A unified statistical model for S-N fatigue curves: probabilistic definition

In recent years, experimental tests exploring the gigacycle fatigue properties of materials suggest the introduction of modifications in well known statistical fatigue life models. Usual fatigue life models, characterized by a single failure mechanism and by the presence of the fatigue limit, have been integrated by models that can take into account the occurrence of two failure mechanisms and do not consider the presence of the fatigue limit. The general case, in which more than two failure mechanisms coexist with the fatigue limit, has not been proposed yet. The paper presents a unified statistical model which can take into account any number of failure mechanisms and the possible presence of the fatigue limit. The case of S-N curves with different fatigue life distributions coexisting for the entire stress range covered by fatigue tests is also considered. The adaptability of the statistical model to the S-N curves proposed in the open literature is demonstrated by qualitative numerical example

A Reduced Order Life Prediction Modeling Approach For Materials Under Thermomechanical Fatigue

Low alloy steels remain to be the materials of choice for large structural components at elevated temperature for extended periods of time. The material 2.25Cr-1Mo is frequently used in boilers, heat exchanger tubes, and throttle valve bodies in both turbo machinery and pressure-vessel/piping applications alike. The resistance of this alloy to deformation and damage under creep and/or fatigue at elevated temperature make it suitable for components expected to endure decades of service. In the present work, a life prediction approach is developed for cases where the material is experiencing conditions where creep and fatigue exist. Parameters for the approach are based on regression fits in comparison with a broad collection experimental data. The data are comprised of low cycle fatigue (LCF) and creep fatigue (CF) experiments. The form of the life prediction model follows the cumulative damage approach where dominant damage maps can be used to identify primary micro structural mechanism associated with failure. The total damage is divided between three different modules in this approach: fatigue, creep, and environmental fatigue. Life calculations are facilitated by the usage of a non-interacting creep-plasticity constitutive model capable of representing not only the temperature-and rate-dependence, but also the history-dependence of the material