Improved Damage Characterization of Carbon-Carbon with Micro-X-Ray Computed Tomography
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composite materials testing↗
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A Procedure to Quantify Interlaminar Damage in Refractory Composites by In-Situ Micro-X-Ray Computed Tomography
Refractory composites are relevant for hot-structure applications on re-entry vehicles. To develop optimized high-performance hot structures, accurate material property data is required. Material properties that often limit design in two-dimensional (2-D) composites are interlaminar strengths. A better understanding of the failure mechanisms for interlaminar shear (ILS), interlaminar tension (ILT), and curved-beam interlaminar tension (CB-ILT) tests can provide insight on improving the design and fabrication of refractory composites. In-situ tests were performed to capture the progressive failure in American Society for Testing and Materials (ASTM) sized ILS (ASTM D3846), ILT (ASTM D7291), and CB-ILT (ASTM D6415) specimens. Before measuring internal damage of refractory composites specimens, the methodology of the test setup warrants a complete and thorough discussion. Detail on the test procedure, test stand design, micro-x-ray computed tomography (CT) configuration, data processing, and CT system uncertainty is discussed. Through keeping the many parameters of the CT system consistent, the uncertainty of the CT system was minimized, optimizing the quality of measurements. The overall quality of a CT scan can be quantified by three metrics: voxel resolution, minimal voxel resolution feature detection, and directional variability. A better understanding of the progressive failure mechanisms of refractory composites is provided by the results of both the present discussion and the one found in the accompanying paper titled “Analysis of Interlaminar Damage in Refractory Composites by In-Situ Micro-X-Ray Computed Tomography”.
In-situ micro-x-ray CT↗
Synchrotron‐source micro‐x‐ray computed tomography for examining butterfly eyes
Comparative anatomy is an important tool for investigating evolutionary relationships among species, but the lack of scalable imaging tools and stains for rapidly mapping the microscale anatomies of related species poses a major impediment to using comparative anatomy approaches for identifying evolutionary adaptations. We describe a method using synchrotron source micro-x-ray computed tomography (syn-μXCT) combined with machine learning algorithms for high-throughput imaging of Lepidoptera (i.e., butterfly and moth) eyes. Our pipeline allows for imaging at rates of ~15 min/mm 3 at 600 nm 3 resolution. Image contrast is generated using standard electron microscopy labeling approaches (e.g., osmium tetroxide) that unbiasedly labels all cellular membranes in a species-independent manner thus removing any barrier to imaging any species of interest. To demonstrate the power of the method, we analyzed the 3D morphologies of butterfly crystalline cones, a part of the visual system associated with acuity and sensitivity and found significant variation within six butterfly individuals. Despite this variation, a classic measure of optimization, the ratio of interommatidial angle to resolving power of ommatidia, largely agrees with early work on eye geometry across species. We show that this method can successfully be used to determine compound eye organization and crystalline cone morphology. Our novel pipeline provides for fast, scalable visualization and analysis of eye anatomies that can be applied to any arthropod species, enabling new questions about evolutionary adaptations of compound eyes and beyond.
59 BASIC BIOLOGICAL SCIENCES↗