In real engineering applications, machine parts are rarely completely homogeneous; in most cases, there are at least some minor notch effects or even more extensive inhomogeneities, which cause critical local stress concentrations from which fatigue fractures develop. In the present research, a shift of the Coffin-Manson εa-N material curve in a structure with random porosity subjected to dynamic LCF loads was studied. This allows the rest of the fatigue life prediction process to remain the same as if it were a homogeneous material. Apart from the cyclic σ-ε curve, which is relatively easy to obtain experimentally, the εa-N curve is the second most important curve to describe the correlation between the fatigue life N and the strain level εa. Therefore, the correct shift of the εa-N curve of the homogeneous material to a position corresponding to the porous state of the material is crucial. We have found that the curve shift can be efficiently performed on the basis of numerical simulations of a combination of five porosity-specific geometric influences and the associated regression analysis. To model the modified synthetic εa-N curve, five geometric influences of porosity by X-ray or μ-CT analysis are quantified, and then the porosity-adjusted coefficients of the Coffin-Manson equation are calculated. The proposed approach has been successfully applied to standard specimens with different porosity topography.
Keywords: Coffin–Manson relationship; Taguchi; aluminium alloy; low-cycle fatigue; multivariate regression analysis; porosity.