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.
How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.
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.
Sintering additives to improve densification and microstructure control of UN provides a facile approach to producing high quality nuclear fuels.
The technologies provide a system and method of needling of veiled AS4 fabric tape.
In order to avoid the limitations and costs due to the use of monolithic components for chemical vapor deposition, we developed a modular system in which the reaction chamber can be composed of a top and bottom cone, nozzle, and in-situ reaction chambers.
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.