Symmetry-Based Automated Extraction of Microstructural Features: Application to Dendritic Cores in Single-Crystal Ni-Based Superalloys (Postprint)
Abstract
Serial sectioning methods continue to produce a wealth of image data for quantifying the three-dimensional nature of material microstructures. Here, we discuss a computational methodology for automated detection and 3D characterization of dendrite cores from images taken from slices of a production turbine blade made of a heat-treated single crystal Ni-based superalloy. The dendrite core locations are detected using an automated segmentation technique that incorporates information over multiple length scales and exploits the four-fold symmetry of the dendrites when viewed down the <001> growth direction. Additional rules that take advantage of the continuity of the dendrites from slice to slice help to exclude segmentation artifacts and improve dendrite core segmentation. The significance of this technique is that it can be extended to include any symmetry features such as mirror planes, improper rotations, or color symmetry, by using suitable matrix representations of these operations. For simplicity, only the four-fold rotation is included in this work.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2010
- Accession Number
- ADA520551
Entities
People
- A. H. Rosenberger
- Christopher F. Woodward
- J. P. Simmons
- M. A. Groeber
- M. A. Tschopp
- R. Fahringer
Organizations
- Air Force Research Laboratory