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NASA's System for In-situ Defect (e.g., porosity, fiber waviness) Detection in Composites During Cure consists of an ultrasonic portable automated C-Scan system with an attached ultrasonic contact probe. This scanner is placed inside of an insulated vessel that protects the temperature-sensitive components of the scanner. A liquid nitrogen cooling systems keeps the interior of the vessel below 38°C. A motorized X-Y raster scanner is mounted inside an unsealed cooling container made of porous insulation boards with a cantilever scanning arm protruding out of the cooling container through a slot. The cooling container that houses the X-Y raster scanner is periodically cooled using a liquid nitrogen (LN2) delivery system. Flexible bellows in the slot opening of the box minimize heat transfer between the box and the external autoclave environment. The box and scanning arm are located on a precision cast tool plate. A thin layer of ultrasonic couplant is placed between the transducer and the tool plate. The composite parts are vacuum bagged on the other side of the tool plate and inspected. The scanning system inside of the vessel is connected to the controller outside of the autoclave. The system can provide A-scan, B-scan, and C-scan images of the composite panel at multiple times during the cure process. The in-situ system provides higher resolution data to find, characterize, and track defects during cure better than other cure monitoring techniques. In addition, this system also shows the through-thickness location of any composite manufacturing defects during cure with real-time localization and tracking. This has been demonstrated for both intentionally introduced porosity (i.e., trapped during layup) as well processing induced porosity (e.g., resulting from uneven pressure distribution on a part). The technology can be used as a non-destructive evaluation system when making composite parts in in an oven or an autoclave, including thermosets, thermoplastics, composite laminates, high-temperature resins, and ceramics.

NASAs software technology uses an Image Quality Indicator (IQI)-based model that can predict whether cracks of a certain size can be detected, as well as a model that can provide appropriate conditions to optimize x-ray crack detection setup. Because this modeling software can predict minimum crack sizes that can be detected by a particular X-ray radiography testing setup, users can test various setups until the desired crack detection capabilities are achieved (predicted) by the modeling system. These flaw size parameter models use a set of measured inputs, including thickness sensitivity, detector modulation transfer function, detector signal response function, and other setup geometry parameters, to predict the minimum crack sizes detectable by the testing setup and X-ray angle limits for detecting such flaws. Current X-ray methods provide adequate control for detection of volumetric flaws but do not provide a high probability of detection (POD), and crack detection sensitivity cannot be verified for reliable detection. This results in reduced confidence in terms of crack detection. Given that these cracks, if undetected, can cause catastrophic failure in various systems (e.g., pressure vessels, etc.), verifying that X-ray radiography systems used for NDE can detect such cracks is of the utmost importance in many applications.