Fatigue crack characterisation in 2024-T351 aluminium alloy through SEM observation combined with the CJP model. (January 2023)

• Record Type: Journal Article
• Authors: Robles, J.M.; Vasco-Olmo, J.M.; Cruces, A.S.; Diaz, F.A.; James, M.N.; Lopez-Crespo, P.
• Is Part Of: International journal of fatigue. Volume 166(2023)
• Publication Date: 2023-01
• Subjects: Fatigue crack growth -- CJP model -- Digital Image Correlation -- Scanning Electron Microscopy; Materials -- Fatigue -- Periodicals; Materials -- Fatigue; Periodicals; 620.1122
• DOI: 10.1016/j.ijfatigue.2022.107279
• Languages: English
• ISSNs: 0142-1123

Abstract

Highlights: First time that CJP model is used combined with SEM information in order to characterize the fatigue behaviour of aluminium alloy 2024-T351. Application of Digital Image Correlation for study of fatigue in metals. Exhaustive characterization of the fracture surface with SEM and extraction of experimental data for fatigue behaviour characterization. Abstract: This work characterises crack growth in AA2024-T315 by combining different methods to further increase the reliability of the results. The Christopher-James-Patterson (CJP) model was fitted to experimental data obtained by digital image correlation (DIC). The effective value of the CJP stress intensity factors were successfully correlated with the ΔK-da/dN curve as obtained with Scanning Electron Microscopy measurements of the depth of striations on the fracture surface. This approach based on fitting the CJP model with DIC data and SEM observations allowed estimation of opening and closure loads and allowed the propagation rate and fracture mode to be effectively characterised.