Statistical modeling of fatigue crack growth rate in Inconel alloy 600.
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, us...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2007 |
| País: | Brasil |
| Institución: | Universidade Federal de Ouro Preto (UFOP) |
| Repositorio: | Repositório Institucional da UFOP |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.ufop.br:123456789/5498 |
| Acceso en línea: | http://www.repositorio.ufop.br/handle/123456789/5498 https://doi.org/10.1016/j.ijfatigue.2006.07.013 |
| Access Level: | acceso abierto |
| Palabra clave: | Inconel alloy 600 Fatigue crack growth rate Statistical modeling Nonlinear regression Model selection |
| Sumario: | 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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