Prediction of Maximum Fatigue Indicator Parameters for Duplex Ti-6Al-4V Using Extreme Value Theory

Abstract

Fatigue Indicator Parameters (FIPs) based on the cyclic plastic strain are used as surrogate measures of the driving force for fatigue crack formation. For a given microstructure, the Extreme Value Distribution (EVD) of FIPs can be populated using results of a number of digital Statistical Volume Element (SVE) instantiations analyzed by the crystal plasticity finite element method. The number of microstructure instantiations affects the maximum FIPs computed. To predict the maximum FIPs in a large volume of material using simulation results from a limited number of SVEs, we proposed a statistical approach based on extreme value theory. The predicted maximum FIP values are compared directly to simulation results of 1000 SVEs to validate the proposed method for duplex Ti-6Al-4V. It is shown that simulations of only 100 SVEs suffice to identify the statistical information for a reliable prediction of the maximum FIPs in polycrystalline duplex Ti-6Al-4V with initial random texture.