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ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
The lattice collimator places a grid of shielding material in front of a radiation detector to reduce the effect of background from surrounding materials and to enhance the RPM sensitivity to point sources rather than distributed sources that are commonly associated with Natur
New demands in electric vehicles have resulted in design changes for the power electronic components such as the capacitor to incur lower volume, higher operating temperatures, and dielectric properties (high dielectric permittivity and high electrical breakdown strengths).
The first wall and blanket of a fusion energy reactor must maintain structural integrity and performance over long operational periods under neutron irradiation and minimize long-lived radioactive waste.
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.
Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.