| Damage in materials is a complex and stochastic process bridging several time and length scales. This dissertation focuses on investigating the damage process in a particular class of precipitate-hardened aluminum alloys which is widely used in automotive and aerospace applications. Most emphasis in the literature has been given either on their ductility for manufacturing purposes or fracture for performance considerations. In this dissertation, emphasis is placed on using nondestructive evaluation (NDE) combined with mechanical testing and characterization methods applied at a scale where damage incubation and initiation is occurring. Specifically, a novel setup built inside a Scanning Electron Microscope (SEM) and retrofitted to be combined with characterization and NDE capabilities was developed with the goal to track the early stages of the damage process in this type of material. The characterization capabilities include Electron Backscatter Diffraction (EBSD) and Energy Dispersive Spectroscopy (EDS) in addition to X-ray micro-computed tomography (mu-CT) and nanoindentation, in addition to microscopy achieved by the Secondary Electron (SE) and Back Scatter Electron (BSE) detectors. The mechanical testing inside the SEM was achieved with the use of an appropriate stage that fitted within its chamber and is capable of applying both axial and bending monotonic and cyclic loads. The NDE capabilities, beyond the microscopy and mu-CT, include the methods of Acoustic Emission and Digital Image Correlation (DIC). This setup was used to identify damage precursors in this material system and their evolution over time and space. The experimental results were analyzed by a custom signal processing scheme that involves both feature-based analyses as well as a machine learning method to relate recorded microstructural data to damage in this material. Extensions of the presented approach to include information from computational methods as well as its applicability to other material systems are discussed. |
