Duarte, Belmiro P. M. Atkinson, Anthony C. Granjo, José F. O. Oliveira, Nuno M. C. |
author_role |
author |
author2 |
Atkinson, Anthony C. Granjo, José F. O. Oliveira, Nuno M. C. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Duarte, Belmiro P. M. Atkinson, Anthony C. Granjo, José F. O. Oliveira, Nuno M. C. |
dc.subject.por.fl_str_mv |
optimal design of experiments approximate designs semidefinite programming liquid–liquid equilibria ternary systems |
topic |
optimal design of experiments approximate designs semidefinite programming liquid–liquid equilibria ternary systems |
description |
Liquid–liquid equilibria (LLE) characterization is a task requiring considerable work and appreciable financial resources. Notable savings in time and effort can be achieved when the experimental plans use the methods of the optimal design of experiments that maximize the information obtained. To achieve this goal, a systematic optimization formulation based on Semidefinite Programming is proposed for finding optimal experimental designs for LLE studies carried out at constant pressure and temperature. The non-random two-liquid (NRTL) model is employed to represent species equilibria in both phases. This model, combined with mass balance relationships, provides a means of computing the sensitivities of the measurements to the parameters. To design the experiment, these sensitivities are calculated for a grid of candidate experiments in which initial mixture compositions are varied. The optimal design is found by maximizing criteria based on the Fisher Information Matrix (FIM). Three optimality criteria (D-, A- and E-optimal) are exemplified. The approach is demonstrated for two ternary systems where different sets of parameters are to be estimated. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10316/107314 http://hdl.handle.net/10316/107314 https://doi.org/10.3390/pr7110834 |
url |
http://hdl.handle.net/10316/107314 https://doi.org/10.3390/pr7110834 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2227-9717 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
MDPI |
publisher.none.fl_str_mv |
MDPI |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799134123072159744 |