Fatigue Crack Propagation Rates Prediction Using Probabilistic Strain‐Based Models

This chapter proposes an evaluation and extension of the UniGrow model to predict the fatigue crack propagation rate, based on a local strain-based approach to fatigue. The UniGrow model, classified as a residual stress‐based crack propagation model, is here applied to derive probabilistic fatigue crack propagation fields (p-da/dN-ΔK-R fields) for P355NL1 pressure vessel steel, covering distinct stress R-ratios. The results are compared with available experimental data. The required strain-life data are experimentally achieved and evaluated. The material representative element size, ρ*, a key parameter in the UniGrow model, is assessed by means of a trial-and-error procedure of inverse analysis. Moreover, residual stresses are computed for varying crack lengths and minimum-to-maximum stress ratios. Elastoplastic stress fields around the crack apex are evaluated with analytical relations and compared with elastoplastic finite-element (FE) computations. The deterministic strain-life relations proposed in the original UniGrow model are replaced by the probabilistic strain‐life fields (p-ε-N) proposed by Castillo and Canteli. This probabilistic model is also extended by considering a damage parameter to allow for mean stress effects. In particular, a probabilistic Smith-Watson-Topper field (p-SWT-N), alternatively to the conventional p-ε-N field, is proposed and applied to derive the probabilistic fatigue crack propagation fields

A comparison between S-N Logistic and Kohout-Věchet formulations applied to the fatigue data of old metallic bridges materials

A new formulation of a Logistic deterministic S-N curve is applied to fatigue data of metallic materials from ancient Portuguese riveted steel bridges. This formulation is based on a modified logistic relation that uses three parameters to fit the low-cycle- (LCF), finite-life- and high-cycle-fatigue (HCF) regions. This model is compared to the Kohout-Věchet fatigue model, which has a refined adjustment from very low-cycle fatigue (VLCF) to very high-cycle fatigue (VHCF). These models are also compared with other models, such as, Power law and fatigue-life curve from the ASTM E739 standard. The modelling performance of the S-N curves was made using the fatigue data considering the stress fatigue damage parameter for the materials from the Eiffel, Luiz I, Fão and Trezói riveted steel bridges. Using a qualitative methodology of graphical adjustment analysis and another quantitative using the mean square error, it was possible to evaluate the performance of the mean S-N curve formulation. The results showed that the formulation of the S-N curve using the Logistic equation applied to the metallic materials from the old bridges obtained superior performance to the analysed models, both in the estimation of fatigue behaviour in the low-cycle fatigue (LCF) region and in the lowest mean square error

A procedure to obtain the probabilistic Kitagawa-Takahashi diagram

An alternative way of interpreting the Kitagawa-Takahashi diagram for structural components is proposed. With this aim, the equivalent initial flaw size (EIFS) model, as a way of defining the initial defects of the structural components is used in conjunction with the probabilistic S-N model proposed by Castillo and Canteli, thus allowing the probabilistic distribution of the EIFS to be generated and, consequently, a probabilistic definition of the KT diagram (P-KT) to be achieved. The proposed approach is applied to a notched plate made of P355NL1 steel, the results of predictions are analyzed and the deviations discussed