1 - 10 of 12 Results
ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
A pressure burst feature has been designed and demonstrated for relieving potentially hazardous excess pressure within irradiation capsules used in the ORNL High Flux Isotope Reactor (HFIR).
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.
This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.
The use of Fluidized Bed Chemical Vapor Deposition to coat particles or fibers is inherently slow and capital intensive, as it requires constant modifications to the equipment to account for changes in the characteristics of the substrates to be coated.
Current technology for heating, ventilation, and air conditioning (HVAC) and other uses such as vending machines rely on refrigerants that have high global warming potential (GWP).
This technology is a strategy for decreasing electromagnetic interference and boosting signal fidelity for low signal-to-noise sensors transmitting over long distances in extreme environments, such as nuclear energy generation applications, particularly for particle detection.
A diver-operated system brings safe and portable imaging to a new operating environment – underwater at depths up to 300 feet.