High cycle fatigue characterization of a nickel-based superalloy based on a novel temperature-dependent regression method

Abstract

High cycle fatigue (HCF) at elevated temperatures is a very significant issue for superalloys commonly used in the field of gas turbine engines. However, nearly all the existing HCF S-N regression models are established irrespective of the temperature factor, which leads to the inconvenience of their application in multi-temperature HCF issues of superalloys. This paper proposes a HCF characterization method based on a novel regression model for the testing data at multiple temperatures. With the model, the HCF failure cycles can be obtained by a continuous function of the fatigue stress levels and temperatures. In order to verify the present method, a series of complete HCF tests for a nickel-based superalloy GH4169 within its typical service temperature range are conducted and numerous S-N data at various temperatures are obtained. The regression calculation and some prediction based on the present model are then carried out. It has been demonstrated that the present temperature-dependent regression method is well suitable for characterizing the HCF properties at elevated temperatures range. Based on the present method, the accuracy of HCF strength evaluation is really good. Especially, lifetime prediction by the present model is satisfied since that nearly all the data points comparing the prediction with the testing data fall within the scatter band with the error factor of three.