Application of a microstructural characterization uncertainty quantification framework to Widmanstätten⍺-laths in additive manufactured Ti-6Al-4V

GT Loughnane, SL Kuntz, N Klingbeil, JM Sosa, J Irwin… - 2015 - repositories.lib.utexas.edu
GT Loughnane, SL Kuntz, N Klingbeil, JM Sosa, J Irwin, AR Nassar, EW Reutzel
2015repositories.lib.utexas.edu
This work applies statistical analysis and uncertainty quantification tools developed for
characterizing virtual microstructures in three dimensions to a two-dimensional experimental
investigation of Ti-6Al-4V Widmanstätten⍺-lath thicknesses obtained from back-scattered
electron (BSE) or electron back-scatter diffraction (EBSD) images on two thin-walled
samples manufactured via the LENS® process. The Materials Image Processing and
Automated Reconstruction (MIPAR™) software optimizes unique recipes for conversion of …
Abstract
This work applies statistical analysis and uncertainty quantification tools developed for characterizing virtual microstructures in three dimensions to a two-dimensional experimental investigation of Ti-6Al-4V Widmanstätten⍺-lath thicknesses obtained from back-scattered electron (BSE) or electron back-scatter diffraction (EBSD) images on two thin-walled samples manufactured via the LENS® process. The Materials Image Processing and Automated Reconstruction (MIPAR™) software optimizes unique recipes for conversion of the BSE or EBSD images to binary data, and subsequently computes the inverse of the linear intercept for each⍺-lath. Mean⍺-lath thicknesses and discrete probability density functions (PDFs) of inverse intercepts are used to make quantitative comparisons of⍺-lath structures at different heights throughout the thin walls. Real-time thermal data collected during the LENS® experiment is then compared to quantitative microstructural results in order to determine trends between⍺-lath structures, thermal gradients, and melt pool areas across experimental process parameters.
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