Modeling approach for a unified crack growth model in short and long fatigue crack regimes. (November 2019)

• Record Type: Journal Article
• Authors: Bang, D.J.; Ince, A.; Noban, M.
• Is Part Of: International journal of fatigue. Volume 128(2019)
• Publication Date: 2019-11
• Subjects: Short crack -- Long crack -- Fatigue crack growth behavior -- UniGrow model -- Fatigue crack growth model; Materials -- Fatigue -- Periodicals; Materials -- Fatigue; Periodicals; 620.1122
• DOI: 10.1016/j.ijfatigue.2019.06.042
• Languages: English
• ISSNs: 0142-1123

Abstract

Highlights: The recently proposed crack growth model is further improved. The modeling approach incorporates the integration of short and long propagation behavior in a unified manner. Fatigue crack growth data sets of eight different materials are used for the model validation. The model accurately predicts the crack growth rates in long crack regime. The model could not accurately predict the variability of short crack growth behavior. Abstract: In this paper, the recently proposed UniGrow model modification is further improved and a modeling framework of the proposed model is developed to account for both the short and long crack growth behavior. The modeling approach incorporates the integration of short and long propagation into the UniGrow crack growth model to address the short and long crack growth in a unified manner. A systematic study is performed to further validate the proposed modeling approach and assess its prediction capabilities and shortcomings to predict crack growth behavior of short and long cracks. The proposed crack growth model is assessed by first comparing the predicted fatigue crack growth results with long crack growth data sets of 7010-T7, 2024-T3, 2324-T3, 7050-T7 and 7075-T6 aluminum alloys at four different R ratios; The results are further assessed by comparison of short and long crack growth predictions to both short and long crack growth data sets of 2090-T8E41, LC9cs aluminum alloys and Ti-6Al-4V titanium alloys at two different R-ratios. The model showed good correlation with long crack data sets of 7010-T7, 2024-T3, 2324-T3, 7050-T7 and 7075-T6 and predicted crack growth results matched well with the nonlinearity of four material data sets at four different R-ratios. The results revealed that even though the proposed model was in good agreement with long crack data sets of 2090-T8E41, LC9cs aluminum alloys and Ti-6Al-4V titanium alloys at two different R-ratios, the model did not correlate well with the short crack data sets of these three materials and to accurately account for the variability of short crack growth.