The objective of the proposed research is to quantitatively characterize and understand the effect of oxidation of composite constituents on the initiation and accumulation of damage (including crack opening displacements and densities), as a result of factors including the applied stress, oxidation degree, and surrounding composite architecture. My research will utilize novel experimental methodologies including SEM-DIC, Acoustic Emission, and Electrical Resistance measurements to provide guidelines on how to mitigate premature component failure through the design of damage-tolerant architectures. I will first perform a suite of room-temperature monotonic and dwell fatigue-cracking studies, and use the resulting data to guide elevated temperature testing. I will combine automated SEM, chemically functionalized self-assemblies of nanoparticles on CMC specimen surfaces, and spatially and temporally distortion-corrected digital image correlation, to enable the acquisition of large, information-rich data sets with extremely high resolution and accuracy. Adopting this new approach towards the characterization of CMCs will allow me to integrate statistical and unsupervised learning methods with materials science in order to examine stochastic behaviors, such as the effect of subsurface composite architecture, on damage accumulation under various oxidative and thermo-mechanical loads.