Quantification of Alpha Lath in Ti-6Al-4V using OpenCV

Microstructure quantification is becoming an important ingredient for predicting material behavior. Here, we present a methodology to quantify 2-phase (α + β) basketweave Ti-6Al-4V microstructures printed by a wire feed directed energy deposition (DED) process. The method focuses on automated quantification of features, such as α lamella thickness and volume fractions of both (α + β) phases, to ensure repeatability and to enable comparison across a wide array of images for subsequent analysis using pre-defined open access image processing libraries in the Python Language. A stereological correction was made for α-lath spacing based on the work of Collins et al., while also assuming area fraction (in 2D images) as equivalent to volume fraction of (α + β) phases. The methodology is expected to be generally applicable to lamellar microstructures and to other microstructure types via adaptation of the methodology for the features in question.