Investigation of particle fracture during fatigue of aluminum 2024. (June 2018) - Wisner, B.; Kontsos, A.
Highlights: Particle fracture of precipitate-hardened Al2024-T3 alloys was investigated during fatigue using an experimental approach combining in situ SEM, DIC, and AE monitoring. This is the first time to the authors' best knowledge that such observations are made directly at the scale that particle fracture occurs combining nondestructive measurements provided by optical, acoustic, and X-ray methods. Direct strain measurements both on and around these particles made possible by leveraging the capabilities of the optical method used demonstrated that such particles are loaded during specimen loading and consequently fracture. Fractured particles were found to then nucleate cracks in the soft matrix grains, in cases where the particles existed near grain boundaries. The chemical composition of the particle was found to play a role on their fracture. Xray μCT confirmed the evolution of particle fracture during cyclic loading. Acoustic Emission provided further insights on the evolution of particle fracture as a function of applied loading. Abstract: A significant portion of the mechanical energy that enters into a material subjected to fatigue is expended to nucleate local, early-state damage which is distinct from later observed catastrophic type damage frequently targeted in fatigue investigations. Therefore, identification of early signs of fatigue damage combined with means to monitor its evolution is crucial for understanding the influence of material microstructure on the development of progressive pre-failure sites that can ultimately lead to conditions that favor the development of fatigue damage. In this context, in situ scanning electron microscope (SEM) testing combined with microstructure-sensitive nondestructive evaluation (NDE) is leveraged, in this article, to allow the direct observation of fatigue damage incubation in a precipitate-hardened aluminum alloy, Al 2024-T3. To validate surface observations of such early signs of damage, X-ray Micro-Computed Tomography (μ-CT) scans were made to investigate the relation between particle size and chemical balance with local grain structure and crystallography. In addition, an effort was made to explore the effect of specimen geometry and loading schemes on the occurrence of particle fracture activity as well its evolution throughout the early stages of the specimen life. Furthermore, a machine learning approach was developed in an attempt to post-process the available NDE data and relate it to particle fracture activity.