Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

You searched for id:"oai:etd.ohiolink.edu:osu1555523646156822". One record found.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


The Ohio State University

1. Brust, Alexander Frederick. Applications of Graph Cutting for Probabilistic Characterization of Microstructures in Ferrous Alloys.

Degree: PhD, Materials Science and Engineering, 2019, The Ohio State University

Processing of martensitic steels requires a thermally driven phase transformation into the austenite phase field, where rapid cooling initiates the diffusionless transformation into martensite. The resultant microstructural constituent is a hard, brittle phase that requires subsequent heat treatment to soften the material for optimized mechanical properties. Although the transformation microstructure has the largest influence on these mechanical properties, the prior austenite microstructure has been shown to significantly affect the final product material in the form of ductile to brittle fracture occurrence, classification of creep and cavitation sites, increasing martensite packet and block sizes resulting in Hall-Petch effects, and temper embrittlement. Therefore, reconstruction of the prior austenite phase field can help optimize both the processing of a sample steel or binary ferrous alloy and predicative examinations on the material. However, analysis of the austenite to martensite transformation is hindered by the large volume of noise associated with the transformation. This can be attributed to the scale of the transformation, which results in a single prior austenite grain producing up to 24 martensitic variants; the plasticity associated with the massive formation of martensite; variations in the orientation relationship across variable compositions and morphologies; errors associated with the EBSD-indexing of the transformation microstructure; and annealing twins forming across the prior austenite microstructure. Due to the inherent noise associated with the transformation, modern reconstruction algorithms using point-to-point or flood-fill algorithms struggle to produce accurate and consistent reconstructions of the austenite microstructure. We therefore propose a probabilistic approach to austenite reconstruction in steels and ferrous alloys based on the graph cutting algorithm. This technique can be applied to a number of inverse problems in materials science, such as image segmentation, microstructure phase and constituent segmentation, atomic cluster identification from atom probe tomography data sets, and the reconstruction of the parent microstructure from the EBSD-indexed post-transformation data set.The chosen algorithm used an energy-minimization technique known as graph cutting to perform the reconstructions. In order to most properly describe the algorithm, information related to the misorientation relationships between martensite variants associated with the same prior austenite grain or twin were utilized. Additionally, an accurate and automated measurement of the orientation relationship for the desired steel data sets was performed through a Bayesian implementation and used conditionally within the reconstruction algorithm. This information was used to perform automated reconstructions on the prior austenite microstructure from transformation martensite. Analysis of a number of steel and binary ferrous alloy data sets with variable orientation relationships was then performed to assess… Advisors/Committee Members: Niezgoda, Stephen (Advisor).

Subjects/Keywords: Materials Science; Engineering; Martensite; Austenite; Steel; Austenite Reconstruction; Crystallography; Misorientation; Graph Cutting; Image Segmentation; Clustering; Microstructure; Transformation; Variant; EBSD Analysis; Packet Segmentation; Sub-block Block Packet Boundary

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Brust, A. F. (2019). Applications of Graph Cutting for Probabilistic Characterization of Microstructures in Ferrous Alloys. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1555523646156822

Chicago Manual of Style (16th Edition):

Brust, Alexander Frederick. “Applications of Graph Cutting for Probabilistic Characterization of Microstructures in Ferrous Alloys.” 2019. Doctoral Dissertation, The Ohio State University. Accessed September 21, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555523646156822.

MLA Handbook (7th Edition):

Brust, Alexander Frederick. “Applications of Graph Cutting for Probabilistic Characterization of Microstructures in Ferrous Alloys.” 2019. Web. 21 Sep 2019.

Vancouver:

Brust AF. Applications of Graph Cutting for Probabilistic Characterization of Microstructures in Ferrous Alloys. [Internet] [Doctoral dissertation]. The Ohio State University; 2019. [cited 2019 Sep 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1555523646156822.

Council of Science Editors:

Brust AF. Applications of Graph Cutting for Probabilistic Characterization of Microstructures in Ferrous Alloys. [Doctoral Dissertation]. The Ohio State University; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1555523646156822

.