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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.

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.

Misalignment issues of the PWPT system have been addressed. The intercell power transformer has been introduced in order to improve load sharing of the system during a mismatch of the primary single-phase coil and the secondary multi-phase coils.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

An ORNL invention proposes using 3D printing to make conductors with space-filling thin-wall cross sections. Space-filling thin-wall profiles will maximize the conductor volume while restricting the path for eddy currents induction.

The invention is related to the implementation of an bi-directional and isolated electric vehicle charger. The bidirectionality allows the electric vehicles to support the grid in case of disturbances thereby reducing the stress on the existing infrastructure.

This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.

Real-time tracking and monitoring of radioactive/nuclear materials during transportation is a critical need to ensure safety and security. Current technologies rely on simple tagging, using sensors attached to transport containers, but they have limitations.

Additively manufacturing of the windings with a conductor distributed in the cross-section according to the Hilbert curve provides many benefits as it allows for the reduction of the high-frequency losses due to the reduction of the effective winding conductor size.