1 - 10 of 45 Results
ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
The technology will offer supportless DIW of complex structures using vinyl ester resin, facilitated by multidirectional 6 axis printing.
We have developed a novel extrusion-based 3D printing technique that can achieve a resolution of 0.51 mm layer thickness, and catalyst loading of 44% and 90.5% before and after drying, respectively.
Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.
The ever-changing cellular communication landscape makes it difficult to identify, map, and localize commercial and private cellular base stations (PCBS).
Wind turbine blades face a harsh environment in which erosion of the leading edge is a major factor for in-use maintenance. Current industrial practices to address this leading edge erosion are replacement of reinforcing materials upon significant damage infliction.
System and method for part porosity monitoring of additively manufactured components using machining
In additive manufacturing, choice of process parameters for a given material and geometry can result in porosities in the build volume, which can result in scrap.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
Through utilizing a two function splice we can increase the splice strength for opposing tows.
Contact:
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.
We proposed and developed a carbon nanofiber (CNF) suspension-based sizing agent, that resulted in improved interfacial, and mechanical properties. The CNF dispersed sizing agent can be applied in a relatively simpler way (by passing the continuous tow through it).