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.
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.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
Fusion reactors need efficient systems to create tritium fuel and handle intense heat and radiation. Traditional liquid metal systems face challenges like high pressure losses and material breakdown in strong magnetic fields.
The traditional window installation process involves many steps. These are becoming even more complex with newer construction requirements such as installation of windows over exterior continuous insulation walls.
This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.
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).
Technologies for optimizing prefab retrofit panel installation using a real-time evaluator is described.