Abstract
A new cohesive fatigue model (CF22) is proposed after an extensive characterization of experimental data. To minimize the number of parameters required, experimental Paris law data is transformed into a plot of amplitude versus mean relative endurance, where the data is fit using an empirical function. This novel characterization procedure helps identify trends and inconsistencies in the data and provides the values of the model input parameters without requiring inverse analyses. The new fatigue model significantly improves the predictions of crack propagation rates and thresholds compared to CF20, especially under conditions of high stress ratios and high values of mode mixity.
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