Statistical modeling of fatigue crack growth rate in Inconel alloy 600.
Autor(a) principal: | |
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Data de Publicação: | 2007 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFOP |
Texto Completo: | http://www.repositorio.ufop.br/handle/123456789/5498 https://doi.org/10.1016/j.ijfatigue.2006.07.013 |
Resumo: | Inconel alloy 600 is widely used in heat-treating industry, in chemical and food processing, in aeronautical industry, and in nuclear engineering. In this work, fatigue crack growth rate (FCGR) was evaluated in air and at room temperature under constant amplitude loading at a stress ratio of 0.1, using compact tension specimens. Collipriest and Priddle FCGR models were proposed to model the data. In addition, these models were modified to obtain a better fit to the data, especially in the near-threshold region. Akaike information criterion was used to select the candidate model that best approximates the real process given the data. The results showed that both Collipriest and Priddle models fit the FCGR data in a similar fashion. However, the Priddle model provided better fit than the Collipriest model. The modified Priddle model was found to be the most appropriate model for the data. |
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Al-Rubaie, Kassim Shamil FadhilGodefroid, Leonardo BarbosaLopes, Jadir Antônio Moreira2015-05-25T17:58:31Z2015-05-25T17:58:31Z2007AL-RUBAIE, K. S. F.; GODEFROID, L. B.; LOPES, J. A. M. Statistical modeling of fatigue crack growth rate in Inconel alloy 600. International Journal of Fatigue, v. 29, p. 931-940, 2007. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0142112306002295>. Acesso em: 09 abr. 2015.0142-1123http://www.repositorio.ufop.br/handle/123456789/5498https://doi.org/10.1016/j.ijfatigue.2006.07.013Inconel alloy 600 is widely used in heat-treating industry, in chemical and food processing, in aeronautical industry, and in nuclear engineering. In this work, fatigue crack growth rate (FCGR) was evaluated in air and at room temperature under constant amplitude loading at a stress ratio of 0.1, using compact tension specimens. Collipriest and Priddle FCGR models were proposed to model the data. In addition, these models were modified to obtain a better fit to the data, especially in the near-threshold region. Akaike information criterion was used to select the candidate model that best approximates the real process given the data. The results showed that both Collipriest and Priddle models fit the FCGR data in a similar fashion. However, the Priddle model provided better fit than the Collipriest model. The modified Priddle model was found to be the most appropriate model for the data.Inconel alloy 600Fatigue crack growth rateStatistical modelingNonlinear regressionModel selectionStatistical modeling of fatigue crack growth rate in Inconel alloy 600.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleO periódico International Journal of Fatigue concede permissão para depósito deste artigo no Repositório Institucional da UFOP. Número da licença: 3624210836520.info:eu-repo/semantics/openAccessengreponame:Repositório Institucional da UFOPinstname:Universidade Federal de Ouro Preto (UFOP)instacron:UFOPLICENSElicense.txtlicense.txttext/plain; charset=utf-82636http://www.repositorio.ufop.br/bitstream/123456789/5498/2/license.txtc2ffdd99e58acf69202dff00d361f23aMD52ORIGINALARTIGO_StatisticalModelingIconel.pdfARTIGO_StatisticalModelingIconel.pdfapplication/pdf964339http://www.repositorio.ufop.br/bitstream/123456789/5498/1/ARTIGO_StatisticalModelingIconel.pdf7e6200e00ed79ae02e0116ed27d0dcbaMD51123456789/54982019-07-26 09:43:34.535oai:localhost: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Repositório InstitucionalPUBhttp://www.repositorio.ufop.br/oai/requestrepositorio@ufop.edu.bropendoar:32332019-07-26T13:43:34Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)false |
dc.title.pt_BR.fl_str_mv |
Statistical modeling of fatigue crack growth rate in Inconel alloy 600. |
title |
Statistical modeling of fatigue crack growth rate in Inconel alloy 600. |
spellingShingle |
Statistical modeling of fatigue crack growth rate in Inconel alloy 600. Al-Rubaie, Kassim Shamil Fadhil Inconel alloy 600 Fatigue crack growth rate Statistical modeling Nonlinear regression Model selection |
title_short |
Statistical modeling of fatigue crack growth rate in Inconel alloy 600. |
title_full |
Statistical modeling of fatigue crack growth rate in Inconel alloy 600. |
title_fullStr |
Statistical modeling of fatigue crack growth rate in Inconel alloy 600. |
title_full_unstemmed |
Statistical modeling of fatigue crack growth rate in Inconel alloy 600. |
title_sort |
Statistical modeling of fatigue crack growth rate in Inconel alloy 600. |
author |
Al-Rubaie, Kassim Shamil Fadhil |
author_facet |
Al-Rubaie, Kassim Shamil Fadhil Godefroid, Leonardo Barbosa Lopes, Jadir Antônio Moreira |
author_role |
author |
author2 |
Godefroid, Leonardo Barbosa Lopes, Jadir Antônio Moreira |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Al-Rubaie, Kassim Shamil Fadhil Godefroid, Leonardo Barbosa Lopes, Jadir Antônio Moreira |
dc.subject.por.fl_str_mv |
Inconel alloy 600 Fatigue crack growth rate Statistical modeling Nonlinear regression Model selection |
topic |
Inconel alloy 600 Fatigue crack growth rate Statistical modeling Nonlinear regression Model selection |
description |
Inconel alloy 600 is widely used in heat-treating industry, in chemical and food processing, in aeronautical industry, and in nuclear engineering. In this work, fatigue crack growth rate (FCGR) was evaluated in air and at room temperature under constant amplitude loading at a stress ratio of 0.1, using compact tension specimens. Collipriest and Priddle FCGR models were proposed to model the data. In addition, these models were modified to obtain a better fit to the data, especially in the near-threshold region. Akaike information criterion was used to select the candidate model that best approximates the real process given the data. The results showed that both Collipriest and Priddle models fit the FCGR data in a similar fashion. However, the Priddle model provided better fit than the Collipriest model. The modified Priddle model was found to be the most appropriate model for the data. |
publishDate |
2007 |
dc.date.issued.fl_str_mv |
2007 |
dc.date.accessioned.fl_str_mv |
2015-05-25T17:58:31Z |
dc.date.available.fl_str_mv |
2015-05-25T17:58:31Z |
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.citation.fl_str_mv |
AL-RUBAIE, K. S. F.; GODEFROID, L. B.; LOPES, J. A. M. Statistical modeling of fatigue crack growth rate in Inconel alloy 600. International Journal of Fatigue, v. 29, p. 931-940, 2007. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0142112306002295>. Acesso em: 09 abr. 2015. |
dc.identifier.uri.fl_str_mv |
http://www.repositorio.ufop.br/handle/123456789/5498 |
dc.identifier.issn.none.fl_str_mv |
0142-1123 |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1016/j.ijfatigue.2006.07.013 |
identifier_str_mv |
AL-RUBAIE, K. S. F.; GODEFROID, L. B.; LOPES, J. A. M. Statistical modeling of fatigue crack growth rate in Inconel alloy 600. International Journal of Fatigue, v. 29, p. 931-940, 2007. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0142112306002295>. Acesso em: 09 abr. 2015. 0142-1123 |
url |
http://www.repositorio.ufop.br/handle/123456789/5498 https://doi.org/10.1016/j.ijfatigue.2006.07.013 |
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eng |
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eng |
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openAccess |
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