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This technology can help to increase number of application areas of Wireless Power Transfer systems. It can be applied to consumer electronics, defense industry, automotive industry etc.
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.
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).
The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.
The technologies polymer cellulose nanocomposite mats and process for making same.
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.
Faults in the power grid cause many problems that can result in catastrophic failures. Real-time fault detection in the power grid system is crucial to sustain the power systems' reliability, stability, and quality.
The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.
We present the design, assembly and demonstration of functionality for a new custom integrated robotics-based automated soil sampling technology as part of a larger vision for future edge computing- and AI- enabled bioenergy field monitoring and management technologies called