Analytic roughness prediction by deep rolling
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFMG |
Texto Completo: | https://doi.org/10.1007/s11740-020-00961-0 http://hdl.handle.net/1843/57014 https://orcid.org/0000-0003-2015-4077 |
Resumo: | CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior |
id |
UFMG_93616ddf4136e65161e9709b0c7152f8 |
---|---|
oai_identifier_str |
oai:repositorio.ufmg.br:1843/57014 |
network_acronym_str |
UFMG |
network_name_str |
Repositório Institucional da UFMG |
repository_id_str |
|
spelling |
2023-07-26T17:22:08Z2023-07-26T17:22:08Z2020-04-30143345354https://doi.org/10.1007/s11740-020-00961-00944-6524http://hdl.handle.net/1843/57014https://orcid.org/0000-0003-2015-4077CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorDeep rolling is a widely applied mechanical surface and subsurface treatment method. It is typically used after conventional machining to improve the roughness, increase the surface hardness and to induce compressive residual stresses. The main influence parameters on the surface topography are the applied deep rolling pressure, the ball diameter and the feed. In general, low feeds, larger ball diameters and higher pressures result in an even surface finish. However, an exact prediction of the roughness is not possible. Therefore, it is the aim of the presented research to find a generally applicable method for surface roughness prediction after deep rolling for a variety of steel and aluminum materials. It is shown that the surface topography can be predicted by an analytical model with high accuracy.engUniversidade Federal de Minas GeraisUFMGBrasilENG - DEPARTAMENTO DE ENGENHARIA MECÂNICAENGENHARIA - ESCOLA DE ENGENHARIAProduction EngineeringEngenharia de Materiais e MetalúrgicaTestes de durezaTopografiaDeep rollingSurface topographyRoughnessRoller burnishingAnalytic roughness prediction by deep rollinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://link.springer.com/article/10.1007/s11740-020-00961-0B. DenkenaAlexandre Mendes AbraoA. KrödelKolja Meyerapplication/pdfinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGLICENSELicense.txtLicense.txttext/plain; charset=utf-82042https://repositorio.ufmg.br/bitstream/1843/57014/1/License.txtfa505098d172de0bc8864fc1287ffe22MD51ORIGINALAnalytic roughness prediction by deep rolling.pdfAnalytic roughness prediction by deep rolling.pdfapplication/pdf2538359https://repositorio.ufmg.br/bitstream/1843/57014/2/Analytic%20roughness%20prediction%20by%20deep%20rolling.pdfaefd39e9c443ccee904e8c9a8cce3876MD521843/570142023-07-26 14:22:08.141oai:repositorio.ufmg.br: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Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2023-07-26T17:22:08Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false |
dc.title.pt_BR.fl_str_mv |
Analytic roughness prediction by deep rolling |
title |
Analytic roughness prediction by deep rolling |
spellingShingle |
Analytic roughness prediction by deep rolling B. Denkena Deep rolling Surface topography Roughness Roller burnishing Engenharia de Materiais e Metalúrgica Testes de dureza Topografia |
title_short |
Analytic roughness prediction by deep rolling |
title_full |
Analytic roughness prediction by deep rolling |
title_fullStr |
Analytic roughness prediction by deep rolling |
title_full_unstemmed |
Analytic roughness prediction by deep rolling |
title_sort |
Analytic roughness prediction by deep rolling |
author |
B. Denkena |
author_facet |
B. Denkena Alexandre Mendes Abrao A. Krödel Kolja Meyer |
author_role |
author |
author2 |
Alexandre Mendes Abrao A. Krödel Kolja Meyer |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
B. Denkena Alexandre Mendes Abrao A. Krödel Kolja Meyer |
dc.subject.por.fl_str_mv |
Deep rolling Surface topography Roughness Roller burnishing |
topic |
Deep rolling Surface topography Roughness Roller burnishing Engenharia de Materiais e Metalúrgica Testes de dureza Topografia |
dc.subject.other.pt_BR.fl_str_mv |
Engenharia de Materiais e Metalúrgica Testes de dureza Topografia |
description |
CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior |
publishDate |
2020 |
dc.date.issued.fl_str_mv |
2020-04-30 |
dc.date.accessioned.fl_str_mv |
2023-07-26T17:22:08Z |
dc.date.available.fl_str_mv |
2023-07-26T17:22:08Z |
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/1843/57014 |
dc.identifier.doi.pt_BR.fl_str_mv |
https://doi.org/10.1007/s11740-020-00961-0 |
dc.identifier.issn.pt_BR.fl_str_mv |
0944-6524 |
dc.identifier.orcid.pt_BR.fl_str_mv |
https://orcid.org/0000-0003-2015-4077 |
url |
https://doi.org/10.1007/s11740-020-00961-0 http://hdl.handle.net/1843/57014 https://orcid.org/0000-0003-2015-4077 |
identifier_str_mv |
0944-6524 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Production Engineering |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Minas Gerais |
dc.publisher.initials.fl_str_mv |
UFMG |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
ENG - DEPARTAMENTO DE ENGENHARIA MECÂNICA ENGENHARIA - ESCOLA DE ENGENHARIA |
publisher.none.fl_str_mv |
Universidade Federal de Minas Gerais |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFMG instname:Universidade Federal de Minas Gerais (UFMG) instacron:UFMG |
instname_str |
Universidade Federal de Minas Gerais (UFMG) |
instacron_str |
UFMG |
institution |
UFMG |
reponame_str |
Repositório Institucional da UFMG |
collection |
Repositório Institucional da UFMG |
bitstream.url.fl_str_mv |
https://repositorio.ufmg.br/bitstream/1843/57014/1/License.txt https://repositorio.ufmg.br/bitstream/1843/57014/2/Analytic%20roughness%20prediction%20by%20deep%20rolling.pdf |
bitstream.checksum.fl_str_mv |
fa505098d172de0bc8864fc1287ffe22 aefd39e9c443ccee904e8c9a8cce3876 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG) |
repository.mail.fl_str_mv |
|
_version_ |
1801676912046637056 |