A Robust Optimization Technique for Calculating Scaling Coefficients in an Energy-Based Fatigue Life Prediction Method

The energy-based lifing method is based on the theory that the cumulative energy in all hysteresis loops of a specimens’ lifetime is equal to the energy in a monotonic tension test. Based on this theory, fatigue life can be calculated by dividing monotonic tensile energy by a hysteresis energy model, which is a function of stress amplitude. Due to variations in the empirically measured hysteresis loops and monotonic fracture area, fatigue life prediction with the energy-based method shows some variation as well. In order to account for these variations, a robust design optimization technique is employed. The robust optimization procedure uses an interval uncertainty technique, eliminating the need to know an exact probability density function for the uncertain parameters. The robust optimization framework ensures that the difference between the predicted lifetime at a given stress amplitude and the corresponding experimental fatigue data point is minimized and within a specified tolerance range while accounting for variations in hysteresis loop energy and fracture diameter measurements. Accounting for these experimental variations will boost confidence in the energy-based fatigue life prediction method despite a limited number of test specimens.