Data-Driven Method for Predicting S-N Curve Based on Structurally Sensitive Fatigue Parameters

Under cyclic loading, almost immediately after its onset, a surface layer forms where hardening and softening processes occur. The interaction of plastic deformation traces with each other, and with other structural elements, leads to the formation of a characteristic microstructure on the surface of a component subjected to cyclic loading. The set of factors (conditions) acting during cyclic loading determines the nature of slip band accumulation, the integral structurally sensitive fatigue parameter, expressed as the slope of the left side of the fatigue curve linearized in logarithmic coordinates, and the location of the breaking point on the fatigue curve in the high-cycle region. A combined review of numerous data on the fatigue of metals, obtained under various combinations of factors, and the generalization of these results through a normalization procedure for obtaining the relative (recalculated) parameters of fatigue, allows us to derive a universal method for “S-N” curve prediction. However, extensive generalization decreases the prediction accuracy for specific cases; therefore, it is proposed to form limited generalized dependencies corresponding to specific operating conditions. This paper evaluates the accuracy of fatigue limit prediction using generalized and limited-generalized relationships of fatigue recalculated parameters for various fatigue curves obtained from independent experimental data.