Artificial Neural Networks for Producing a Low-Cost Austempered Ductile Iron
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Materials research (São Carlos. Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-14392022000100391 |
Resumo: | Two artificial neural networks (ANNs) were developed for producing an austempered ductile iron (ADI) with low-cost chemical composition and mechanical properties as per ASTMA897/897M-16-grade-1050/750/07 standard. Thus, the first ANN predicted the chemical composition range within the lowest cost and required mechanical properties. Next, in the second ANN, the resulting values from the first ANN were refined considering the target chemical composition suggested in the standard. Moreover, mechanical properties and microstructural analyses were undertaken in the ADI produced to support the ANNs’ findings. Hence, ANNs can be used to make a standard-compliant ADI and achieve cost savings. |
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Materials research (São Carlos. Online) |
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Artificial Neural Networks for Producing a Low-Cost Austempered Ductile IronAustempered ductile ironArtificial neural networkMechanical propertiesCost-savingsTwo artificial neural networks (ANNs) were developed for producing an austempered ductile iron (ADI) with low-cost chemical composition and mechanical properties as per ASTMA897/897M-16-grade-1050/750/07 standard. Thus, the first ANN predicted the chemical composition range within the lowest cost and required mechanical properties. Next, in the second ANN, the resulting values from the first ANN were refined considering the target chemical composition suggested in the standard. Moreover, mechanical properties and microstructural analyses were undertaken in the ADI produced to support the ANNs’ findings. Hence, ANNs can be used to make a standard-compliant ADI and achieve cost savings.ABM, ABC, ABPol2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-14392022000100391Materials Research v.25 2022reponame:Materials research (São Carlos. Online)instname:Universidade Federal de São Carlos (UFSCAR)instacron:ABM ABC ABPOL10.1590/1980-5373-mr-2022-0336info:eu-repo/semantics/openAccessHofmam,DiogoRamos,Fabiano DornellesLemos,Guilherme Vieira BragaLessa,Cleber Rodrigo de Limaeng2022-11-16T00:00:00Zoai:scielo:S1516-14392022000100391Revistahttp://www.scielo.br/mrPUBhttps://old.scielo.br/oai/scielo-oai.phpdedz@power.ufscar.br1980-53731516-1439opendoar:2022-11-16T00:00Materials research (São Carlos. Online) - Universidade Federal de São Carlos (UFSCAR)false |
dc.title.none.fl_str_mv |
Artificial Neural Networks for Producing a Low-Cost Austempered Ductile Iron |
title |
Artificial Neural Networks for Producing a Low-Cost Austempered Ductile Iron |
spellingShingle |
Artificial Neural Networks for Producing a Low-Cost Austempered Ductile Iron Hofmam,Diogo Austempered ductile iron Artificial neural network Mechanical properties Cost-savings |
title_short |
Artificial Neural Networks for Producing a Low-Cost Austempered Ductile Iron |
title_full |
Artificial Neural Networks for Producing a Low-Cost Austempered Ductile Iron |
title_fullStr |
Artificial Neural Networks for Producing a Low-Cost Austempered Ductile Iron |
title_full_unstemmed |
Artificial Neural Networks for Producing a Low-Cost Austempered Ductile Iron |
title_sort |
Artificial Neural Networks for Producing a Low-Cost Austempered Ductile Iron |
author |
Hofmam,Diogo |
author_facet |
Hofmam,Diogo Ramos,Fabiano Dornelles Lemos,Guilherme Vieira Braga Lessa,Cleber Rodrigo de Lima |
author_role |
author |
author2 |
Ramos,Fabiano Dornelles Lemos,Guilherme Vieira Braga Lessa,Cleber Rodrigo de Lima |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Hofmam,Diogo Ramos,Fabiano Dornelles Lemos,Guilherme Vieira Braga Lessa,Cleber Rodrigo de Lima |
dc.subject.por.fl_str_mv |
Austempered ductile iron Artificial neural network Mechanical properties Cost-savings |
topic |
Austempered ductile iron Artificial neural network Mechanical properties Cost-savings |
description |
Two artificial neural networks (ANNs) were developed for producing an austempered ductile iron (ADI) with low-cost chemical composition and mechanical properties as per ASTMA897/897M-16-grade-1050/750/07 standard. Thus, the first ANN predicted the chemical composition range within the lowest cost and required mechanical properties. Next, in the second ANN, the resulting values from the first ANN were refined considering the target chemical composition suggested in the standard. Moreover, mechanical properties and microstructural analyses were undertaken in the ADI produced to support the ANNs’ findings. Hence, ANNs can be used to make a standard-compliant ADI and achieve cost savings. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 |
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=S1516-14392022000100391 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-14392022000100391 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1980-5373-mr-2022-0336 |
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 |
ABM, ABC, ABPol |
publisher.none.fl_str_mv |
ABM, ABC, ABPol |
dc.source.none.fl_str_mv |
Materials Research v.25 2022 reponame:Materials research (São Carlos. Online) instname:Universidade Federal de São Carlos (UFSCAR) instacron:ABM ABC ABPOL |
instname_str |
Universidade Federal de São Carlos (UFSCAR) |
instacron_str |
ABM ABC ABPOL |
institution |
ABM ABC ABPOL |
reponame_str |
Materials research (São Carlos. Online) |
collection |
Materials research (São Carlos. Online) |
repository.name.fl_str_mv |
Materials research (São Carlos. Online) - Universidade Federal de São Carlos (UFSCAR) |
repository.mail.fl_str_mv |
dedz@power.ufscar.br |
_version_ |
1754212681755131904 |