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spelling SALGADO, César MarquesBRANDÃO, Luis Eduardo BarreiraPEREIRA, Cláudio Márcio do Nascimento AbreuSALGADO, William L.SECICSERADDENNAPLICAÇÃO DE TÉCNICAS NUCLEARES NA INDÚSTRIA, SAÚDE E MEIO AMBIENTEotero@ien.gov.brbrandao@ien.gov.brcmnap@ien.gov.brwilliam.otero@hotmail.comhttp://lattes.cnpq.br/9316451931152992http://lattes.cnpq.br/3694416401427409http://lattes.cnpq.br/2341184189645578http://lattes.cnpq.br/32661987655001102014-06-19T02:58:36Z2014-06-19T02:58:36Z2014-09http://hdl.handle.net/ien/67410.1016/j.pnucene.2014.05.004Submitted by Lemos Marina (marinalemos@id.uff.br) on 2014-06-19T02:58:36Z No. of bitstreams: 0Made available in DSpace on 2014-06-19T02:58:36Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-09IEN-CNENIEN-CNENIEN-CNENIFRJhttp://www.sciencedirect.com/science/article/pii/S0149197014001231SALGADO, César M. et al. Salinity independent volume fraction prediction in annular and stratified (water–gas–oil) multiphase flows using artificial neural networks. Progress in Nuclear Energy, v. 76, p. 17-23, 2014.Salinity independent volume fractionMCNP-XArtificial neural networkGamma-raysSalinity independent volume fraction prediction in annular and stratified (water–gas–oil) multiphase flows using artificial neural networksinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleengreponame:Repositório Institucional do IENinstname:Instituto de Engenharia Nuclearinstacron:IENinfo:eu-repo/semantics/openAccessORIGINALSalinity independent volume.pdfSalinity independent volume.pdfapplication/pdf794061http://carpedien.ien.gov.br:8080/xmlui/bitstream/ien/674/2/Salinity+independent+volume.pdf9a8a5ef77e5566c8ee0e6270a25b68c2MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://carpedien.ien.gov.br:8080/xmlui/bitstream/ien/674/1/license.txt8a4605be74aa9ea9d79846c1fba20a33MD51ien/674oai:carpedien.ien.gov.br:ien/6742015-07-28 11:51:06.029Dspace IENlsales@ien.gov.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
dc.title.pt_BR.fl_str_mv Salinity independent volume fraction prediction in annular and stratified (water–gas–oil) multiphase flows using artificial neural networks
title Salinity independent volume fraction prediction in annular and stratified (water–gas–oil) multiphase flows using artificial neural networks
spellingShingle Salinity independent volume fraction prediction in annular and stratified (water–gas–oil) multiphase flows using artificial neural networks
SALGADO, César Marques
Salinity independent volume fraction
MCNP-X
Artificial neural network
Gamma-rays
title_short Salinity independent volume fraction prediction in annular and stratified (water–gas–oil) multiphase flows using artificial neural networks
title_full Salinity independent volume fraction prediction in annular and stratified (water–gas–oil) multiphase flows using artificial neural networks
title_fullStr Salinity independent volume fraction prediction in annular and stratified (water–gas–oil) multiphase flows using artificial neural networks
title_full_unstemmed Salinity independent volume fraction prediction in annular and stratified (water–gas–oil) multiphase flows using artificial neural networks
title_sort Salinity independent volume fraction prediction in annular and stratified (water–gas–oil) multiphase flows using artificial neural networks
author SALGADO, César Marques
author_facet SALGADO, César Marques
BRANDÃO, Luis Eduardo Barreira
PEREIRA, Cláudio Márcio do Nascimento Abreu
SALGADO, William L.
SECIC
SERAD
DENN
APLICAÇÃO DE TÉCNICAS NUCLEARES NA INDÚSTRIA, SAÚDE E MEIO AMBIENTE
otero@ien.gov.br
brandao@ien.gov.br
cmnap@ien.gov.br
william.otero@hotmail.com
http://lattes.cnpq.br/9316451931152992
http://lattes.cnpq.br/3694416401427409
http://lattes.cnpq.br/2341184189645578
http://lattes.cnpq.br/3266198765500110
author_role author
author2 BRANDÃO, Luis Eduardo Barreira
PEREIRA, Cláudio Márcio do Nascimento Abreu
SALGADO, William L.
SECIC
SERAD
DENN
APLICAÇÃO DE TÉCNICAS NUCLEARES NA INDÚSTRIA, SAÚDE E MEIO AMBIENTE
otero@ien.gov.br
brandao@ien.gov.br
cmnap@ien.gov.br
william.otero@hotmail.com
http://lattes.cnpq.br/9316451931152992
http://lattes.cnpq.br/3694416401427409
http://lattes.cnpq.br/2341184189645578
http://lattes.cnpq.br/3266198765500110
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv SALGADO, César Marques
BRANDÃO, Luis Eduardo Barreira
PEREIRA, Cláudio Márcio do Nascimento Abreu
SALGADO, William L.
SECIC
SERAD
DENN
APLICAÇÃO DE TÉCNICAS NUCLEARES NA INDÚSTRIA, SAÚDE E MEIO AMBIENTE
otero@ien.gov.br
brandao@ien.gov.br
cmnap@ien.gov.br
william.otero@hotmail.com
http://lattes.cnpq.br/9316451931152992
http://lattes.cnpq.br/3694416401427409
http://lattes.cnpq.br/2341184189645578
http://lattes.cnpq.br/3266198765500110
dc.subject.other.pt_BR.fl_str_mv Salinity independent volume fraction
MCNP-X
Artificial neural network
Gamma-rays
topic Salinity independent volume fraction
MCNP-X
Artificial neural network
Gamma-rays
dc.description.affilliation.fl_txt_mv IEN-CNEN
IEN-CNEN
IEN-CNEN
IFRJ
description IEN-CNEN
publishDate 2014
dc.date.accessioned.fl_str_mv 2014-06-19T02:58:36Z
dc.date.available.fl_str_mv 2014-06-19T02:58:36Z
dc.date.issued.fl_str_mv 2014-09
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
status_str publishedVersion
format article
dc.identifier.uri.fl_str_mv http://hdl.handle.net/ien/674
dc.identifier.doi.none.fl_str_mv 10.1016/j.pnucene.2014.05.004
url http://hdl.handle.net/ien/674
identifier_str_mv 10.1016/j.pnucene.2014.05.004
dc.language.iso.fl_str_mv eng
language eng
dc.relation.uri.pt_BR.fl_str_mv http://www.sciencedirect.com/science/article/pii/S0149197014001231
dc.relation.references.pt_BR.fl_str_mv SALGADO, César M. et al. Salinity independent volume fraction prediction in annular and stratified (water–gas–oil) multiphase flows using artificial neural networks. Progress in Nuclear Energy, v. 76, p. 17-23, 2014.
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.source.none.fl_str_mv reponame:Repositório Institucional do IEN
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