Fractographic analysis of silicate glasses by computer vision |
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| Affiliation: | 1. The State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, 430070, China;2. Guangxi Key Laboratory of Information Materials, Guilin University of Electronic Technology, Guilin, 541004, China;1. Universidad de Málaga, Departamento de Química Inorgánica, 29071, Málaga, Spain;2. Universidad de Málaga, Departamento de Física Aplicada I, 29071, Málaga, Spain;1. Engineering Ceramics Research Group, Korea Institute of Materials Science, 797 Changwondaero, Changwon, Gyeongnam, 51508, Republic of Korea;2. Department of Nano Materials Engineering, Kyungnam University, Changwon, Republic of Korea;3. Agency for Defence Development, Yuseong P.O. Box 35, Daejeon, 34186, Republic of Korea;1. Key Laboratory for Anisotropy and Texture of Materials (Ministry of Education), Northeastern University, Shenyang, Liaoning 110819, China;2. Institute of Ceramics and Powder Metallurgy, School of Materials Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China;3. College of New Energy, Bohai University, Jinzhou, Liaoning 121007, China;4. Research Center for Functional Materials, National Institute for Materials Science, 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan |
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| Abstract: | ASTM C1678 describes the state-of-the-art's fractographic techniques to estimate the fracture strength of glasses and ceramics through empirical, strength vs. fracture mirror length relationships. However, the methodology is subjective and only applicable to a few loading scenarios and relatively pristine fracture surfaces. This work presents a semi-automated, alternative approach to objectively estimate the strength of silicate glasses for ampler loading and geometric scenarios. The proposed method relies on a baseline set of fracture surface profilometry-scans gathered on samples of known strengths. A computer vision-based algorithm compares relevant, topological features extracted from the baseline set to the features on the fracture surfaces investigated. An empirical relationship based on over 2,100 fractured silicate specimens is used to compute the strength of the trial sample. The proposed scheme could accurately estimate the strength of specimens beyond the capacity of ASTM C1678, such as in chemically strengthened glasses and fracture surfaces displaying significant damage. |
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| Keywords: | Fractography Silicate glass Fracture strength Computer vision Chemically strengthened glass |
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