1 - 10 of 13 Results
ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
In nuclear and industrial facilities, fine particles, including radioactive residues—can accumulate on the interior surfaces of ventilation ducts and equipment, posing serious safety and operational risks.
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.
The invention presented here addresses key challenges associated with counterfeit refrigerants by ensuring safety, maintaining system performance, supporting environmental compliance, and mitigating health and legal risks.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
Through the use of splicing methods, joining two different fiber types in the tow stage of the process enables great benefits to the strength of the material change.
This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.
Knowing the state of charge of lithium-ion batteries, used to power applications from electric vehicles to medical diagnostic equipment, is critical for long-term battery operation.
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).