1 - 10 of 18 Results
ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.
Ruthenium is recovered from used nuclear fuel in an oxidizing environment by depositing the volatile RuO4 species onto a polymeric substrate.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
A novel method that prevents detachment of an optical fiber from a metal/alloy tube and allows strain measurement up to higher temperatures, about 800 C has been developed. Standard commercial adhesives typically only survive up to about 400 C.
Test facilities to evaluate materials compatibility in hydrogen are abundant for high pressure and low temperature (<100C).
The technologies provide a system and method of needling of veiled AS4 fabric tape.
Spherical powders applied to nuclear targetry for isotope production will allow for enhanced heat transfer properties, tailored thermal conductivity and minimize time required for target fabrication and post processing.
ORNL will develop an advanced high-performing RTG using a novel radioisotope heat source.
This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.