ABSTRACT
ABSTRACT: Various sources of uncertainty exist in fatigue crack growth analysis, such as variability in loading conditions, material parameters, experimental data, model uncertainty and unclear information in the modeling. The object of this paper is to present a methodology for fatigue damage prognosis under epistemic uncertainty. The parameters in fatigue crack growth model are obtained by fitting the available sparse experimental data and then the uncertainty in these parameters is taken into account. Evidence theory and differential evolution algorithm are proposed to characterize and propagate the epistemic uncertainty. The overall procedure is demonstrated using experimental data of Ti-6Al-4V aluminum alloy specimens. With comparison of probability theory and interval method, the computational efficiency and accuracy of this approach are also investigated.
