1 - 10 of 23 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.
High-gradient magnetic filtration (HGMF) is a non-destructive separation technique that captures magnetic constituents from a matrix containing other non-magnetic species. One characteristic that actinide metals share across much of the group is that they are magnetic.
Method to operate a compression ignition engine in dual fuel operation with premixed turbulent flame propagation from low to high loads.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
The invention discloses methods of using a reducing agent for catalytic oxygen reduction from CO2 streams, enabling the treated CO2 streams to meet the pipeline specifications.
An electrochemical cell has been specifically designed to maximize CO2 release from the seawater while also not changing the pH of the seawater before returning to the sea.
A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.
Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.