Abstract
ASTM C1678 outlines an approach to estimate the fracture strength of glasses and ceramics through the use of empirical relationships relating the strength to characteristic fractographic length-scales, such as the ‘mirror radius’. However, the process of measuring radii is subjective, and the relationship suggested by ASTM standards has been shown to be relatively inaccurate for flexural stress fields. This research introduces and tests a visual analysis algorithm to carry out the fractographic analysis of silicate glasses automatically and objectively. The fracture surfaces of various silicate glasses produced by both tensile and flexural stress fields were considered. First, optical images of the fracture surfaces were gathered and unique; descriptive features such as the shape of the ‘mirror-mist boundary’ were extracted using visual analysis tools. Next, a newly developed algorithm compared the processed images with a database comprised of fracture samples of known strengths, fracture toughness, stress fields, and geometric features. Lastly, dimensional analysis principles coupled with a broad, experimental set of over 2100 fracture surfaces was used to accurately estimate the strengths of the imaged fracture surfaces.
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Notes
Toolbox used: Curve Fitting (version 3.4.11), Image Processing (version 11.1), Signal Processing (version 8.4), and Symbolic Math (version 8.5).
Abbreviations
- \(\sigma_{{\text{f}}}\) :
-
Fracture strength, MPa
- A :
-
Mirror constant, MPa√m
- R i :
-
Mirror radius, m
- H :
-
Thickness, m
- K Ic :
-
Fracture toughness, MPa√m
- D * :
-
Fractal increment
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Xiao, Y., Dugnani, R. Automated Quantitative Fractography of Silicate Glasses with Visual Analysis. J. of Materi Eng and Perform 30, 3612–3623 (2021). https://doi.org/10.1007/s11665-021-05697-1
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DOI: https://doi.org/10.1007/s11665-021-05697-1