Statistical analysis of the influence of defects on fatigue life using a Gumbel distribution. (July 2018)

• Record Type: Journal Article
• Authors: Anderson, K.V.; Daniewicz, S.R.
• Is Part Of: International journal of fatigue. Volume 112(2018)
• Page Start: 78
• Page End: 83
• Publication Date: 2018-07
• Subjects: Fatigue crack growth -- Strip-yield model -- Statistics; Materials -- Fatigue -- Periodicals; Materials -- Fatigue; Periodicals; 620.1122
• DOI: 10.1016/j.ijfatigue.2018.03.008
• Languages: English
• ISSNs: 0142-1123

Abstract

Highlights: Location and scale parameters impact the mean and standard deviation of fatigue life. A modified strip-yield model reasonably approximates S-N curves. Initial crack sizes following a Gumbel distribution yield log-normal fatigue lives. Abstract: Location and scale parameters, λ and δ, of a Gumbel distribution are used to quantify defects in metallic materials. To determine the impact of these parameters on fatigue life performance and variability, fatigue crack growth simulations of 7075-T651 aluminum alloy were performed using a modified strip-yield model to produce S-N data. It was observed that defects representing initial crack lengths following a Gumbel distribution yield a fatigue life that follows a log-normal distribution. It was determined that location and scale parameters impact the fatigue life mean and standard deviation, but have little to no effect on the coefficient of variation.