A New Finite Element Approach to Biaxial Fatigue Life Prediction in Gas Turbine Engine

Abstract

High cycle fatigue is the most common cause of failure in gas turbine engines. Different design tools have been developed to predict number of cycles to failure for a component subjected to fatigue loads. An energy-based fatigue life prediction framework was previously developed in recent research for prediction of axial and bending fatigue life at various stress ratios. The framework for the prediction of fatigue life via energy analysis was based on a new constitutive law, which states the following: the amount of energy required to fracture a material is constant. A finite element approach for uniaxial and bending fatigue was developed by authors based on this constitutive law. In this study, the energy expressions that construct the new constitutive law are integrated into minimum potential energy formulation to develop a new QUAD-4 finite element for fatigue life prediction. The newly developed QUAD-4 element is further modified to obtain a plate element. The Plate element can be used to model plates subjected to biaxial fatigue including bending loads. The new QUAD-4 element is benchmarked with previously developed uniaxial tension/compression finite element. The comparison of Finite element method (FEM) results to existing experimental fatigue data, verifies the new finite element development for fatigue life prediction. The final output of this finite element analysis is in the form of number of cycles to failure for each element in ascending or descending order. Therefore, the new finite element framework can predict the number of cycles to failure at each location in gas turbine engine structural components. The new finite element provides a very useful tool for fatigue life prediction in gas turbine engine components. The performance of the fatigue finite element is demonstrated by the fatigue life predictions from Al6061-T6 aluminum and Ti-6Al-4V. Results are compared with experimental results and analytical predictions.