Study of volume fractions for stratified and annular regime in multiphase flows using Gamma-Rays and artificial neural network

Detalhes bibliográficos
Autor(a) principal: SALGADO, César Marques
Data de Publicação: 2007
Outros Autores: BRANDÃO, Luis Eduardo Barreira, SCHIRRU, Roberto, PEREIRA, Cláudio Márcio do Nascimento Abreu, RAMOS, Robson, SILVA, Ademir Xavier da, http://lattes.cnpq.br/9316451931152992, http://lattes.cnpq.br/3694416401427409, http://lattes.cnpq.br/5766592315448911, http://lattes.cnpq.br/2341184189645578, http://lattes.cnpq.br/2568120215884387, http://lattes.cnpq.br/5706200091973418
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional do IEN
Texto Completo: http://carpedien.ien.gov.br:8080/handle/ien/1681
Resumo: This work presents methodology based on the use of nuclear technique and artificial intelligence for attainment of volume fractions in stratified and annular multiphase flow regime, oil-water-gas, very frequent in the offshore industry petroliferous. Using the principles of absorption and scattering of gamma-rays and an adequate geometry scheme of detection with two detectors and two energies measurement are gotten and they vary as changes in the volume fractions of flow regime occur. The MCNP-X code was used in order to provide the data training for artificial neural network that matched such information with the respective actual volume fractions of each material.
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spelling SALGADO, César MarquesBRANDÃO, Luis Eduardo BarreiraSCHIRRU, RobertoPEREIRA, Cláudio Márcio do Nascimento AbreuRAMOS, RobsonSILVA, Ademir Xavier dahttp://lattes.cnpq.br/9316451931152992http://lattes.cnpq.br/3694416401427409http://lattes.cnpq.br/5766592315448911http://lattes.cnpq.br/2341184189645578http://lattes.cnpq.br/2568120215884387http://lattes.cnpq.br/57062000919734182016-03-24T18:38:36Z2016-03-24T18:38:36Z2007http://carpedien.ien.gov.br:8080/handle/ien/1681Submitted by Sherillyn Lopes (sherillynmartins@yahoo.com.br) on 2016-03-24T18:38:36Z No. of bitstreams: 1 Study of volume fractions for stratified and annular.pdf: 121128 bytes, checksum: a0d19e843fc40ea61e9a175634ce073d (MD5)Made available in DSpace on 2016-03-24T18:38:36Z (GMT). No. of bitstreams: 1 Study of volume fractions for stratified and annular.pdf: 121128 bytes, checksum: a0d19e843fc40ea61e9a175634ce073d (MD5) Previous issue date: 2007This work presents methodology based on the use of nuclear technique and artificial intelligence for attainment of volume fractions in stratified and annular multiphase flow regime, oil-water-gas, very frequent in the offshore industry petroliferous. Using the principles of absorption and scattering of gamma-rays and an adequate geometry scheme of detection with two detectors and two energies measurement are gotten and they vary as changes in the volume fractions of flow regime occur. The MCNP-X code was used in order to provide the data training for artificial neural network that matched such information with the respective actual volume fractions of each material.engInstituto de Engenharia NuclearIENBrasilGamma-RaysArtificial Neural NetworksStudy of volume fractions for stratified and annular regime in multiphase flows using Gamma-Rays and artificial neural networkinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject2007info:eu-repo/semantics/openAccessreponame:Repositório Institucional do IENinstname:Instituto de Engenharia Nuclearinstacron:IENLICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://carpedien.ien.gov.br:8080/xmlui/bitstream/ien/1681/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52ORIGINALStudy of volume fractions for stratified and annular.pdfStudy of volume fractions for stratified and annular.pdfapplication/pdf121128http://carpedien.ien.gov.br:8080/xmlui/bitstream/ien/1681/1/Study+of+volume+fractions+for+stratified++and+annular.pdfa0d19e843fc40ea61e9a175634ce073dMD51ien/1681oai:carpedien.ien.gov.br:ien/16812016-03-24 15:38:36.352Dspace IENlsales@ien.gov.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
dc.title.pt_BR.fl_str_mv Study of volume fractions for stratified and annular regime in multiphase flows using Gamma-Rays and artificial neural network
title Study of volume fractions for stratified and annular regime in multiphase flows using Gamma-Rays and artificial neural network
spellingShingle Study of volume fractions for stratified and annular regime in multiphase flows using Gamma-Rays and artificial neural network
SALGADO, César Marques
Gamma-Rays
Artificial Neural Networks
title_short Study of volume fractions for stratified and annular regime in multiphase flows using Gamma-Rays and artificial neural network
title_full Study of volume fractions for stratified and annular regime in multiphase flows using Gamma-Rays and artificial neural network
title_fullStr Study of volume fractions for stratified and annular regime in multiphase flows using Gamma-Rays and artificial neural network
title_full_unstemmed Study of volume fractions for stratified and annular regime in multiphase flows using Gamma-Rays and artificial neural network
title_sort Study of volume fractions for stratified and annular regime in multiphase flows using Gamma-Rays and artificial neural network
author SALGADO, César Marques
author_facet SALGADO, César Marques
BRANDÃO, Luis Eduardo Barreira
SCHIRRU, Roberto
PEREIRA, Cláudio Márcio do Nascimento Abreu
RAMOS, Robson
SILVA, Ademir Xavier da
http://lattes.cnpq.br/9316451931152992
http://lattes.cnpq.br/3694416401427409
http://lattes.cnpq.br/5766592315448911
http://lattes.cnpq.br/2341184189645578
http://lattes.cnpq.br/2568120215884387
http://lattes.cnpq.br/5706200091973418
author_role author
author2 BRANDÃO, Luis Eduardo Barreira
SCHIRRU, Roberto
PEREIRA, Cláudio Márcio do Nascimento Abreu
RAMOS, Robson
SILVA, Ademir Xavier da
http://lattes.cnpq.br/9316451931152992
http://lattes.cnpq.br/3694416401427409
http://lattes.cnpq.br/5766592315448911
http://lattes.cnpq.br/2341184189645578
http://lattes.cnpq.br/2568120215884387
http://lattes.cnpq.br/5706200091973418
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv SALGADO, César Marques
BRANDÃO, Luis Eduardo Barreira
SCHIRRU, Roberto
PEREIRA, Cláudio Márcio do Nascimento Abreu
RAMOS, Robson
SILVA, Ademir Xavier da
http://lattes.cnpq.br/9316451931152992
http://lattes.cnpq.br/3694416401427409
http://lattes.cnpq.br/5766592315448911
http://lattes.cnpq.br/2341184189645578
http://lattes.cnpq.br/2568120215884387
http://lattes.cnpq.br/5706200091973418
dc.subject.por.fl_str_mv Gamma-Rays
Artificial Neural Networks
topic Gamma-Rays
Artificial Neural Networks
dc.description.abstract.por.fl_txt_mv This work presents methodology based on the use of nuclear technique and artificial intelligence for attainment of volume fractions in stratified and annular multiphase flow regime, oil-water-gas, very frequent in the offshore industry petroliferous. Using the principles of absorption and scattering of gamma-rays and an adequate geometry scheme of detection with two detectors and two energies measurement are gotten and they vary as changes in the volume fractions of flow regime occur. The MCNP-X code was used in order to provide the data training for artificial neural network that matched such information with the respective actual volume fractions of each material.
description This work presents methodology based on the use of nuclear technique and artificial intelligence for attainment of volume fractions in stratified and annular multiphase flow regime, oil-water-gas, very frequent in the offshore industry petroliferous. Using the principles of absorption and scattering of gamma-rays and an adequate geometry scheme of detection with two detectors and two energies measurement are gotten and they vary as changes in the volume fractions of flow regime occur. The MCNP-X code was used in order to provide the data training for artificial neural network that matched such information with the respective actual volume fractions of each material.
publishDate 2007
dc.date.issued.fl_str_mv 2007
dc.date.accessioned.fl_str_mv 2016-03-24T18:38:36Z
dc.date.available.fl_str_mv 2016-03-24T18:38:36Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
status_str publishedVersion
format conferenceObject
dc.identifier.uri.fl_str_mv http://carpedien.ien.gov.br:8080/handle/ien/1681
url http://carpedien.ien.gov.br:8080/handle/ien/1681
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Instituto de Engenharia Nuclear
dc.publisher.initials.fl_str_mv IEN
dc.publisher.country.fl_str_mv Brasil
publisher.none.fl_str_mv Instituto de Engenharia Nuclear
dc.source.none.fl_str_mv reponame:Repositório Institucional do IEN
instname:Instituto de Engenharia Nuclear
instacron:IEN
reponame_str Repositório Institucional do IEN
collection Repositório Institucional do IEN
instname_str Instituto de Engenharia Nuclear
instacron_str IEN
institution IEN
bitstream.url.fl_str_mv http://carpedien.ien.gov.br:8080/xmlui/bitstream/ien/1681/2/license.txt
http://carpedien.ien.gov.br:8080/xmlui/bitstream/ien/1681/1/Study+of+volume+fractions+for+stratified++and+annular.pdf
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repository.name.fl_str_mv Dspace IEN
repository.mail.fl_str_mv lsales@ien.gov.br
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