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Microstructural and mechanical characterization of variability in porous advanced ceramics using X-ray computed tomography and digital image correlation.

  • Author(s) / Creator(s)
  • This paper explores microstructural and mechanical variability in porous ceramics, combining advanced X-ray computed tomography (XCT) and digital image correlation (DIC) techniques to characterize an alumina material. The results show low variability in microstructure, with median pore size values for this alumina ranging from 16.0 μm to 17.2 μm across ten samples. Spatial analysis showed internal pores are regularly distributed, and though spacing was found to be largely independent of pore size, the variability in spacing was shown to be greater for smaller pores. Mechanical results show a strain-rate dependence and greater scatter at quasi-static rates, with the coefficient of variation for compressive strength and failure strain decreasing from 10.28% and 10.23% at quasi-static to 5.20% and 4.17% at dynamic rates. In view of the consistency demonstrated in the microstructure, the difference in variability between the quasi-static and dynamic mechanical properties is attributed to variability in testing conditions (e.g., misalignment of platens) and the activation of a greater number of pores in dynamic compression. In summary, these results motivate the use of new spatial characterization parameters via XCT for links to manufacturing, the integration of realistic microstructures into computational models, and focus on the role of defect distributions in dynamic compressive failure events.

  • Date created
    2019-01-01
  • Subjects / Keywords
  • Type of Item
    Article (Draft / Submitted)
  • DOI
    https://doi.org/10.7939/r3-w70g-2y79
  • License
    Attribution-NonCommercial-NoDerivatives 4.0 International
  • Language
  • Citation for previous publication
    • Lo, Calvin, Tomoko Sano, and James D. Hogan. "Microstructural and mechanical characterization of variability in porous advanced ceramics using X-ray computed tomography and digital image correlation." Materials Characterization 158 (2019): 109929. https://doi-org/10.1016/j.matchar.2019.109929