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dc.contributor.authorZoeger, Christian
dc.description.abstractComposite materials are being used due to the fact that they are lightweight and their properties can be tailored to maximize the overall structural performance. As such, the testing of these materials is of major importance. Testing notched coupons is beneficial as the parts are optimized for damage tolerance thereby reducing time and cost of testing. Additional advantages of these tests are that machining of the coupon is not critical, the location of failure is known, and notched samples simulate worst case defects. Digital Image Correlation (DIC) is used to measure strain. With the use of two high resolution cameras, images of a coupon were captured as the load was applied. As the coupon is deformed by the applied load, the stochastic pattern painted onto the coupon also deformed. This deformation is then correlated from one image to the other, using an algorithm that tracks the pattern and transforms it into measured strain. DIC allows! for full-field, quantitative visualization of strains that then correlate to stress concentrations. This research hypothesized that the amount of testing required to establish compressive material properties could be reduced by using DIC. A unique coupon based on standardized open hole compression (OHC) and compression after impact (CAI) test methods was used. Notched IM7 carbon fiber/RS8 Bismaleimide coupons with symmetric laminates were tested. The load was recorded at the same time each image set was captured, allowing for the calculation of stress. Then, several material properties were found and compared to published values. Full field strain and stress at failure matched the published values. In addition, static fatigue testing was performed. While no plastic deformation is noted at this loading during testing-to-failure, plastic strains were noted as high as 0.2% strain with load durations as short as 60 minutes. Overall, these results indicate that DIC may effectively be used for the visualization of stress concentrations while quantifying defect and material properties. Adviser: Jared W. Nelson, Engineeringen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.subjectMaterial Propertiesen_US
dc.subjectCarbon Fiberen_US
dc.subjectCompression testen_US
dc.subjectDamage Progressionen_US
dc.subjectResearch Subject Categories::TECHNOLOGY::Engineering physics::Material physics with surface physicsen_US
dc.titleUse of Digital Image Correlation to Find Compressive Material Properties of Carbon Fiber Compositesen_US

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Attribution-NonCommercial-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States