A four-parameters model for fatigue crack growth data analysis

A four-parameters model for interpolation of fatigue crack growth data is presented. It has been validated by means of both data produced by the Authors and data collected from Literature. The proposed model is an enhanced version of a three-parameters model already discussed in a previous work that...

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Main Authors: M. Grasso, F. Penta, P. Pinto, G.P. Pucillo
Format: Article
Language:English
Published: Gruppo Italiano Frattura 2013-09-01
Series:Fracture and Structural Integrity
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Online Access:https://www.fracturae.com/index.php/fis/article/view/1172
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author M. Grasso
F. Penta
P. Pinto
G.P. Pucillo
author_facet M. Grasso
F. Penta
P. Pinto
G.P. Pucillo
author_sort M. Grasso
collection DOAJ
description A four-parameters model for interpolation of fatigue crack growth data is presented. It has been validated by means of both data produced by the Authors and data collected from Literature. The proposed model is an enhanced version of a three-parameters model already discussed in a previous work that has been suitably modified in order to overcome some drawbacks raised when applied to a quite wider experimental data set. Results of validation study have also revealed that the new model, besides interpolating accurately crack growth data, allows to identify the presence of anomalies in the data sets. For this reason, by a suitable filter to be chosen depending on the size and number of anomalies, it can be used to remove them and obtain sigmoidal crack propagation curves smoother than those obtained when the current analysis techniques are used. In the end, possible model parameters correlations are analysed.
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institution Kabale University
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publisher Gruppo Italiano Frattura
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series Fracture and Structural Integrity
spelling doaj-art-a8f4d559d9a24d879fb38f2e3ddda8fc2024-12-02T05:48:16ZengGruppo Italiano FratturaFracture and Structural Integrity1971-89932013-09-01726A four-parameters model for fatigue crack growth data analysisM. GrassoF. PentaP. PintoG.P. PucilloA four-parameters model for interpolation of fatigue crack growth data is presented. It has been validated by means of both data produced by the Authors and data collected from Literature. The proposed model is an enhanced version of a three-parameters model already discussed in a previous work that has been suitably modified in order to overcome some drawbacks raised when applied to a quite wider experimental data set. Results of validation study have also revealed that the new model, besides interpolating accurately crack growth data, allows to identify the presence of anomalies in the data sets. For this reason, by a suitable filter to be chosen depending on the size and number of anomalies, it can be used to remove them and obtain sigmoidal crack propagation curves smoother than those obtained when the current analysis techniques are used. In the end, possible model parameters correlations are analysed.https://www.fracturae.com/index.php/fis/article/view/1172Correlation model
spellingShingle M. Grasso
F. Penta
P. Pinto
G.P. Pucillo
A four-parameters model for fatigue crack growth data analysis
Fracture and Structural Integrity
Correlation model
title A four-parameters model for fatigue crack growth data analysis
title_full A four-parameters model for fatigue crack growth data analysis
title_fullStr A four-parameters model for fatigue crack growth data analysis
title_full_unstemmed A four-parameters model for fatigue crack growth data analysis
title_short A four-parameters model for fatigue crack growth data analysis
title_sort four parameters model for fatigue crack growth data analysis
topic Correlation model
url https://www.fracturae.com/index.php/fis/article/view/1172
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AT fpenta afourparametersmodelforfatiguecrackgrowthdataanalysis
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AT gppucillo afourparametersmodelforfatiguecrackgrowthdataanalysis
AT mgrasso fourparametersmodelforfatiguecrackgrowthdataanalysis
AT fpenta fourparametersmodelforfatiguecrackgrowthdataanalysis
AT ppinto fourparametersmodelforfatiguecrackgrowthdataanalysis
AT gppucillo fourparametersmodelforfatiguecrackgrowthdataanalysis