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Advisory Committee Chair

Charles Monroe

Advisory Committee Members

Robin Foley

John Griffin

Document Type

Thesis

Date of Award

2015

Degree Name by School

Master of Science in Materials Engineering (MSMtE) School of Engineering

Abstract

Microstructural analysis of aluminum high pressure die castings (HPDC) is challenging and time consuming. Automating the stereology method is an efficient way in obtaining quantitative data; however, validating the accuracy of this technique can also pose some challenges. In this research, a semi-automated algorithm to quantify microstructural features in aluminum HPDC was developed. Analysis was done near the casting surface where it exhibited fine microstructure. Optical and Secondary electron (SE) and backscatter electron (BSE) SEM images were taken to characterize the features in the casting. Image processing steps applied on SEM and optical micrographs included median and range filters, dilation, erosion, and a hole-closing function. Measurements were done on different image pixel resolutions that ranged from 3 to 35 pixel/µm. Pixel resolutions below 6 px/µm were too low for the algorithm to distinguish the phases from each other. At resolutions higher than 6 px/µm, the volume fraction of primary α-Al and the line intercept count curves plateaued. Within this range, comparable results were obtained validating the assumption that there is a range of image pixel resolution relative to the size of the casting features at which stereology measurements become independent of the image resolution. Volume fraction within this curve plateau was consistent with the manual measurements while the line intercept count was significantly higher using the computerized technique for all resolutions. This was attributed to the ragged edges of some primary α-Al; hence, the algorithm still needs some improvements. Further validation of the code using other castings or alloys with known phase amount and size may also be beneficial.

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