Abstract
A statistical methodology for the assessment of high cycle fatigue failure probability is presented. Based on a probabilistic Haigh diagram for a unit volume in combination with a weakest link model, the approach allows failure probability quantification for arbitrarily shaped components. We demonstrate how the model can be calibrated using a maximum likelihood approach for censored data. In order to show its potential, the proposed methodology is applied on three different publicly available data sets containing tests for smooth and notched sheet specimens. In all considered cases the model predictions are in good agreement with the test data.
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