Probabilistic fatigue models are required to account conveniently for the several sources of uncertainty arising in the prediction procedures, such as the scatter in material behavior. In this paper, a recently proposed stress-based probabilistic model is assessed using fatigue data available for the P355NL1 steel (a pressure vessel steel). The referred probabilistic model is a log-Gumbel regression model, able to predict the probabilistic Wo¨hler field (P-S-N field), taking into account the mean stress (or stress R-ratio) effects. The parameters of the probabilistic model are identified using stress-life data derived for the P355NL1 steel, from smooth specimens, for three distinct stress R-ratios, namely R = −1, R = −0.5 and R = 0. The model requires a minimum of two test series with distinct stress R-ratios. Since data from three test series is available, extrapolations are performed to test the adequacy of the model to make extrapolations for stress R-ratios other than those used in the model parameters assessment. Finally, the probabilistic model is used to model the fatigue behavior of a notched plate made of P355NL1 steel. In particular, the P-S-N field of the plate is modeled and compared with available experimental data. Cyclic elastoplastic analysis of the plate is performed since plasticity at the notch root is developed.

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