Improved Pre-Strain Method for Generating Goodman Data with Vibration-Based Fatigue Testing

Abstract

Generating Goodman data via vibration fatigue testing is demonstrated in this study. Empirical Goodman data is acquired using a two-fold procedure: first, a pre-strain method is used to generate steady stress; second, the vibration-based fatigue testing methodology is employed to determine failure life cycles. Using this two-fold approach to ascertain Goodman line behavior is a cost effective method (less time than standard axial test and cheaper than component testing) for understanding high cycle fatigue (HCF) characteristics. The vibration-based test also provides both a stress state and operating frequency that better represent possible airfoil HCF conditions in gas turbine engines than conventional axial fatigue tests. The goal of this work is to improve the finite element model (FEM) analysis associated with the pre-strain method for more accurate steady stress assessment. Improvements will be made to the FEM by incorporating empirical hardening effects, pressures, and forces acting on the vibration-based specimen during localized monotonic loading. Validations for improvements to the pre-strain steady stress generation method will be demonstrated on Aluminum 6061-T6 by comparing strain field results from digital image correlation (DIC) and strain gage to FEM analysis.