Novel methods for microstructure-sensitive probabilistic fatigue notch factorReportar como inadecuado


Novel methods for microstructure-sensitive probabilistic fatigue notch factor


Novel methods for microstructure-sensitive probabilistic fatigue notch factor - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

An extensive review of probabilistic techniques in fatigue analysis indicates thatthere is a need for new microstructure-sensitive methods in describing the effectsof notches on the fatigue life reduction in cyclically loaded components. Of specialinterest are notched components made from polycrystalline nickel-base superalloys,which are used for high temperature applications in aircraft gas turbine engine disks.Microstructure-sensitive computational crystal plasticity is combined with novel probabilistictechniques to determine the probability of failure of notched componentsbased on the distribution of slip within the notch root region and small crack initiationprocesses. The key microstructure features of two Ni-base superalloys, a fine andcoarse grain IN100, are reviewed and the method in which these alloys are computationallymodeled is presented. Next, the geometric model of the notched specimensand method of finite element polycrystalline reconstruction is demonstrated. Shear-basedfatigue indicator parameters are used to characterize the shear-based, mode Iformation and propagation of fatigue cracks. Finally, two different probabilistic approachesare described in this work including a grain-scale approach, which describesthe probability of forming a crack on the order of grain size, and a transition cracklength approach, which describes the probability of forming and propagating a crackto the transition crack length. These approaches are used to construct cumulativedistribution functions for the probability of failure as a function of various notch rootsizes and strain load amplitudes.



Georgia Tech Theses and Dissertations - School of Mechanical Engineering Theses and Dissertations -



Autor: Musinski, William D. - -

Fuente: https://smartech.gatech.edu/







Documentos relacionados