Understanding the Role of Glaze Layer With Multiple Surface Characterization Techniques Aligned by Computer Vision Algorithms

Zhang, Chuchu; Neu, Richard W.

Title:

Understanding the Role of Glaze Layer With Multiple Surface Characterization Techniques Aligned by Computer Vision Algorithms

dc.contributor.author	Zhang, Chuchu
dc.contributor.author	Neu, Richard W.
dc.contributor.corporatename	Georgia Institute of Technology. Center for Career Discovery and Development	en_US
dc.contributor.corporatename	Georgia Institute of Technology. Office of Graduate Studies	en_US
dc.contributor.corporatename	Georgia Institute of Technology. Office of the Vice Provost for Graduate Education and Faculty Development	en_US
dc.contributor.corporatename	Georgia Institute of Technology. Student Government Association	en_US
dc.contributor.corporatename	Georgia Institute of Technology. School of Materials Science and Engineering	en_US
dc.contributor.corporatename	Georgia Institute of Technology. George W. Woodruff School of Mechanical Engineering	en_US
dc.date.accessioned	2021-10-12T17:25:23Z
dc.date.available	2021-10-12T17:25:23Z
dc.date.issued	2021-02-10
dc.description	Presented online at the Georgia Tech Career, Research, and Innovation Development Conference (CRIDC), February 9, 2021.	en_US
dc.description	The Career, Research, and Innovation Development Conference (CRIDC) is designed to equip on-campus and online graduate students with tools and knowledge to thrive in an ever-changing job market.	en_US
dc.description.abstract	A glaze layer that significantly reduces friction and wear has been found on the surface of many Fe-, Cr-, and Ni-based material systems undergoing fretting/sliding at elevated temperature. In this work we proposed a novel way to understand the role of glaze layer using computer vision algorithms. Two workflows, one for quantitative glaze layer identification and the other for image alignment, have been developed. For glaze layer identification, we used computer vision concepts that considers the color and reflectiveness of glaze layer under optical microscope (OM). For image alignment, we developed a strategy to conduct pixel-to-pixel alignment of images acquired by multiple techniques (e.g., OM, scanning electron microscopy, 3D optical profilers) with sub-pixel error. As such, the correlation between the height map and locations of the glaze layer within the wear scar can be readily determined. These methods are used to evaluate wear scars and quantify glaze layer coverage on 310S stainless steel under like-on-like, cylinder-on-flat fretting conditions from 20°C to 700°C. The glaze layer is found to always occupy relatively high locations within wear scar, and the height difference between glaze layer and none-glaze layer is statistically significant. The results provide evidence that severe-to-mild wear transition resulted from spreading of glaze layer coverage, and glaze layer may reduce friction and wear by reducing real contact area. The open-source workflows we developed are powerful tools that enable multi-spectrum analysis without upgrading existing characterization tools, which can be easily transferable to all other applications in academia and industry.	en_US
dc.identifier.uri	http://hdl.handle.net/1853/65388
dc.language.iso	en_US	en_US
dc.publisher	Georgia Institute of Technology	en_US
dc.relation.ispartofseries	CRIDC
dc.subject	Image analysis	en_US
dc.subject	Computer vision	en_US
dc.subject	High temperature wear	en_US
dc.subject	Material characterization	en_US
dc.subject	Fretting	en_US
dc.title	Understanding the Role of Glaze Layer With Multiple Surface Characterization Techniques Aligned by Computer Vision Algorithms	en_US
dc.type	Text
dc.type.genre	Poster
dspace.entity.type	Publication
local.contributor.author	Neu, Richard W.
local.contributor.corporatename	Office of Graduate Education
local.relation.ispartofseries	Career, Research, and Innovation Development Conference
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relation.isOrgUnitOfPublication	d9390dfc-6e95-4e95-b14b-d1812f375040
relation.isSeriesOfPublication	4976ff66-25a7-4118-9c75-a356abde9732