This paper describes the development of methodology for a probabilistic material strength degradation model, that provides for quantification of uncertainty in the lifetime material strength of structural components of aerospace propulsion systems subjected to a number of diverse random effects. The model has most recently been extended to include thermal fatigue. The discussion of thermal fatigue, in the context of probabilistic material strength degradation, is the central feature of this paper. The methodology, for all effects, is embodied in two computer programs, PROMISS and PROMISC. These programs form a “material resistance” model that may be used in the aerospace structural reliability program, NESSUS or in other applications. A probabilistic material strength degradation model for thermal fatigue and other relevant effects, in the form of a postulated randomized multifactor interaction equation, is used to quantify lifetime material strength. Each multiplicative term in the model has the property that if the current value of an effect equals the ultimate value, then the lifetime strength will be zero. Also, if the current value of an effect equals the reference value, the term equals one and lifetime strength is not affected by that particular effect. Presently, the model includes up to four effects that typically reduce lifetime strength: high temperature, mechanical fatigue, creep and thermal fatigue. Statistical analysis of experimental data for Inconel 718 obtained from the open literature and laboratory reports is also included in the paper. The statistical analysis provided regression parameters for use as the model’s empirical material constants, thus calibrating the model specifically for Inconel 718. Model calibration was carried out for four variables, namely, high temperature, mechanical fatigue, creep and thermal fatigue. Finally, using the PROMISS computer program, a sensitivity study was performed with the calibrated random model to illustrate the effects of mechanical fatigue, creep and thermal fatigue, at about 1000 °F, upon random lifetime strength.
Investigation into Methods for Predicting Connection Temperatures
