A four-parameters model for fatigue crack growth data analysis
DOI:
https://doi.org/10.3221/IGF-ESIS.26.08Keywords:
Correlation modelAbstract
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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