Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/19327
Title: | Fatigue Behaviour of Forged Ti-6Al-4V Made From Blended Element Powder Metallurgy |
Authors: | Haynes, Noel |
Advisor: | Zurob, Hatem |
Department: | Materials Science and Engineering |
Keywords: | titanium;Ti-6Al-4V;powder;blended element;fatigue;porosity;forging;digital image correlation |
Publication Date: | 2016 |
Abstract: | A detailed metallurgical analysis was conducted to correlate microstructure to axial strain-controlled high cycle fatigue of Ti-6Al-4V forgings made from cold isostatic pressed and sintered preforms of blended element powder metallurgy (BEPM) incorporating hydrogenated titanium. Analysis included fractographic examination by SEM, microstructure examination by optical microscopy, texture examination via EBSD, chemical analysis and fatigue strain mapping via digital image correlation (DIC). From a literature review and observations of findings, factors that were of primary concern were: maximum pore diameter, primary α volume fraction, primary α width, primary α particle count, oxygen equivalency (OE) and texture of the α phase. The primary α volume fraction was found to have the single most influential effect on fatigue, whereby decreasing volume fraction increased fatigue life. Using statistical analysis, multivariable regression analyses were performed to evaluate combinations of predictors on fatigue life. The resulting outcome of volume fraction and maximum pore diameter, having a 3.3 to 1 weighting, was the most significant at predicting the fatigue response. Improving fatigue life of forged Ti-6Al-4V made from BEPM should thus be primarily focused on microstructure refinement. It is suggested future experimentation also consider the effects of the number of primary α particles and OE when modeling fatigue strength. |
URI: | http://hdl.handle.net/11375/19327 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Haynes_Noel_C_201605_MASc.pdf | Thesis | 2.92 MB | Adobe PDF | View/Open |
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