Estimations of fatigue life and variability under random loading in aluminum Al-2024T351 using strip yield models from NASGRO. (October 2016)

• Record Type: Journal Article
• Authors: Moreno, B.; Martin, A.; Lopez-Crespo, P.; Zapatero, J.; Dominguez, J.
• Is Part Of: International journal of fatigue. Volume 91: Part 2(2016)
• Page Start: 414
• Page End: 422
• Publication Date: 2016-10
• Subjects: Random loading -- Strip yield model -- NASGRO software -- Aluminum alloy 2024-T351; Materials -- Fatigue -- Periodicals; Materials -- Fatigue; Periodicals; 620.1122
• DOI: 10.1016/j.ijfatigue.2015.09.031
• Languages: English
• ISSNs: 0142-1123

Abstract

Highlights: The strip yield models implemented in NASGRO software are used. Constant constraint-loss model and variable constraint-loss model are compared. A new crack growth rate relation ( da / dN –Δ K eff ) is proposed for Al-2024T351. Comparisons between three different crack growth rate relations are made. Good predictions of fatigue lives are obtained under random loadings. Abstract: This paper is concerned with the application of the strip yield models implemented in NASGRO to estimate fatigue crack growth under random loading. The two different strip yield model options (constant constraint-loss (CCL) and variable constraint-loss (VCL)) implemented in the software are considered and compared. In addition, three crack grow rate relations, obtained from constant amplitude data, the NASGRO material database and the literature, were also considered and compared. The capacity of the models to estimate the fatigue life and variability is analyzed by comparing simulated results with experimental data of fatigue crack growth under different stationary Gaussian random load processes on compact, C ( T ), specimens of aluminum alloy 2024-T351. The analysis performed showed that both model options provide very similar good fatigue life predictions. The estimated fatigue lives are within ±13% of the test lives with the best option. The variability of the results due to the randomness of the load is also analyzed. In this case, the variable constraint-loss option provides better estimation than the constant constraint-loss option.