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A fracture mechanics-based fatigue reliability analysis of a submarine pipeline is investigated using the Bayesian approach. The proposed framework enables the estimation of the reliability level of submarine pipelines based on limited experimental data. Bayesian updating method and Markov Chain Monte Carlo simulation are used to estimate the posterior distribution of the parameters of a fracture mechanics-based fatigue model regarding different sources of uncertainties. Failure load cycle distribution and the reliability-based performance assessment of API 5L X56 submarine pipelines as a case study are estimated for three different cases. In addition, the impact of different parameters, including the stress ratio, maximum load, uncertainties of stress range and initial crack size, corrosion-enhanced factor, and also the correlation between material parameters on the reliability of the investigated submarine pipeline has been indicated through a sensitivity study. The applied approach in this study may be used for uncertainty modelling and fatigue reliability-based performance assessment of different types of submarine pipelines for maintenance and periodic inspection planning. [ABSTRACT FROM AUTHOR]

The aim of this paper is to characterise the fatigue reliability for various random strain loads under extreme value distribution while considering the cycle sequence effect condition in fatigue life prediction. The established strain–life models, i.e., Morrow and Smith–Watson–Topper, considered a mean stress effect and strain amplitude; nevertheless, it excluded the load sequence effect, which involves the fatigue crack closure that is subjected to overload or underload. A FESEM-EDX analysis is conducted to characterise the failure features that occurred on the leaf spring. A finite element is simulated to determine the critical region in order to obtain the strain load behaviour. In addition, the strain signal is captured experimentally at 500 Hz for 100 s under operating conditions for three different road loads based on the critical location obtained from the finite element analysis. The fatigue life correlation shows that the Pearson correlation coefficients are greater than 0.9, which indicates the effective strain damage model is linearly correlated with the strain–life models. The fatigue life data are modelled using extreme value distribution by considering the random strain loads as extreme data. The reliability rate for the fatigue life is reported to be more than 0.59 within the hazard rate range of 9.6 × 10−8 to 1.2 × 10−7 based on the mean cycle to the failure point. Hence, the effective strain damage model is proposed for a fatigue reliability assessment under extreme conditions with higher reliability and provides fatigue life prediction when subjected to cycle sequence effects. [ABSTRACT FROM AUTHOR]