The objectives of this ongoing research project focus on health monitoring and data analytics of concrete slabs with alkali-silica reaction (ASR) degradation. Researchers at Vanderbilt University cast a controlled concrete slab with four pockets of reactive aggregates (pure silica, wells, placitas, and spratt) and cured in representative conditions to accelerate degradation due to ASR. A set of four concrete samples were also cast and cured at the University of Alabama for ASR testing. Of these four samples, two slabs contained reactive aggregates while the other two had the non-reactive aggregate counterparts mixed throughout the samples. Vibro-acoustic testing was used on these slabs to locate ASR damage within the reactive samples. Vibro-acoustic modulation (VAM) is a vibration-based nondestructive examination (NDE) method that utilizes signatures of nonlinear dynamic interactions on contact surfaces of crack or delamination damage to detect and localize the damage. VAM analysis was conducted on both the Vanderbilt and Alabama samples using multiple variables for damage detection and localization. This report discusses in detail the results from the data analysis of the vibroacoustic testing on concrete slabs cured at Vanderbilt University and the University of Alabama. Results for damage localization are dependent on multiple variables used in the vibro-acoustic modulation experiments. A major focus of this report is to quantify the uncertainty in the diagnosis due to multiple factors and uncertainty sources. Researchers applied the uncertainty quantification methodology presented in this report to VAM-based diagnosis and prognosis. However, the methodology is general, and is capable of being applied to multiple techniques that collect spatially distributed data. Future work needs to investigate the incorporation of uncertainty quantification in developing a robust Prognostics and Health Management framework. Digital image correlation is a three-dimensional, full-field, optical NDE technique to measure contour, deformation, vibration, and strain. This report also discusses the application of the digital image correlation technique to study ASRrelated degradation on a large concrete specimen at the University of Tennessee. Research observations are collected and presented in this report. v