Application of the Effective critical plane approach for the fatigue assessment of ductile cast iron under multiaxial and non-proportional loading conditions

• The Effective Critical Plane (ECP) method improves fatigue life prediction of cast iron; • The method is validated under multiaxial, non-proportional loading conditions; • The method uses a single calibration parameter for fast and reliable fatigue assessment; • The computational efficiency makes ECP suitable for practical engineering applications. The fatigue assessment of structural components, especially made of ductile cast iron subjected to complex loading conditions, heavily relies on analyzing fatigue damage resulting from stress concentrations induced by geometric irregularities like notches and shrinkage pores. Standard methodologies, encompassing the Theory of Critical Distances (TCD), Strain Energy Density (SED), and Critical Plane (CP), have played pivotal roles in predicting fatigue strength for components featuring such irregularities. In this work, the authors explore the applicability of the Effective Critical Plane (ECP) approach on ductile cast iron notched specimens subjected to multiaxial and non-proportional loading conditions. The method focuses on evaluating the critical plane factor, after averaging the stress and strain field within a given control volume or area (i.e. defined by a control radius), centered on the critical node. The study aims to enhance the accuracy of fatigue life prediction for structural components made of ductile cast iron, thereby contributing to the improvement and practical applicability of fatigue assessment under complex loading conditions. The methodology, integrating the Smith-Watson-Topper and Fatemi-Socie CP factor, was applied to several experimental fatigue data obtained from ductile cast iron notched specimens, tested under multiaxial non-proportional loading conditions. After establishing the control radius associated with the investigated material, the method was utilized to perform a fatigue life forecast analysis on a specimen with porous defects.