Probabilistic modeling of fatigue related microstructural parameters in aluminum alloys

This paper presents the results of probabilistic modeling of the fatigue related microstructural parameters in unclad 2024-T351 aluminum sheets. The statistical distributions of the constituent particle size, which were obtained from metallographic measurements from polished surfaces, were determined by graphical goodness-of-fit tests. The distributions of the crack-nucleating particle sizes were determined using the data measured from various fatigue fracture surfaces. Initially, an extreme value theory based model was investigated to correlate the overall particle distribution with its fatigue subsets. Furthermore, a new Monte Carlo simulation was developed to determine the fatigue subsets using the microstructural parameters such as particle size, grain size, and grain orientation distributions, in association with qualitative criteria on fatigue crack nucleation and growth mechanisms.