A specialized genetic algorithm for the electrical impedance tomography of two-phase flows

Detalhes bibliográficos
Autor(a) principal: Rolnik,Vanessa P.
Data de Publicação: 2006
Outros Autores: Seleghim Jr.,Paulo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782006000400002
Resumo: The main objective of this work is to contribute to the development of a new tomographic reconstruction method well suited for processing signals obtained from electrical or other soft sensing field probes. The adopted approach consists in formulating the reconstruction problem in terms of an error function, which assesses the difference between a prospective and the actual internal contrast distribution (3D image), and searching for its minimum with the help of a specialized genetic algorithm (GA). Numerical simulations have been performed to demonstrate the feasibility of the proposed reconstruction method, as well as to emphasize the relation between the ill-posed nature of the problem and the topology of the minimization hyper-surface, and the importance of considering this relation when designing the numerical solution procedure. Results show that convergence is greatly enhanced when a priori information is introduced in the error function.
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spelling A specialized genetic algorithm for the electrical impedance tomography of two-phase flowsElectrical impedance tomographygenetic algorithminverse problemoptimizationmultiphase-flowThe main objective of this work is to contribute to the development of a new tomographic reconstruction method well suited for processing signals obtained from electrical or other soft sensing field probes. The adopted approach consists in formulating the reconstruction problem in terms of an error function, which assesses the difference between a prospective and the actual internal contrast distribution (3D image), and searching for its minimum with the help of a specialized genetic algorithm (GA). Numerical simulations have been performed to demonstrate the feasibility of the proposed reconstruction method, as well as to emphasize the relation between the ill-posed nature of the problem and the topology of the minimization hyper-surface, and the importance of considering this relation when designing the numerical solution procedure. Results show that convergence is greatly enhanced when a priori information is introduced in the error function.Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM2006-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782006000400002Journal of the Brazilian Society of Mechanical Sciences and Engineering v.28 n.4 2006reponame:Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online)instname:Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM)instacron:ABCM10.1590/S1678-58782006000400002info:eu-repo/semantics/openAccessRolnik,Vanessa P.Seleghim Jr.,Pauloeng2007-10-08T00:00:00Zoai:scielo:S1678-58782006000400002Revistahttps://www.scielo.br/j/jbsmse/https://old.scielo.br/oai/scielo-oai.php||abcm@abcm.org.br1806-36911678-5878opendoar:2007-10-08T00:00Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) - Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM)false
dc.title.none.fl_str_mv A specialized genetic algorithm for the electrical impedance tomography of two-phase flows
title A specialized genetic algorithm for the electrical impedance tomography of two-phase flows
spellingShingle A specialized genetic algorithm for the electrical impedance tomography of two-phase flows
Rolnik,Vanessa P.
Electrical impedance tomography
genetic algorithm
inverse problem
optimization
multiphase-flow
title_short A specialized genetic algorithm for the electrical impedance tomography of two-phase flows
title_full A specialized genetic algorithm for the electrical impedance tomography of two-phase flows
title_fullStr A specialized genetic algorithm for the electrical impedance tomography of two-phase flows
title_full_unstemmed A specialized genetic algorithm for the electrical impedance tomography of two-phase flows
title_sort A specialized genetic algorithm for the electrical impedance tomography of two-phase flows
author Rolnik,Vanessa P.
author_facet Rolnik,Vanessa P.
Seleghim Jr.,Paulo
author_role author
author2 Seleghim Jr.,Paulo
author2_role author
dc.contributor.author.fl_str_mv Rolnik,Vanessa P.
Seleghim Jr.,Paulo
dc.subject.por.fl_str_mv Electrical impedance tomography
genetic algorithm
inverse problem
optimization
multiphase-flow
topic Electrical impedance tomography
genetic algorithm
inverse problem
optimization
multiphase-flow
description The main objective of this work is to contribute to the development of a new tomographic reconstruction method well suited for processing signals obtained from electrical or other soft sensing field probes. The adopted approach consists in formulating the reconstruction problem in terms of an error function, which assesses the difference between a prospective and the actual internal contrast distribution (3D image), and searching for its minimum with the help of a specialized genetic algorithm (GA). Numerical simulations have been performed to demonstrate the feasibility of the proposed reconstruction method, as well as to emphasize the relation between the ill-posed nature of the problem and the topology of the minimization hyper-surface, and the importance of considering this relation when designing the numerical solution procedure. Results show that convergence is greatly enhanced when a priori information is introduced in the error function.
publishDate 2006
dc.date.none.fl_str_mv 2006-12-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782006000400002
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782006000400002
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1678-58782006000400002
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM
publisher.none.fl_str_mv Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM
dc.source.none.fl_str_mv Journal of the Brazilian Society of Mechanical Sciences and Engineering v.28 n.4 2006
reponame:Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online)
instname:Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM)
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instname_str Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM)
instacron_str ABCM
institution ABCM
reponame_str Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online)
collection Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online)
repository.name.fl_str_mv Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) - Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM)
repository.mail.fl_str_mv ||abcm@abcm.org.br
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